Medical Laboratory Observer - March 2024

MLO-online.com

March 2024

Vol 56, No. 3

™ The Peer-Reviewed Management Source for Lab Professionals since 1969

State of the Industry Laboratory data

CE: Artificial intelligence in healthcare Page 8

analytics Page 22

LAB INNOVATOR

Harvey Kaufman, MD Senior Medical Director, Quest Diagnostics

PLUS

Pre-eclampsia diagnosis Page 14 Diabetes and heart failure Page 20

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IN THIS ISSUE...

4 6

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From the editor The observatory

March 2024 | Vol. 56, No. 3

A

S S

CONTINUING EDUCATION

8

Artificial intelligence in healthcare...Friend or foe?

By Anthony Kurec, MS, MASCP, H(ASCP)DLM

A P

CLINICAL ISSUES

14

Complications and diagnosis of pre-eclampsia

By Jason Armstrong

La in

INFECTION DIAGNOSTICS

8

18

Closing clinical gaps in cervical cancer

T st is pr

By Allison McMullen, PhD D (ABMM)

LAB MANAGEMENT

19

The importance of prognostic testing for patients with chronic lymphocytic leukemia

By Mark Kruzel, MD, MBA

EDUCATION

18

20

Diabetes and heart failure: Understanding the role of cardiac biomarker testing

By Dagmar Schumacher, PhD

STATE OF THE INDUSTRY

22

Medical labs increase use of performance analytics; Target strategic IT investments

By Kara Nadeau

MOLECULAR DIAGNOSTICS

22

28

Liquid biopsy — The rapidly evolving technique in oncology

By Rajasri Chandra, MS, MBA

SPECIAL FOCUS

30

A new international standard for healthcare organization management

By Dr. Donna M. Gillespie and Sheila Woodcock, MBA

PRODUCT FOCUS

28

32

Vitamin D

LAB INNOVATOR

36

Innovation is a constant

By Christina Wichmann

DEPARTMENTS

35 36

C

Index of advertisers

© co pro an

ON THE COVER: Pixtum, Illustrator de la Monde, RLT_Images, & Magnilion / Getty Images

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Laboratorians and clinicians at Auburn Community Hospital (ACH) in central New York are thrilled to be the FIRST institution in the United States to debut the Abbott’s Alinity h-series within their core laboratory.

The Alinity h-series is a diagnostic system composed of an automated hematology analyzer and an integrated slide maker stainer. This new system will drastically improve the quality of care for patients at ACH, especially since the institution is expanding its services for cardiology and oncology patients; blood samples from these patient populations have been proven to be more difficult to analyze.

“We are both honored and humbled for Auburn Community Hospital to be the first laboratory in the country to house the newest cutting-edge technology for hematology testing available in the current market: Abbott’s Alinity h-series. Through implementation of the Alinity h-series here in Auburn, we are excited to shepherd this mission together and elevate the standard of quality care in our local neighboring community and throughout central New York.”

- Jessica Giacona, Core Laboratory Supervisor at Auburn Community Hospital

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F ROM T HE EDITOR

Cybersecurity goals

T

his month, we published the results of our third annual State of the Industry survey on laboratory data analytics. Thank you to all who responded to this survey. As Stacia Sump, Global Product Director at Clinisys told our author, “Labs are generating more data across a variety of use cases (e.g., synoptic reporting, digital pathology, etc.) and technology has made this data more accessible for analysis.” Laboratories are analyzing data for many purposes including staffing needs, supply utilization, quality improvement initiatives, tracking testing costs, and patient care.

By Christina Wichmann Respondents indicated that the top strategic IT priEditor in Chief orities for their laboratories include infrastructure and platform development, a new laboratory information system (LIS) system, data analytics optimization to support lab management, and integration with the electronic health record (EHR) system. Other priorities include revenue cycle management optimization, move to a cloud-based LIS system, and cybersecurity. Technology is leading to improvements in patient outcomes, organizational expenditures, staff time and resources, among other things. (This month’s Continuing Education article also describes many wonderful advances technology is bringing to healthcare!) However, the increased use of technology, such as EHRs and cloud-based systems, has a significant (and expensive) downside.

The U.S. Department of Health and Human Services’ (HHS) Office of Civil Rights reported over 134 million individuals were affected by large data breaches in 2023, whereas 55 million were affected in 2022. Hospitals and health systems have become the biggest target for cybersecurity attacks in recent years largely due to the quantity of sensitive patient information available such as social security numbers, names, dates of birth, addresses, diagnoses, and payment information.

Most of this information is hard to change, unlike a stolen credit card number, so patient medical records command a larger price with identity thieves.

HHS recently published voluntary healthcare-specific cybersecurity performance goals to help organizations prioritize implementation of effective cybersecurity practices. The goals are separated into two categories: essential goals that outline minimum cybersecurity controls and enhanced goals that outline advanced cybersecurity controls. There are ten goals in each category as follows:

Essential goals:

• Mitigate known vulnerabilities • Email security • Multifactor authentication • Basic cybersecurity training • Strong encryption • Revoke credentials for departing employees, contractors, volunteers • Basic incident planning and preparedness • Unique credentials • Separate user and privileged accounts • Vendor/supplier cybersecurity requirements

Enhanced goals:

• Asset inventory • Third party vulnerability disclosure • Third party incident reporting • Cybersecurity testing • Cybersecurity mitigation • Detect and respond to relevant threats and tactics • Network segmentation • Centralized log collection • Centralized incident planning and preparedness • Configuration management

The full information on these cybersecurity performance goals can be accessed at https://hphcyber.hhs.gov/performance-goals.html. I hope this information serves as a helpful reminder that as more investments are made in IT, such as placing more data in a cloud, more investment in security will be needed.

I welcome your comments and questions — please send them to me at cwichmann@mlo-online.com.

Vol.56, No. 3 PUBLISHER Chris Driscoll

cdriscoll@endeavorb2b.com EDITOR IN CHIEF Christina Wichmann

cwichmann@mlo-online.com

MANAGING EDITOR Erin Brady

ebrady@endeavorb2b.com

PRODUCTION MANAGER Edward Bartlett ART DIRECTOR Kermit Mulkins AUDIENCE DEVELOPMENT/LIST RENTALS

Laura Moulton | lmoulton@endeavorb2b.com ADVERTISING SERVICES MANAGER

Karen Runion | krunion@endeavorb2b.com ADVERTISING DIRECTOR OF SALES EAST COAST/MIDWEST SALES, CLASSIFIEDS

Carol Vovcsko (941) 321-2873 | cvovcsko@mlo-online.com SOUTH/WEST COAST/ILLINOIS SALES

Lora Harrell (941) 328-3707 | lharrell@mlo-online.com MLO EDITORIAL ADVISORY BOARD John Brunstein, PhD, Biochemistry (Molecular Virology) President & CSO PathoID, Inc., British Columbia, Canada Lisa-Jean Clifford, COO & Chief Strategy Officer Gestalt, Spokane, WA Barbara Strain, MA, SM(ASCP), CVAHP Principal, Barbara Strain Consulting LLC, Formerly Director, Value Management, University of Virginia Health System, Charlottesville, VA Jeffrey D. Klausner, MD, MPH Professor of Preventive Medicine in the Division of Disease Prevention, Policy and Global Health, Department of Preventive Medicine at University of Southern California Keck School of Medicine.

Donna Beasley, DLM(ASCP), Director, Huron Healthcare, Chicago, IL Anthony Kurec, MS, H(ASCP)DLM, Clinical Associate Professor, Emeritus, SUNY Upstate Medical University, Syracuse, NY Suzanne Butch, MLS(ASCP)CM, SBBCM, DLMCM Freelance Consultant, Avon, OH Paul R. Eden, Jr., MT(ASCP), PhD, Lt. Col., USAF (ret.), (formerly) Chief, Laboratory Services, 88th Diagnostics/Therapeutics Squadron, Wright-Patterson AFB, OH Daniel J. Scungio, MT (ASCP), SLS, CQA (ASQ), Consultant at Dan the Lab Safety Man and Safety Officer at Sentara Healthcare, Norfolk, VA CORPORATE TEAM

CEO Chris Ferrell PRESIDENT June Griffin COO Patrick Rains CRO Reggie Lawrence CHIEF DIGITAL OFFICER Jacquie Niemiec CHIEF ADMINISTRATIVE AND LEGAL OFFICER

Tracy Kane

EVP CITY SERVICES & HEALTHCARE Kylie Hirko

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THE OBSERVATORY :: NEWS • TRENDS • ANALYSIS 3X overdose mortality among those aged 35 to 44 during the study period. From 4.9 deaths per 100,000 mothers aged 35 to 44 with a live birth in the 2018 period to 15.8 in the 2021 period.

Overdose deaths increased in pregnant and postpartum women from early 2018 to late 2021 Drug overdose deaths rose markedly between January to June 2018 and July to December 2021 among 10- to 44-year-old girls and women who were pregnant or pregnant within the previous 12 months, according to a new study by researchers at National Institute on Drug Abuse (NIDA) at the National Institutes of Health.

Source: https://www.nih.gov/ news-events/news-releases/ overdose-deaths-increased-pregnantpostpartum-women-early-2018-late-2021

4.9 deaths

3805894 © Michel Van Loon | Dreamstime.com

Fast Facts

FDA and CMS: Americans deserve accurate and reliable diagnostic tests, wherever they are made

The following is attributed to Jeff Shuren, M.D., J.D., director of the FDA’s Center for Devices and Radiological Health (CDRH) and Dora Hughes, M.D., M.P.H., acting chief medical officer and acting director of the Center for Clinical Standards and Quality, Centers for Medicare & Medicaid Services (CMS).

Physicians heavily rely on laboratory tests to make critical decisions about their patients’ care—roughly 70% of healthcare decisions depend on laboratory test results according to the Centers for Disease Control and Prevention (CDC).

For example, results from laboratory tests can be the sole determinant of whether a patient with cancer gets a particular therapy, potentially risking the patient’s life with an inaccurate test result. Because of the important role of laboratory tests in healthcare decisions, it is essential to ensure these tests work.

While the U.S Food and Drug Administration (FDA) actively oversees tests made outside laboratories by test manufacturers, tests made and run within a single laboratory, known as laboratory developed tests or LDTs, are often used without such oversight. The FDA’s approach was developed half a century ago when tests made and used in single labs were generally simple, often made to address local individual needs, and mostly manufactured in small volumes. Therefore, the FDA, as a policy approach, generally did not enforce requirements for LDTs. However, since then, LDTs have evolved. Due to the increased risk to patients, it is time to reconsider this approach.

In recent decades, the FDA has identified concerns with a number of LDTs. In October of this year, the FDA issued a notice of proposed rulemaking to help ensure the safety and effectiveness of LDTs by phasing out the FDA’s current approach to LDTs. If finalized, LDTs would generally fall under the same enforcement approach as other tests. The Centers for Medicare & Medicaid Services (CMS) supports the FDA’s proposal.

Both CMS and the FDA believe that patients and their doctors need to know that LDTs are valid. The FDA and CMS both provide oversight to help assure the accuracy of test results, however, they have different roles. CMS regulates laboratories that perform testing on individuals in the U.S. through the Clinical Laboratory Improvement Amendments of 1988 (CLIA)

15.8 deaths

3.1 deaths 6.1 deaths 2018 2021

2X overdose mortality ratios among those aged 10 to 44 who died between 43 days and one year after pregnancy - from 3.1 in the 2018 period to 6.1 in the 2021 period.

by establishing quality standards for all laboratory testing to help ensure the accuracy, reliability and timeliness of patient test results. In 2013, CMS published a fact sheet on LDTs, outlining each agency’s authority and the complementary roles of the two regulatory schemes. That said, a decade later, in connection with the FDA’s notice of proposed rulemaking, we are – together – reiterating that CMS’s CLIA program is separate in scope and purpose from FDA oversight.

Some have suggested that concerns with LDTs should be addressed through expansion of CLIA. This is not the answer.

As was stated in our 2015 testimony, CMS does not have the expertise to assure that tests work; the FDA does. Moreover, establishing a duplicative system for the oversight of tests by expanding CLIA would create more government bureaucracy and inconsistencies. That makes no sense.

The FDA and CMS have long stood together in mutual support of FDA oversight of the analytical and clinical validity of LDTs. LDTs play an important role in healthcare, but when they perform poorly or are not supported by science, they put patients at risk. The current approach has enabled some tests to enter the market with unfounded claims of innovation.

These claims can mislead the public, undermine legitimate competition and disincentivize responsible, science-based innovation. Applying the same oversight approach to laboratories and non-laboratories that manufacture tests would better assure the safety and effectiveness of LDTs and would remove a disincentive for non-laboratory manufacturers to develop novel tests that can be available to and used by many laboratories for many patients.

We are now emerging from a global pandemic that has underscored the importance of accurate and reliable tests.

Patients and providers need to have confidence that laboratory tests work. We believe the complementary FDA and CMS frameworks are both critical to assuring patients can rely on the clinical accuracy of their test results.

CDC’s 2022 STI Surveillance Report underscores that STIs must be a public health priority

The Centers for Disease Control and Prevention (CDC) published a report on January 30. Sexually Transmitted Infections

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THE OBSERVATORY :: NEWS • TRENDS • ANALYSIS 75.4% compared with 59.5% of females who died from drug overdose during pregnancy, compared to those who died from obstetric causes, were more likely to be aged 10 to 34.

60% to 73% of pregnant and postpartum women who died from an overdose were either at home or other nonhealthcare places.

> 60% of these pregnancyassociated overdose deaths occurred outside healthcare settings, though often in counties with available healthcare resources, such as emergency and obstetric care.

51% to 53% of pregnant and postpartum women who died from overdoses resided in counties with at least two general hospitals ranked at the 95th percentile for obstetric care among U.S. counties.

Surveillance, 2022 provides the most current and complete data for nationally notifiable STIs for federally funded control programs.

CDC’s annual report underscores that STIs must be a public health priority. In 2022, more than 2.5 million cases of syphilis, gonorrhea, and chlamydia were reported in the United States. The most alarming concerns center around the syphilis and congenital syphilis epidemics, signaling an urgent need for swift innovation and collaboration from all STI prevention partners. In addition to the syphilis epidemic worsening, reported gonorrhea cases declined for the first time in at least a decade while reported chlamydia cases were level. CDC will continue to examine this finding closely and look to 2023 data for better understanding, but recognize this finding may be a cause for an even closer look at public health efforts and redoubled prevention strategies. As STI services and related resources continue to rebound from the U.S. COVID-19 pandemic and mpox outbreak, we must act now to mobilize and execute a whole-of-nation approach if we hope to turn the tide.

The study was conducted by researchers from the NIH’s National Institute of Allergy and Infectious Diseases (NIAID) and National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at the Metabolic Clinical Research Unit in the NIH Clinical Center. The 20 participants were diverse with respect to ethnicity, race, gender, body mass index (BMI), and age. Each person ate as much as desired of one diet (vegan or keto) for two weeks, followed by as much as desired of the other diet for two weeks. People on the vegan diet, which contained about 10% fat and 75% carbohydrates, chose to consume fewer calories than those on the keto diet, which contained about 76% fat and 10% carbohydrates. Throughout the study period, blood, urine, and stool were collected for analysis. The effects of the diets were examined using a “multi-omics” approach that analyzed multiple data sets to assess the body’s biochemical, cellular, metabolic, and immune responses, as well as changes to the microbiome. Participants remained on site for the entire month-long study, allowing for careful control of the dietary interventions.

Switching exclusively to the study diets caused notable changes in all participants. The vegan diet significantly impacted pathways linked to the innate immune system, including antiviral responses. On the other hand, the keto diet led to significant increases in biochemical and cellular processes linked to adaptive immunity, such as pathways associated with T and B cells. The keto diet affected levels of more proteins in the blood plasma than the vegan diet, as well as proteins from a wider range of tissues, such as the blood, brain and bone marrow. The vegan diet promoted more red blood cell-linked pathways, including those involved in heme metabolism, which could be due to the higher iron content of this diet. Additionally, both diets produced changes in the microbiomes of the participants, causing shifts in the abundance of gut bacterial species that previously had been linked to the diets. The keto diet was associated with changes in amino acid metabolism—an increase in human metabolic pathways for the production and degradation of amino acids and a reduction in microbial pathways for these processes— which might reflect the higher amounts of protein consumed by people on this diet.

Switching to vegan or ketogenic diet rapidly impacts immune system

Researchers at the National Institutes of Health observed rapid and distinct immune system changes in a small study of people who switched to a vegan or a ketogenic (also called keto) diet.

Scientists closely monitored various biological responses of people sequentially eating vegan and keto diets for two weeks, in random order. They found that the vegan diet prompted responses linked to innate immunity—the body’s non-specific first line of defense against pathogens—while the keto diet prompted responses associated with adaptive immunity—pathogen-specific immunity built through exposures in daily life and vaccination. Metabolic changes and shifts in the participants’ microbiomes—communities of bacteria living in the gut—were also observed. More research is needed to determine if these changes are beneficial or detrimental and what effect they could have on nutritional interventions for diseases such as cancer or inflammatory conditions.

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Artificial intelligence in healthcare...

Friend or foe?

By Anthony Kurec, MS, MASCP, H(ASCP)DLM

inkoly & metamorworks iStock / Getty Images Plus Getty Images

I

n the last several decades, the advancement in computer technology has created numerous opportunities for collecting vast amounts of information, or ‘big data.’ Management of such and the ability to maximize its practical use sets the stage for artificial intelligence (AI). This technology has been used in banking, marketing, manufacturing, entertainment, art, traffic control, and even agriculture.1 In the last decade or so, AI and robotics have been incorporated into various healthcare practices, from keeping people healthy to early warning of potential diseases. Figure 1 shows the impact of AI and robotics on some key areas of healthcare. The influence of AI has grown as seen with personal assistant

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CONTINUING EDUCATION :: ARTIFICIAL INTELLIGENCE apps that have been developed to help patients with drug warnings, patient education material, and monitoring of a patient’s health condition. AI-driven virtual human avatars have been created and used to converse with patients with mental problems in obtaining a diagnosis and treatment, an activity that was prevalent during the isolation days of the COVID-19 pandemic. 2 In the last fifty years, laboratory science has seen significant changes in the application of new technologies and methodologies. As new testing modalities were developed and implemented, testing volumes for most clinical laboratories increased. Again, this has been especially true as evidenced during the COVID-19 pandemic with increased workloads, staffing shortages, staff burnout, and supply chain issues.

From the days of manual pipetting to sophisticated automated track systems, the need to manage the ever-changing laboratory environment has inspired innovative laboratories to consider the use of artificial intelligence–based systems.

Artificial intelligence

In 1950, the British mathematician and computer scientist, Alan Turing, proposed a thought experiment that suggested machines (i.e., computers) could potentially mimic functions similar to how the human brain collected and assembled information to solve problems and make key decisions. Thus, the Turing Test (TT), a method of inquiry to see if a third-party judge could differentiate between human responses compared to that of a machine was introduced. If a third-party judge could not determine if the majority of correct responses were from a machine or the human respondent, then it passed the Turing Test, thus the machine was considered to possess artificial intelligence. Today, with improved acumen in computer science and access to cloud computing, the TT reveals some limitations. Based on this, the Lovelace Test 2.0 became another tool for determining the presence of intelligence. Ada Lovelace (1815-1852), considered the first computer programmer, believed that to have true machine intelligence it had to demonstrate creativity (create art, poems, stories, engineering, science, etc.). Thus, this was a test to determine a machine’s ability to be creative by producing something that the programmer could not explain.

Computer technology would not reach the level of providing the needed computing power and storage capabilities to support data acquisition and the running of complex programs for decades, yet the concept of artificial intelligence (AI) was born. Today, a number of AI platforms are available such as Amazon’s Alexa, Google’s Med-PaLM, ChatGPT-4, Bard, Bert, Dall-E, and Watson to name a few. Thus, as computer technology improved, the capability to collect data, store it, and process it at phenomenal speeds was in part due to cloud computing, the use of a network of remote servers that could manage and process data externally thus freeing up internal computer resources. This set the stage for the presence of big data sets, the key ingredient for AI technology.1 The introduction of AI and robotics has already had a profound impact on our daily lives and has been suggested as the beginning of the Fourth Industrial Revolution.

What is artificial intelligence?

To better understand and appreciate the significance of AI and its potential impact in the near future, some basic information about what AI is and how it works can be useful. The purpose of AI is to make decisions based on historical or real-time data.

From these outcomes, it refines and improves the information output making changes as needed consisting of several subsets: neural networks, deep learning, and machine learning.

In developing AI programs, algorithms are created using large databases to provide a set of instructions followed in a specific order that ultimately drives the decision-making process.

Neural networks: Contain specific amounts of information or data. Layers of nodes are created and then adapt to learning from the outcomes. In combining computer science and statistics, the results lead to continuous improvement in solving complex issues and become the basis for algorithms. This is similar to the human brain where neurons interconnect with other neurons to receive (input layer), process (hidden layer), and transmit (output layer) information. Neural networks learn the rules by finding patterns in large data sets that are available.3,4 Machine learning: Occurs when computers collect billions of bits of data that are then used in creating statistical models in building algorithms. Because of the vast amounts of data used in AI, much is broken down into smaller, more manageable units called tokens. Tokens are words, characters, numbers, or symbols that then can be converted to numerical units and applied in developing algorithms efficiently.This allows the computer to learn and adapt, a process that was modeled after the human brain.5 Using statistical methods, algorithms are developed and ‘trained’ to classify or predict outcomes based on relevant data mining information and past outcomes.6 Machine learning does not involve explicit programming to reach a conclusion but recognizes patterns to make a prediction.

Deep learning: Is a subset of machine learning. It consists of a number of neural networks with many hidden layers of unstructured data that identify patterns based on images, texts, sounds, and time inputs. Deep learning provides the logical structure needed for analyzing complex data (obtained from neural networks) that allow for drawing certain conclusions and again, is analogous to how a human brain would work.6 Deep learning is the basis for digital assistants, voice-enabled TV remotes, credit card fraud detection programs, and self-driving cars. It is a type of AI that generates answers or decisions based on past experiences rather than predetermined calculations/algorithms.7 Generative AI: May be considered the next phase in AI. In collecting raw data sets from users’ queries (deep learning), certain patterns are identified to create new text, video, and images. ChatGPT is an example and has been used in healthcare as a tool for some basic administrative tasks such as billing, post-appointment clinical notes, and communicating

Earning CEUs

See test online at www.mlo-online.com under the Continuing Education tab. Passing scores of 70 percent or higher are eligible for 1 contact hour of P.A.C.E. credit.

LEARNING OBJECTIVES

Upon completion of this article, the reader will be able to: 1. Summarize the foundation of AI and its presence in healthcare.

2. Differentiate the computer science tests that have proven AI to be valuable, and define the factors that make up the elements of AI. 3. Identify examples of how AI has been used in the field of healthcare.

4. Discuss reasons for failures of AI in healthcare settings.

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CONTINUING EDUCATION :: ARTIFICIAL INTELLIGENCE

A

with patients. Such communications with patients are then entered directly into a patient’s electronic health record (EHR). It has been reported that patients were more willing to share information and preferred using the chatbot rather than talking with a healthcare professional.8

In the clinical laboratory, numerous advances in the automation of diagnostic testing have improved accuracy, processing, and data collection, but also have provided a platform for new testing modalities. In addition, data-collecting devices, such as point-of-care testing, smartwatches, Wi-Fi–enabled arm bands, or other real-time biometrics have been applied Impact of AI on healthcare and the laboratory in looking at the prevention, diagnosis, treatment, and manA few decades ago, laboratory test results were provided in agement of patient issues. In one study of 500,000 people hand-written reports that had to be manually delivered to using such AI-supported technology, readmission rates and each nursing unit or mailed to a healthcare provider. As digital emergency department visits were significantly reduced. This technology improved, the laboratory information system (LIS) also resulted in fewer follow-up home visits and better patient became a critical part of laboratory management, not only adherence rates to treatment plans. Cost savings, as seen improving the quality and timeliness of delivering patient at Grady Hospital in Atlanta, saw a $4 million decrease in reports but also improving the overall efficiency and quality readmission rate costs over two years.2 of patient care. Besides managing patient test results, the LIS In Pennsylvania, AI algorithms were trained using data has become a resource for managing internal and external outcomes from 1.25 million surgical patients and used in quality control/assessments, test requests, blood collecidentifying post-surgical, high-risk patients such as predicting tion, turnaround times, delta-checks, instrument the likelihood of developing sepsis or respiratory management, and other quality management problems. It also predicted the need for information, collectively amassing large massive blood transfusions. The ability to amounts of data. Artificial intelligence prepare multiple units of blood before has taken the beginning steps in surgery minimizes the wait time for managing this process.9 the blood bank to process many Wellness In recent years, personalized blood units/products needed. It medicine, the practice of using also requires fewer technical Early Education Detection genetic and other biodata to staff to prepare the units and make healthcare decisions ensures typed-match produnique to an individual, has ucts are available.12 been evolving. To achieve In addition, some wearthis, significant computing able devices have been used AI & power is needed to review in predicting healthcare Diagnosis Research Robotics issues based on changes medical literature; analyze patient test results; and seen in some basic laboratory provide the best options in tests such as hematocrit, hediagnosing, treating, and moglobin, glucose, and platemanaging that individual lets, thus signaling a potential End Of Life Decisions Care patient. Artificial intelligence underlying health issue.13 In can play a big role in that. managing a patient’s electronic Treatment The use of this type of precision health record (EHR), AI programs medicine allows for patients to be can find and present any abnormal accurately profiled based on personal laboratory test and contrast it with other examinations and laboratory tests. These patient data. For example, a low platelet data sets may be viewed asstructured data or count would certainly be noted, however, AI as unstructured data (See Table 1). It has been Figure 1: The impact of AI could explore a patient’s medication list and estimated that healthcare providers generate and robotics on healthcare.28 promptly notify the healthcare practitioner of 137 terabytes daily or about 50 petabytes every possible drug-induced thrombocytopenia, a year, most of which is considered unstructured. process all done in the background.14 Big healthcare data sets are continually growing in part due to Much of this information is then relayed to databases that ever-evolving medical device technology, genetic testing, and with the aid of an appropriate algorithm, can detect, monitor, patient-generated health data (point-of-care testing, wearable and manage patient care activities. AI can serve as a tool in devices, etc.). A single chest X-ray is about 15 megabytes (Mb) support of clinical decision-making as seen with ‘Watson for in size and a 3-D mammogram is about 300 Mb, but a digital Oncology,’ an application from IBM that can help to better pathology file consumes as much as 3 gigabytes. The ability diagnose and classify treatments for various cancers such to collate this kind of useful patient information in a practical as breast, colon, rectal, prostate, gastric, lung, ovarian, and and efficient manner is a part that AI is expected to play.10 cervical cancers. By entering cancer patient information, a As noted, data management in healthcare is essential. It has treatment plan can be devised based on data extracted and been estimated that about 30% of the world’s data is related collated from past clinical cases, 290 medical journals, 200 to healthcare or roughly 270 Gb of healthcare data for each textbooks, and 12 million pages of medical research.2 11 person in the world. It is anticipated that these databases will Another area AI has been used is the diagnosing of rare continue to grow, thus the need for efficient data management diseases. There are as many as 8,000 known rare diseases that can parse out critical bits of healthcare information to affecting as many as 400 million people around the world and providers and patients. Critical to the process is to ensure often requiring up to five years to accurately diagnose. While data privacy and that AI is ethically and responsibly used in many medical professionals are not specifically trained or whatever aspect it is applied to. even know of these diseases, AI has been shown as a resource

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Alinity i TBI

AWARENESS IS THE FIRST STEP IN EVALUATING CONCUSSIONS DID YOU KNOW...

• only 3% of reported concussions are due to sports1 • women have a higher rate of concussions than men2 • 15% of concussion patients experience long-term symptoms3 • CT scans can miss 1 out of every 4 concussions compared to MRIs4 • Abbott’s TBI plasma-based biomarker test aids in concussion assessment ruling out the need for a CT scan in mild traumatic brain injury patients5 ALINITY i TBI TEST PATHWAY

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• For In Vitro Diagnostic Use 1. F. Korley. et al., (2016). Emergency Department Evaluation of Traumatic Brain Injury in the United States, 2009-2010, J Head Trauma Rehabil, 2016;31:379-387.

2. Albrecht JS, Hirshon JM, McCunn M, et al. Increased Rates of Mild Traumatic Brain Injury Among Older Adults in US Emergency Departments, 2009-2010. J Head Trauma Rehabil. 2016;31(5):E1-E7. doi:10.1097/ HTR.0000000000000190 3. Blennow et al., Traumatic brain injuries. Nat Rev Dis Primers 2, 16085 (2016).

4. Yue JK, Yuh EL, Korley FK, et al. Association between plasma GFAP concentrations and MRI abnormalities in patients with CT-negative traumatic brain injury in the TRACK-TBI cohort: a prospective multicentre study. Lancet Neurol.

2019;18(10):953-961. doi:10.1016/S1474-4422(19)30282-0 5. Alinity i TBI IFU 802673R01. Abbott Diagnostics. May 2023. © 2024 Abbott. All rights reserved. All trademarks referenced are trademarks of either the Abbott group of companies or their respective owners. Any photos displayed are for illustrative purposes only. Any person depicted in such photos may be a model. ADD-148714-USA-EN 2/24

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CONTINUING EDUCATION :: ARTIFICIAL INTELLIGENCE tool for identifying them based on symptomatic patterns and associations that would otherwise not be detected by a human.

It also can forecast disease progression and offer targeted treatment regimens.15 An AI-based tool developed by Harvard Medical School has been used in the genomic profiling of brain tumors (gliomas).

Similar to performing a frozen section during surgery, the Cryosection Histopathology Assessment and Review Machine (CHARM) can detect genetic mutations, differentiate between the types of glioma, provide associated treatment plans, and offer a prognosis in real time.16 Over 12 million mammograms are done each year in the United States of which some are erroneously identified as cancer positive. AI-assisted programs have been used to read and translate these images 30 times faster than reading these images manually and with 99% accuracy.17 In another example, an AI-enabled eye disease diagnosis system provided the stage of the disease in 30 seconds with a 95% accuracy rate. It has been reported that 60% of all medical errors are due to a wrong initial diagnosis resulting in an estimated 40,000 to 80,000 deaths each year in the United States.

The intent of using AI in medicine is to provide healthcare professionals with a resource that will ultimately improve patient care with no intent of replacing them.2 As AI databases are developed and expanded, algorithms can and have been created that have improved the precision and speed of predicting various maladies. As an example, AI has been used in predicting the diagnosis of iron-deficiency anemia (with low serum iron levels) based on routine CBC results. AI has been used in analyzing digital images of urine sediment, microbiology plate reading, and predicting the prognosis for patients with 14 different cancer types by analyzing digital histology sections and genomic data. It also can help in identifying what laboratory tests should be ordered, thus reducing the number (up to 25% of orders) of unnecessary repeat laboratory tests.18,19,20

Robotics and drones

Robotics and drones have had a long history with the military.

Medical uses of AI-driven robots and drones are now used in hospitals and other healthcare facilities around the world. Surgical assistance from robots such as the da Vinci robot provides better precision, dexterity, and control in surgery. The da Vinci system has been used in cardiac, urologic (prostate cancer), gynecologic (hysterectomies), pediatric, and general surgeries requiring minimal surgical incisions that improve patient recovery, with less blood loss, less pain, and less scarring.21 Procedures in robotic manipulation have been formalized with structured training (Master of Science in Robotic Surgery) available for physicians offering state-of-the-art techniques.22

There is a greater presence of mobile robots in hospitals involving more timely delivery of medications, supplies, and laboratory specimens. This alleviates hiring staff specifically for transport services, which subsequently increases labor costs. In many cases, nurses, aides, or clerical staff are used for transport — personnel that is in short supply and has other pressing duties. The implementation of automated mobile robots also reduced the need for hard-to-supply PPE (personal protective equipment) and minimized staff exposure to patients in isolation. Table 2 identifies the four major types of robots used in healthcare.

In the past few decades, the clinical laboratory has expanded its footprint beyond the hospital walls. A tremendous amount of time and effort has been spent on specimen collection and delivery to the laboratory. While still in the early stages, unmanned aerial vehicles (UAVs or drones) have been successfully used by a number of laboratories to transport specimens, provide phlebotomy supplies, and move needed blood products quickly and safely. The use of drones is particularly efficient in busy, high-traffic metropolitan areas as well as difficult-to-reach rural areas that are at a distance from a laboratory. Drones have been employed in underserved areas in many countries, particularly during medical emergencies and disasters.23

AI issues to consider

While AI and robotics have many positive aspects, it is still a work in progress. One issue that has raised concern is that of trust in the technology and safety of those involved. In these still early days of AI development, some inherent concerns have been identified and are being attended to.

AI-related problems are likely due to the high dependence on how AI algorithms are ‘taught,’ meaning that misleading, inaccurate, or biased data input will result in incorrect outcomes with limited or bad data input. Further, issues of ethics, transparency, copyright problems, bias, plagiarism, and other legal matters have been voiced.3,24 In addition, there is some fear that certain jobs may be replaced by AI. However, it is believed that new career opportunities will evolve in creating and supporting AI functions. While it has been estimated that AI would automate the workload for 60%-70% of workers performing various manual activities, to date, the impact of AI on the labor market is minimal at best, and focused on unique parts of the economy.25 Regardless, even with AI involvement, human intervention will still be required.2,26 These types of AI concerns about when things go wrong have led to the creation of the Artificial Intelligence Incident Database (https://incidentdatabase.ai), a growing repository of AI-related failures that have been reported as causing “harms or near harms.”27 As humans learn from their mistakes, AI, too, will learn.

Conclusion Unstructured Data

Structured Data

Interpretive results • Medical images • Physician/nursing notes • Written reports • Any other patientrelated written narrative

Quantitative or input results (Generally do not require in-depth interpretation but are straightforward information that is entered into a system.)

• Patient demographics • Vital signs • Billing codes • Medications • Laboratory test results

Table 1. Structured data versus unstructured data.10

Yet, as with any growing technology, early results may not always be perfect, but as technology improves, it is certain that AI will play a bigger role in healthcare and other professions with billions of dollars invested in its development. As for the laboratory, there appears to be a number of areas that would improve efficiency and the quality of services with AI guidance. Critical to the development of AI is the assurance that the ‘learning data’ used in developing an AI algorithm is complete and unbiased. As the adage goes, garbage in, garbage out will result in poor and/or inaccurate outcomes. Yet, AI continues to learn, grow, and be implemented in many areas of everyday life including healthcare and the laboratory.

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CONTINUING EDUCATION :: ARTIFICIAL INTELLIGENCE

Care robots

Hospital logistic robots

Care robots offer needed support to elderly and disabled patients that include medication reminders, temperature and blood pressure measurements, and aid in blood draws.

Hospital logistic robots are used to deliver laundry, medications, blood samples, and other transportable products.

Exoskeletons

Surgical robots

Exoskeletons provide movement opportunities and treatment for spinal injury patients.

Surgical robots assist in various surgeries such as bariatric and gynecological surgeries.

Table 2. Four types of robots. (Information from Yujin Robot)

While still in the early stages, AI has been incorporated into some areas of the laboratory such as genetic testing for a number of syndromes, cancers, various strains of bacteria, and digital pathology. As has been the case with laboratory instrumentation integrating computer technology several decades ago, implementing AI into laboratory practices by predicting test values, offering better test result interpretations, providing sophisticated instrumentation management, and generating diagnostic evaluations are in the works. In addition to the technical considerations, AI could improve laboratory management such as quality assurance practices, distribution of test results, and better defining of true reference values that would minimize patient bias.18 AI, though not perfect at this junction, will drive many aspects of everyday life, especially healthcare. As AI continues to improve, grow, and impact healthcare, it is critical to ensure that it does not overwhelm and remove the human element in interpersonal transactions and that the end results generated by AI are productive and not destructive.

REFERENCES 1. SITNFlash. The history of artificial intelligence. Science in the News.

Published August 28, 2017. Accessed January 24, 2024. https://sitn. hms.harvard.edu/flash/2017/history-artificial-intelligence/.

2. Lee D, Yoon SN. Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges. Int J Environ Res Public Health. 2021;18(1):271. doi:10.3390/ijerph18010271.

3. Lawton G. What is generative AI? Everything you need to know.

Enterprise AI. Published January 18, 2024. Accessed January 24, 2024. https://www.techtarget.com/searchenterpriseai/definition/ generative-AI. 4. Pure Storage. Deep learning vs. Neural networks. Pure Storage Blog. Published October 26, 2022. Accessed January 24, 2024. https://blog.purestorage.com/purely-informational/ deep-learning-vs-neural-networks/.

5. What is machine learning? Ibm.com. Accessed January 24, 2024. https://www.ibm.com/topics/machine-learning.

6. Wolfewicz A. How do machines learn? A beginners guide. Levity.ai.

Published November 16, 2022. Accessed January 24, 2024. https://levity.ai/blog/how-do-machines-learn.

7.

Macrometa - The hyper distributed cloud for real-time results.

Macrometa. Accessed January 24, 2024. https://www.macrometa.com/.

8. Perna G, Turner BEW. Dr. ChapGPT: A guide to generative AI in healthcare. Modern Healthcare. Published May 15, 2023. Accessed January 24, 2024. https://www.modernhealthcare.com/digital-health/ chatgpt-healthcare-everything-to-know-generative-ai-artificialintelligence.

9. Padoan A, Plebani M. Flowing through laboratory clinical data: the role of artificial intelligence and big data. Clin Chem Lab Med. 2022;60(12):1875-1880. doi:10.1515/cclm-2022-0653.

10. Eastwood B. How to navigate structured and unstructured data as a healthcare organization. Publisher. Published May 8, 2023. Accessed January 24, 2024. https://healthtechmagazine.net/article/2023/05/ structured-vs-unstructured-data-in-healthcare-perfcon.

11. Miclaus K. Top 3 barriers to entry for AI in health care. Dataiku.com.

Published July 29, 2022. Accessed January 24, 2024. https://blog. dataiku.com/top-3-barriers-ai-health-care.

12. Melchionna M. ML Model Detects Patients at Risk of Postoperative Issues. Healthitanalytics.com. Published July 7, 2023.

Accessed January 24, 2024. https://healthitanalytics.com/news/ ml-model-detects-patients-at-risk-of-postoperative-issues.

13. Smartwatch data used to predict clinical test results.

National Institute of Biomedical Imaging and Bioengineering. Published November 30, 2021. Accessed January 24, 2024. https://www.nibib.nih.gov/news-events/newsroom/ smartwatch-data-used-predict-clinical-test-results-4.

14. Harris JE. An AI-Enhanced Electronic Health Record Could Boost Primary Care Productivity. JAMA. 2023;5;330(9):801-802. doi:10.1001/ jama.2023.14525.

15. Visibelli A, Roncaglia B, Spiga O, Santucci A. The impact of artificial Intelligence in the odyssey of rare diseases. Biomedicines.

2023;11(3):887. doi:10.3390/biomedicines11030887.

16. Melchionna M. AI Tool Provides Profile of Brain Cancer Genome During Surgery. Healthitanalytics.com. Published July 11, 2023.

Accessed January 24, 2024. https://healthitanalytics.com/news/ ai-tool-provides-profile-of-brain-cancer-genome-during-surgery.

17. PricewaterhouseCoopers. What doctor? Why AI and robotics will define new health. PwC. Accessed January 24, 2024. https://www. pwc.com/gx/en/news-room/docs/what-doctor-why-ai-and-roboticswill-define-new-health.pdf.

18. A status report on AI in laboratory medicine. Myadlm.org. Published January 1, 2023. Accessed January 24, 2024. https://www.myadlm.org/ cln/articles/2023/janfeb/a-status-report-on-ai-in-laboratory-medicine.

19. Newton E. How can clinical labs benefit from machine learning and AI? clinicallab. Published October 10, 2022.

Accessed January 24, 2024. https://www.clinicallab.com/ how-can-clinical-labs-benefit-from-machine-learning-and-ai-26775.

20. Artificial intelligence in pathology. College of American Pathologists.

Published April 16, 2020. Accessed January 24, 2024. https://www.cap. org/member-resources/councils-committees/informatics-committee/ artificial-intelligence-pathology-resources.

21. Da Vinci robotic surgery. Upstate.edu. Accessed January 31, 2024. https://www.upstate.edu/community/services/surgery/davinci.php.

22. Online master of science in robotic surgery. AdventHealth University. Accessed January 23, 2024. https://www.ahu.edu/programs/ online-master-of-science-robotic-surgery.

23. Laksham KB. Unmanned aerial vehicle (drones) in public health: A SWOT analysis. J Family Med Prim Care. 2019;8(2):342-346. doi:10.4103/jfmpc.jfmpc_413_18.

24. Sallam M. ChatGPT utility in healthcare education, research, and practice: Systematic review on the promising perspectives and valid concerns. Healthcare (Basel). 2023;11(6):887. doi:10.3390/ healthcare11060887.

25. Past AI100 Officers. Gathering strength, gathering storms: The one hundred year study on artificial intelligence (AI100) 2021 study panel report. One Hundred Year Study on Artificial Intelligence (AI100). Accessed January 24, 2024. https:// ai100.stanford.edu/gathering-strength-gathering-stormsone-hundred-year-study-artificial-intelligence-ai100-2021 -study.

26. Lutkevich B. Will AI replace jobs? 9 job types that might be affected.

WhatIs. Published November 3, 2023. Accessed January 24, 2024. https://www.techtarget.com/whatis/feature/Will-AI-replace-jobs-9-jo b-types-that-might-be-affected.

27. Mcgregor S. When AI systems fail: Introducing the AI incident database. Partnership on AI. Published November 18, 2020. Accessed January 24, 2024. https://partnershiponai.org/aiincidentdatabase/.

28. PricewaterhouseCoopers. No longer science fiction, AI and robotics are transforming healthcare. PwC. Accessed January 24, 2024. https:// www.pwc.com/gx/en/industries/healthcare/publications/ai-roboticsnew-health/transforming-healthcare.html.

Anthony Kurec, MS, MASCP, H(ASCP)DLM is Clinical Associate Professor, Emeritus, at SUNY Upstate Medical University in Syracuse, NY. He is also a member of the MLO Editorial Advisory Board.

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CLINICAL ISSUES :: PRE-ECLAMPSIA

Complications and diagnosis of pre-eclampsia

By Jason Armstrong

Pre-eclampsia and epidemiology

Pre-eclampsia is traditionally defined as new onset hypertension and proteinuria in pregnancy,1 however, the International Federation of Gynecology and Obstetrics’ (FIGO) clinical definition describes it as sudden onset hypertension (>20 weeks of gestation) and at least one of the following: proteinuria, maternal organ dysfunction, or uteroplacental dysfunction.2 It is responsible for an estimated 70,000 maternal deaths, and 500,000 fetal deaths globally.3 Pre-eclampsia affects around 4% of pregnancies in the United States and is more common in low-to-middle income countries (LMICs), displaying an overall pooled incidence of 13% in a cohort from sub-Saharan Africa.4 The risk factors for pre-eclampsia are shown in Figure 1.

Major Risk Factors

Moderate Risk Factors

• • • • • • •

• • • • • •

Previous pre-eclampsia Chronic renal disease Chronic hypertension Diabetes Systemic lupus erythematosus Antiphospholipid syn drome BMI > 30Kg/m2

First pregnancy Age > 40 years Multifetal pregnancy Prior placental abruption Prior stillbirth Prior fetal growth restriction

Figure 1: Major and moderate risk factors of pre-eclampsia.

Photo 34206315 © Wong Yu Liang | Dreamstime.com

T

he placenta is an ephemeral organ that provides us with the nutrients necessary for development and our initial immunity, removes malevolent agents, and much more before being cast off as we enter the world. Though all organs work together to support life, as our first organ, the significance of the placenta is irrefutable. Placental dysfunction, along with several other factors, is known to contribute to the development of pre-eclampsia — a complex, multisystem hypertensive disorder of pregnancy. While the etiology of pre-eclampsia remains largely unknown, the grave complications associated with it have driven development of novel methods for predicting its onset.

The placenta is an ephemeral organ that provides us with the nutrients necessary for development and our initial immunity, removes malevolent agents, and much more before being cast off as we enter the world.

Though all organs work together to support life, as our first organ, the significance of the placenta is irrefutable. Placental dysfunction, along with several other factors, is known to contribute to the development of pre-eclampsia — a complex, multisystem hypertensive disorder of pregnancy. While the etiology of pre-eclampsia remains largely unknown, the grave complications associated with it have driven development of novel methods for predicting its onset.

Pre-eclampsia is associated with increased morbidity and mortality worldwide. In the United States, pre-eclampsia is the foremost cause of maternal death, severe maternal morbidity, maternal intensive care admissions, and premature births.5 Classical classification of pre-eclampsia included early-onset (<34 weeks gestation) and late-onset (>34 weeks gestation). However, this classification lacks clinical utility as they do not accurately illustrate maternal or fetal prognosis.

Therefore, the International Society for the study of Hypertension in Pregnancy (ISSHP) and contemporary studies prefer to classify pre-eclampsia as preterm (delivery <37 weeks of gestation), term (delivery ≥37 weeks of gestation) and postpartum pre-eclampsia (after delivery) (Figure 2).

Pre-eclampsia complications

Pre-eclampsia has been associated with acute and chronic complications for both mother and child. Worldwide risk of maternal and fetal morbidity displays adjusted odds ratios of 3.73 and 3.12 respectively (pre-eclampsia versus non pre-eclampsia).6

Acute maternal complications

A range of neurological complications are associated with preeclampsia. The most obvious is eclampsia, defined as seizures in pregnant women commonly from 20 weeks of gestation or after birth.7 Eclampsia has two proposed mechanisms: abnormal placentation reduces blood supply and causes oxidative stress, leading to endothelial damage; and elevated blood pressure in pre-eclampsia disrupts cerebral vasculature, causing hypoperfusion and damage.8 In high-income countries (HICs), most women make a full recovery, however, more severe cases of eclampsia can result in permanent disability or brain damage.7 Stroke is a significant complication of pre-eclampsia, constituting 36% of strokes related to pregnancy.9 The hypertension characteristic of pre-eclampsia can weaken the walls of blood

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CLINICAL ISSUES :: PRE-ECLAMPSIA vessels causing subarachnoid or intracerebral haemorrhage with relative risk shown to be 1.45 (95% Cl 1.20-1.76).14 Other resulting in haemorrhagic stroke. Ischaemic stroke is also of complications documented in neonates born through preconcern due to blood clotting complications, which will be eclamptic pregnancies include neonatal thrombocytopenia, discussed later. bronchopulmonary dysplasia, and a range of neurodevelopAdditional neurological complications include visual ment outcomes.15 scotoma, cortical blindness, cerebral venous sinus thrombosis, cerebral vasoconstriction syndrome, and posterior reversible Long-term complications encephalopathic syndrome (PRES). Notably, the last three in The only known cure for pre-eclampsia is delivery. However, this list frequently manifest postpartum without warning.6 the complications for both mother and child can last long HELLP (haemolysis, elevated liver enzymes, and low after even an uncomplicated delivery. After a pre-eclamptic platelets) syndrome is a liver and blood clotting disorder pregnancy, women are at increased risk of end stage renal and life-threatening complication of pre-eclampsia. HELLP disease (4.7-fold), stroke (4-fold), and vascular dementia (3syndrome most commonly presents immediately postpar- fold) later in life.5 Women are also at increased risk of other tum but can manifest any time after 20 weeks of gestation.7 cardiovascular diseases (CVD) including chronic hypertenMicroangiopathy, or small blood vessel disorder, leads to sion, coronary artery disease, congestive heart failure, and ischaemia and a subsequent increase in oxidative stress and ischaemic heart disease.5,13 In offspring, IUGR increases the inflammation, causing an increase in liver enzymes and par- risk of development of hypertension and other CVDs.13 Finally, ticipates in the initiation of HELLP. Thrombocytopenia, or offspring have been shown to be at higher risk of increased platelet deficiency, is considered a product of platelet deple- body mass index, changes in neuroanatomy, reductions in tion resulting from heightened platelet activation triggered cognitive function, and hormonal abnormalities.13 by widespread endothelial damage.6 Another blood clotting condition associated with pre-eclampsia is disFigure 2: Classical and ISSHP classification of pre-eclampsia. seminated intravascular coagulation (DIC),7 described as the dysfunction of the maternal blood clotting system reClassical ISSHP classification classification sulting in multiple organ dysfunction syndrome.10 DIC can cause excessive Early onset Preterm bleeding due to lack of clotting pro<37 weeks <34 weeks teins, or the formation of clots due to of gestation of gestation overactive clotting proteins, ultimately Late onset Term causing organ damage.10 >34 weeks ≥37 weeks As described earlier, proteinuria is of gestation of gestation included in the diagnostic criteria for Postpartum pre-eclampsia, suggesting involvediagnosed ment of the kidneys. This is caused after delivery by high concentrations of soluble FMS like tyrosine kinase 1 (sFLT-1), a placental angiogenic factor, which 20 weeks Early 34 weeks Late Preterm 37 weeks Term Delivery Postpartum inhibits proteins of the podocyte slit diaphragm, which is involved in preventing the leakage of proteins into the urine.6,11 Reduced levels of vascular endothelial growth sFLT-1/PlGF ratio factor (VEGF) and placental growth factor (PlGF) stimulates The pathophysiology of pre-eclampsia is complex and endothelin-1 expression,6 known to promote podocyte detach- enigmatic. However, placental dysfunction is known to be a factor in pre-eclampsia development. The placental-related ment, further contributing to proteinuria.12 Finally, pulmonary edema, excessive fluid accumulation angiogenic factors, sFLT-1 (anti-angiogenic), and PlGF (proin the lungs, is an acute and life-threatening complication angiogenic) have been implicated in this development. This associated with pre-eclampsia, the likelihood of which is ratio provides a useful measure of placental dysfunction as a increased via administration of antihypertensive medications.6 sharp increase in sFLT-1 and decrease in PlGF has been shown approximately five weeks before onset of pre-eclampsia.16 Acute neonatal complications Until recently, diagnosis of pre-eclampsia was one of clinical There are several documented complications affecting the manifestation. However, studies such as PROGNOSIS17 and baby of a pre-eclamptic mother. Firstly, intrauterine growth PROGNOSIS Asia,18 along with others,19,20 have shown strong restriction (IUGR) can result in underdevelopment of the utility of this ratio. The PROGNOSIS study showed that a ratio fetus because of deficient transfer of oxygen and other nu- cutoff of ≥38 was useful for ruling out pre-eclampsia within trients from mother to child.13 This can result in low birth one week with a negative predictive value (NPV) of 99.3% or weight, particularly when pre-eclampsia occurs prior to 37 four weeks with a positive predictive value (PPV) of 36.7%.17 weeks of gestation.7 In pre-eclampsia with severe symptoms, The definitions of pre-eclampsia used by the International delivery frequently occurs prematurely, either spontaneously Society for the Study of Hypertension in Pregnancy (ICCHP) or through induction. Preterm delivery can result in com- and the American College of Obstetricians and Gynaecoloplications such as neonatal respiratory distress syndrome gists (ACOG) have a PPV of around 20%, but when used in and neonates requiring ICU admission.7 Additionally, there combination with the sFLT-1/PlGF ratio, the PPV is enhanced is increased risk of stillbirth in pre-eclamptic pregnancies to 65.5% for ruling in pre-eclampsia within four weeks.21 MLO-ONLINE.COM MARCH 2024 | 15

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CLINICAL ISSUES :: PRE-ECLAMPSIA

Acute Maternal Complications Increased risk of: • Eclampsia/seizures • Stroke • Visual scotoma • Cortical blindness • Cerebral venous sinus thrombosis • Posterior reversible encephalopathic syndrome (PRES) • HELLP syndrome • Disseminated intravascular coagulation • Pulmonary edema

Long-term Maternal Complications

Acute Neonatal Complications

Long-term Offspring Complications

Increased risk of: • End stage renal disease • Stroke • Vascular dementia • Chronic hypertension • Coronary artery disease • Congestive heart failure • lschemic heart disease

Increased risk of: • Intrauterine growth restriction (UIGR) • Low birth weight • Preterm birth • Neonatal respiratory distress syndrome • Neonatal thrombocytopenia • Bronchopulmonary dysplasia

Increased risk of: • Hypertension and other forms of CVD • Stroke • Delayed physical development and sensorimotor reflex maturation • Increased body mass index • Alterations in neuroanatomy • Reductions in cognitive function • Hormonal abnormalities

Figure 3: Maternal and neonatal complications of pre-eclampsia.

Similar results have been shown in an Asian cohort in the PROGNOSIS Asia Study. Using the same cutoff value, this study reported an NPV of 98.9%.18 Furthermore, in a sub-analysis of this cohort that looked at Japanese participants, a cutoff of ≥38 displayed an NPV of 100% for ruling out pre-eclampsia within one week and a PPV of 32.4% for ruling in within four weeks.22

Accurate identification is essential

Like all clinical assays, those used to determine the sFLT-1/ PlGF ratio are subject to rigorous quality control, essential to ensure accurate results and diagnosis. The complications of pre-eclampsia are severe and often life-threating for both mother and child. Early and accurate identification is imperative for optimal monitoring, management, and timely interventions to reduce the risk of the grave consequences associated with pre-eclampsia.

The utility of the sFLT-1/PlGF ratio has been shown over various large cohorts and provides improved identification when used in combination with established clinical definitions. While the enigma of pre-eclampsia persists, the dedication of the scientific community to unravel its complexities ensures a future where expectant mothers may benefit from more effective and tailored strategies to mitigate the risks associated with this puzzling condition. Continued research endeavours will undoubtedly shape the landscape of maternal-fetal medicine, fostering advancements that hold the promise of improved outcomes for both mothers and their unborn children.

REFERENCES 1. Hypertension in pregnancy. Report of the American College of Obstetricians and Gynecologists’ Task Force on Hypertension in Pregnancy. Obstet Gynecol. 2013;122(5):1122-1131. doi:10.1097/01.

AOG.0000437382.03963.88.

2. Poon LC, Shennan A, Hyett JA, et al. The International Federation of Gynecology and Obstetrics (FIGO) initiative on pre‐eclampsia: A pragmatic guide for first‐trimester screening and prevention. Int J Gynaecol Obstet. 2019;145(S1):1-33. doi:10.1002/ijgo.12802.

7.

NHS. Pre-eclampsia. Health A to Z. Published September 28, 2021. Accessed January 3, 2024. https://www.nhs.uk/conditions/ pre-eclampsia/complications/.

8. Magley M, Hinson MR. Eclampsia. StatPearls Publishing; 2023.

9. Crovetto F, Somigliana E, Peguero A, Figueras F. Stroke during pregnancy and pre-eclampsia. Curr Opin Obstet Gynecol.

2013;25(6):425-432. doi:10.1097/GCO.0000000000000024.

10. Costello RA, Nehring SM. Disseminated Intravascular Coagulation.

StatPearls Publishing; 2023.

11. Kawachi H, Fukusumi Y. New insight into podocyte slit diaphragm, a therapeutic target of proteinuria. Clin Exp Nephrol. 2020;24(3):193-204. doi:10.1007/s10157-020-01854-3.

12. Trimarchi H. Mechanisms of Podocyte Detachment, Podocyturia, and Risk of Progression of Glomerulopathies. Kidney Dis (Basel).

2020;6(5):324-329. doi:10.1159/000507997.

13. Turbeville HR, Sasser JM. Preeclampsia beyond pregnancy: long-term consequences for mother and child. Am J Physiol Renal Physiol.

2020;1;318(6):F1315-F1326. doi:10.1152/ajprenal.00071.2020.

14. Harmon QE, Huang L, Umbach DM, et al. Risk of fetal death with preeclampsia. Obstet Gynecol. 2015;125(3):628-635. doi:10.1097/ AOG.0000000000000696.

15. Backes CH, Markham K, Moorehead P, Cordero L, Nankervis CA, Giannone PJ. Maternal Preeclampsia and Neonatal Outcomes. J Pregnancy. 2011;2011:1-7. doi:10.1155/2011/214365.

16. Verlohren S, Galindo A, Schlembach D, et al. An automated method for the determination of the sFlt-1/PIGF ratio in the assessment of preeclampsia. Am J Obstet Gynecol. 2010;202(2):161.e1-161.e11. doi:10.1016/j.ajog.2009.09.016.

17. Zeisler H, Llurba E, Chantraine F, et al. Predictive Value of the sFlt-1:PlGF Ratio in Women with Suspected Preeclampsia. N Engl J Med. 2016;7;374(1):13-22. doi:10.1056/NEJMoa1414838.

18. Bian X, Biswas A, Huang X, et al. Short-term prediction of adverse outcomes using the sFlt-1 (Soluble fms-Like Tyrosine Kinase 1)/ PlGF (Placental Growth Factor) ratio in Asian women with suspected preeclampsia. Hypertension. 2019;74(1):164-172. doi:10.1161/ HYPERTENSIONAHA.119.12760.

19. Hughes RCE, Phillips I, Florkowski CM, Gullam J. The predictive value of the sFlt‐1/PlGF ratio in suspected preeclampsia in a New Zealand population: A prospective cohort study. Aust N Z J Obstet Gynaecol.

2023;63(1):34-41. doi:10.1111/ajo.13549.

20. Nikuei P, Rajaei M, Roozbeh N, et al. Diagnostic accuracy of sFlt1/ PlGF ratio as a marker for preeclampsia. BMC Pregnancy Childbirth.

2020;20(1):80. doi:10.1186/s12884-020-2744-2.

3. Karrar SA, Hong PL. Preeclampsia. StatPearls Publishing; 2023.

21. Verlohren S, Brennecke SP, Galindo A, et al. Clinical interpretation and implementation of the sFlt-1/PlGF ratio in the prediction, diagnosis and management of preeclampsia. Pregnancy Hypertens.

2022;27:42-50. doi:10.1016/j.preghy.2021.12.003.

4. Jikamo B, Adefris M, Azale T, Alemu K. Incidence, trends and risk factors of preeclampsia in sub-Saharan Africa: a systematic review and meta-analysis. PAMJ - One Health. 2023;11:1. doi:10.11604/ pamj-oh.2023.11.1.39297.

22. Ohkuchi A, Saito S, Yamamoto T, et al. Short-term prediction of preeclampsia using the sFlt-1/PlGF ratio: a subanalysis of pregnant Japanese women from the PROGNOSIS Asia study. Hypertens Res. 2021;44(7):813-821. doi:10.1038/s41440-021-00629-x.

5. Rana S, Lemoine E, Granger JP, Karumanchi SA. Preeclampsia. Circ Res. 2019;124(7):1094-1112. doi:10.1161/CIRCRESAHA.118.313276.

Jason Armstrong BSc is a Scientific Content Creator at Randox Laboratories Ltd. After achieving his degree in Biochemistry and beginning his career in an R&D laboratory, he made the switch to pursue his passion in scientific communications.

6. Dimitriadis E, Rolnik DL, Zhou W, et al. Pre-eclampsia. Nat Rev Dis Primers. 2023;9(1):8. doi:10.1038/s41572-023-00417-6.

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INFECTION DIAGNOSTICS :: CERVICAL CANCER

Closing clinical gaps in cervical cancer

Photo 186156526 © Noipornpan | Dreamstime.com

By Allison McMullen, PhD D (ABMM)

T

he last few decades may very well be considered the decades of innovation for improvement in women’s sexual health. Since the Pap’s efficacy in detecting cervical cancer was proved in 1941,1 little innovation has occurred until recently to advance cervical health and better manage cervical cancer risk.1 Labs have played a major role in recent advancements to bridge clinical gaps in cervical health.

Once the leading cause of cancer death among women, cervical cancer is the most preventable of all gynecologic cancers. In the past 40 years, the number of cases and deaths from cervical cancer have decreased significantly as more women regularly had Pap tests and with the introduction of human papillomavirus (HPV) testing and the development of HPV vaccines.

HPV primary screening/extended genotyping

The link between HPV and cervical cancer was discovered in the 1980s. However, as not all the 100 types of HPV cause cervical cancer,it became important to distinguish which do.2 In the 1990s, high-risk HPV genotypes were identified as the main risk factor for developing cervical cancer. HPV testing was first recommended for triage of ASC-US lesions by the American Society of Colposcopy and Cervical Pathology (ASCCP) in 2001.3 So far, 14 genotypes of HPV are linked to cancer, with HPV 16 and 18 causing 70 percent of cervical cancer and cervical cancer lesions. Today, several PCR tests exist that can identify different HPV genotypes.

United States Preventive Services Task Force guidelines support different methods of screening. The most common are a primary screening HPV test or co-testing – Pap cytology testing and an HPV test. ASCCP management guidelines state that positive results from HPV primary screening for 12 high-risk HPV genotypes (exclusive of HPV 16 and 18, which are recommended for direct colposcopy) without a history of

abnormal results should be followed by another screening in one year as most of the time the infection goes away on its own.

Dual-stain cytology

However, that left a gap in the screening continuum. Healthcare providers and their patients who were sent home with high-risk genotypes other than HPV 16 and HPV 18 didn’t know for sure what would happen over the course of the year until their next exam. It is especially important to identify when an HPV infection is transforming as early as possible because only about 4 in 10 women come back for later testing,4 and a transforming HPV infection, a precursor of pre-cancer, could still occur.

To bridge this gap, a new cytology-based, dual-stain technology was introduced in 2020. P16 is a biomarker that occurs in normal cells and signifies cell cycle arrest. Ki-67 is also a biomarker that occurs in normal cells and signifies cell cycle division. Dual-stain technology can detect the tumor-suppressor protein p16 and cell proliferation marker Ki-67 in women with positive HPV results. A cell is considered positive if both stains are present in the same cell. The same sample used for HPV primary screening or Pap cytology can also be used for dual-stain cytology, and the technology is approved for use with one specific HPV screening test.

The information from the dual-stain test immediately gives healthcare providers and patients the information they need to move forward. Finding cancer as early as possible is critical for treatment. When detected at an early stage, the five-year survival rate for women with invasive cervical cancer is 92 percent.5 The IMPACT clinical trial has shown that dual-stain as a triage detected cervical disease earlier than Pap cytology in seven out of ten women who were already identified as HPV positive.6,7 This allows providers to Continued on page 34

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LAB MANAGEMENT :: PROGNOSTIC TESTING

The importance of prognostic testing for patients with chronic lymphocytic leukemia

By Mark Kruzel, MD, MBA

T

Photo 161457366 © Jarun011 | Dreamstime.com

here are many misconceptions associated with leukemia; while people generally understand that it is a cancer of the blood, most remain unaware of exactly how the disease works. Some believe it is a condition that only affects children (as it is the most common childhood cancer), though two-thirds of all leukemia patients nationwide are over 65 years old.

But leukemia can affect anyone, and the disease is further categorized by providers based on which type of white blood cell is involved (lymphocytes or myeloid cells) and how fast or slow the disease is developing (acutely or chronic).1 As the most common type of leukemia in adults, chronic lymphocytic leukemia (CLL) begins with the development of abnormal lymphocytes in the bone marrow.2,3

About CLL and its diagnosis

The median age at diagnosis is 72. As disease incidence increases with age, incidence is substantially higher in people older than 80. Only about 10% of CLL cases are in people younger than 55.4 Because the leukemic cells multiply slowly at first, most people are asymptomatic for a few years. However, the cells eventually spread to other parts of the body, including potentially the lymph nodes, liver, and spleen. Still, the course of disease for CLL is variable and can be either indolent, with slow progression that may not require treatment, or very aggressive.

How prognostic testing helps CLL patients

Given the complex pathophysiology of this disease, prognostic testing is essential to CLL management. Unlike predictive biomarker testing, which looks at the effectiveness of a patient’s treatment relative to their disease progression, a prognostic biomarker informs about a likely cancer outcome (like disease recurrence or progression) independent of treatment received.5 While most patients may not require therapy in the early stage of the disease, in some patients, CLL can be aggressive.

Within a year, tumor mass for this population may increase significantly, imposing serious health problems. It is difficult to determine based on clinical presentation which patient will progress faster than the others. Therefore, there is a need to use accurate prognostic indicators to predict the clinical course of this disease.

Recent advances in CLL therapy and biology have made it possible to develop new tests, and a combination of these tests can be particularly helpful in determining the treatment path for CLL patients. The prognosis for patients with CLL depends on many factors, including prognostic markers, several of which are used to predict survival and guide treatment. Some of these prognostic markers include immunoglobulin heavy-chain variable gene segment mutation status, cell surface markers and chromosomal aberrations.6 Because most cases of CLL are “incurable,” a provider’s main treatment goals are often to prolong survival and maintain or improve quality of life for the patient.4

Testing for prognostic markers of CLL

The wide variation in CLL outcomes makes clinical management of the condition difficult.2 Because clinical management is dependent on the presenting features and disease course, using molecular and immunophenotypic markers to help identify those patients with a higher risk for aggressive disease can help physicians select the optimal treatment and surveillance program at the time of the patient’s initial diagnosis.3 Testing for multiple biomarkers, in this case, is important as many instances of high-risk CLL have abnormal results for several prognostic markers. Few cases, however, demonstrate the presence of all the unfavorable markers. Furthermore, multiple large studies have shown that, although some unfavorable markers are closely correlated to each other, most still have independent prognostic power in multivariate models.2 Therefore, consideration of favorable and unfavorable markers and their relative prognostic power provides the most complete picture of a patient’s risk for aggressive disease.

In a comprehensive CLL Prognostic Panel,7 a patient-specific interpretation that considers the relative prognostic power of the markers detected is provided, so that the test may be used for determining disease prognosis and risk stratification.

It includes chromosome analysis, a 6-marker FISH panel, IgVH gene mutation analysis, ZAP-70, CD38, and serum ß2-microglobulin, and generates a patient-specific overall risk categorization based on all the test results.

When combined with routine laboratory studies as well as advanced testing, such as cytogenetics like karyotyping, flow cytometry, mutation analysis, and immunophenotyping, these tests can provide important insights towards both the diagnosis of CLL and the management and follow-up of patients with this disease.

Staying abreast of test results related to CLL is vital, as there are unfavorable complications associated with the disease which, left untreated, can cause other cancers, infections, or immune system dysfunction.2 Continued on page 35 MLO-ONLINE.COM MARCH 2024 | 19

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EDUCATION :: DIABETES AND HEART FAILURE

Diabetes and heart failure

Understanding the role of cardiac biomarker testing

By Dagmar Schumacher, PhD

L

aboratories may begin to see an influx of cardiac biomarker tests accompanying HbA1c testing based on updated American Diabetes Association (ADA) guidelines concerning heart failure in people with diabetes. Released late last year, the ADA’s “Standards of Care in Diabetes-2024,”1 marks the first-time use of cardiac biomarkers, namely the measurement of natriuretic peptides, for heart failure risk prediction has been included in the organization’s official guidelines for diabetes care. Specifically, the ADA’s heart failure recommendations advise that clinicians consider testing adults with diabetes by measuring B-type natriuretic peptide [BNP] or N-terminal pro-BNP [NT-proBNP] levels to help prevent stage C, or symptomatic, heart failure. 2 This is not the first time the ADA has recognized the clinical significance of this simple blood test in the management of diabetes. In its consensus report published in Diabetes Care in 2022, the ADA noted,“the addition of relatively inexpensive biomarker testing as part of the standard of care may help refine [heart failure] risk prediction in individuals with diabetes.” Endorsed by the American College of Cardiology, the consensus report also states that “substantial data indicate the ability of these biomarkers to identify those in Stage A or B [heart failure] at highest risk of progressing to symptomatic [heart failure] or death.”3 The value of natriuretic peptides and other cardiac biomarkers, such as high-sensitivity troponin, cannot be overstated when considering their impact on heart failure risk prediction, early diagnosis, clinical decision-making, and as a key in improving patient outcomes (See Figure 1). These biomarkers are the most sensitive tools available today to detect the onset of ventricular wall stress, injury, and remodeling of the heart that accompanies the development of heart failure.

Finding clinically proven ways to address the high incidence of heart failure in the United States is a major concern from a public health perspective as well. In the U.S., 6.2 million

adults are living with heart failure.4 When considering that people with diabetes—a population that numbers more than 37 million5—are at increased risk of heart failure, the number of people with the disease could rise to a staggering level in the coming years. A panel of clinical experts from the Diabetes Technology Society affirms that investing in heart failure monitoring in this population is in the public interest.

Referencing the use of cardiac biomarker testing, the panel states,“Biomarker screening for heart failure in people with diabetes is a sensible public health practice because both the disease and the available screening tests meet the criteria of a sound screening program for identifying asymptomatic heart failure.”6

Use of cardiac biomarkers for diagnosis and monitoring

First used to diagnose acute heart failure in the emergency department (ED), the use of cardiac biomarkers—specifically natriuretic peptides—has evolved over the past two decades.

Following their application in the ED, lab measurements of natriuretic peptides were used more broadly to diagnose symptomatic heart failure. The employment of cardiac biomarkers eventually expanded to include risk prediction—from the acute phase to new acute episodes—and ultimately to predict long-term risk and risk in specific populations, such as people with diabetes. Today, clinicians use regular natriuretic peptide testing to monitor patients at risk and to regularly evaluate a patient’s trajectory along the course of the disease once the patient is diagnosed with heart failure.

For prognostication and early diagnosis of heart failure in people with diabetes, the ADA’s consensus report states that “measurement of a natriuretic peptide or high-sensitivity cardiac troponin is recommended on at least a yearly basis to identify the earliest heart failure stages and implement strategies to prevent transition to symptomatic heart failure.”3

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EDUCATION :: DIABETES AND HEART FAILURE Advantages of NT-proBNP in cardiac biomarker testing

Improving patient outcomes through cardiac biomarker testing

While the ADA states that either NT-proBNP or BNP testing In people with diabetes, early diagnosis of heart failure could can be used to screen for heart failure, there are several analyt- enable targeted treatment to prevent progression of disease ical advantages of using laboratory-based NT-proBNP assays. and other adverse outcomes. If annual cardiac biomarker For testing ordered in a primary care setting, the extended monitoring is widely adopted when treating people with stability of NT-proBNP compared to BNP is a real advantage diabetes, more patients can be appropriately monitored and when samples must be sent from a clinician’s office to an off- diagnosed with heart failure earlier in the disease course. site lab. NT-proBNP has a longer half-life—60 to 120 minutes, This sets the stage for improved treatment, delayed disease as compared to 20 minutes for BNP7— and a lower intrinsic progression, and the potential for improved quality of life biological variability with approximately 25% as compared to over a longer period of time for these patients. For more BNP with approximately 40%.8 For laboratories, this enables information on Roche’s commitment to Cardiometabolic more flexibility for outreach and add-on testing. Consistent Health, visit https://diagnostics.roche.com/us/en/products/ results in the ED and inpatient and outpatient settings allow product-category/cardiometabolic.html. for more confidence in the management of heart failure.

Figure 1: The evolving role of natriuretic peptides.

Finally, it is important to note that some cardiac biomarkers are affected by angiotensin receptor-neprilysin inhibitor (ARNI), a newer, best-in-class medication that is becoming more Rule out Diagnose Heart failure Heart failure Monitoring frequently prescribed to patients with heart failure heart failure risk prediction patient patients diagnosed heart failure. In patients in the ED and discharge management at risk taking an ARNI, BNP levels will appear levels elevated, which could lead to errors in treatment. In contrast, NT-proBNP is not Courtesy of Roche Diagnostics affected by neprilysin.

With ARNIs going off patent soon, it REFERENCES is expected that more heart failure patients will be prescribed 1. American Diabetes Association Professional Practice Committee. these proven medications. As a result, I believe it is likely Standards of care in diabetes – 2024. Diabetes Care. January 2024. doi:10.2337/dc24-SINT. that NT-proBNP will become the more widely used cardiac 2. American Diabetes Association Professional Practice Committee. 10. biomarker testing strategy moving forward.

Cutoff values and what they signal for clinical management

Laboratorians have the notable job of providing results of cardiac biomarker testing to clinicians charged with making decisions about heart failure treatment. Results of laboratorybased cardiac biomarker testing help guide heart failure treatment for people with diabetes.

According to the ADA consensus report, pre-heart failure, or Stage B, is defined by an NT-proBNP value greater than 125 pg/mL. For BNP, Stage B is defined by a value greater than 50 pg/mL.3 These values indicate early molecular changes of pre-symptomatic structural heart disease and are the recommended cutoffs for outpatient non-acute testing. The rule-out cutoff for NT-proBNP for acute heart failure is <300 pg/mL (high negative predictive value) and the age-stratified rule-in cutoffs, which reflect aging effects on the heart, are <450 pg/mL for adults younger than 50, <900 pg/mL for adults ages 50 to 75, and <1800 pg/mL for adults older than age 75 (good positive predictive value).9 The rule-out cutoff for BNP is <100 pg/ml, while the rule-in cutoff, across all age groups, is >400 pg/mL.8 When cardiac biomarkers are elevated indicating a risk of heart failure, the clinical guidance for adults with type 2 diabetes is to prescribe a sodium-glucose cotransporter 2 (SGLT2) inhibitor for glycemic management. These medications also help reduce the cardiovascular risk associated with diabetes. If the patient is also obese, a glucagon-like peptide 1 (GLP-1) receptor agonist may be prescribed in addition. Optimizing the management of additional risk factors, such as hypertension and dyslipidemia, is also recommended.1,3

Cardiovascular disease and risk management: Standards of care in diabetes – 2024. Diabetes Care. January 2024;47(Supplement_1):S17 9-S218. doi:10.2337/dc24-S010.

3. Pop-Busui R, Januzzi JL, Bruemmer D, et. al. Heart failure: an underappreciated complication of diabetes. A consensus report of the American Diabetes Association. Diabetes Care. 2022;45(7):1670-1690.

4. Centers for Disease Control and Prevention. Heart failure. cdc.gov.

Updated January 5, 2023. Accessed January 25, 2024. https://www.cdc. gov/heartdisease/heart_failure.htm.

5. Centers for Disease Control and Prevention. National diabetes statistics report. cdc.gov. Updated November 29, 2023. Accessed January 25, 2024. https://www.cdc.gov/diabetes/data/statistics-report/ index.html.

6. Yeung AM, Huang J, Pandey A, et. al. Biomarkers for the diagnosis of heart failure in people with diabetes: a consensus report from Diabetes Technology Society. Prog Cardiovasc Dis. 2023;79:65-79. doi: 10.1016/j.pcad.2023.05.002.

7.

Gaggin, HK, Januzzi JL, The past, the present, and the future of natriuretic peptides in the diagnosis of heart failure, European Heart Journal Supplements, 2018;20(G)11–20. doi:10.1093/eurheartj/suy024.

8. Tsutsui H, Albert NM, Coats AJS, et al. Natriuretic peptides: role in the diagnosis and management of heart failure: a scientific statement from the Heart Failure Association of the European Society of Cardiology, Heart Failure Society of America and Japanese Heart Failure Society. Eur J Heart Fail. 2023;25(5):616-631. doi: 10.1002/ejhf.2848.

9. Januzzi JL Jr, Chen-Tournoux AA, Christenson RH, et al. N-terminal pro–B-type natriuretic peptide in the emergency department. J Am Coll Cardiol. 2018;71(11):1191-1200. doi:10.1016/j.jacc.2018.01.021.

Dagmar Schumacher, PhD, spent 12 years of her career in basic pharmacological research in the cardiovascular, diabetes and cancer disease areas at the Max Planck Institute for Heart and Lung Research and as an assistant professor at the University of Heidelberg, Germany. She joined Roche Diagnostics in 2019 to support point-of-care projects around coagulation and SARS-CoV-2. She then moved into her current position in cardiometabolism, where she works as a scientific partner in Medical and Scientific Affairs, a non-commercial division of Roche.

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STATE OF THE INDUSTRY :: LABORATORY DATA ANALYTICS

D

igital transformation of processes and the resulting data and analytics generated are growing in importance across the healthcare industry, including medical laboratories.

To understand how medical laboratory professionals are using technology and data in their operations, Medical Laboratory Observer issued its third annual State of the Industry (SOI) survey on laboratory data analytics.

Three key findings:

1. The top strategic IT priorities for labs in the next three years are infrastructure and platform development, investment in new laboratory information system (LIS), and data analytics optimization to support lab management.

2. Increased use of data analytics for all aspects of lab management has grown, including areas such as performance measurement of turnaround times, quality improvement initiatives, test costs, and forecasting of test utilization.

3. Interoperability and data integration issues with laboratory information or electronic health record (EHR) systems remain a stumbling block to labs implementing electronic processes, with more than half of respondents citing this as a challenge.

Among those surveyed this year, the majority work in hospital laboratories (57%) and hold lab manager, administrator or supervisor positions (46%). Looking at lab size, 26% work in labs with 1-10 employees, 20% in labs with 11-20 employees, 22% in labs with 21-50 employees, 13% in labs with 51-100 employees, and 19% in labs with more than 100 employees.

For a broader industry perspective on the use of technology solutions in the clinical lab environment, MLO secured

103645135 © Mast3r Dreamstime.com

Medical labs increase use of performance analytics; Target strategic IT investments By Kara Nadeau

insights from solutions providers on the data and analytics trends they are seeing in the marketplace.

Note: This year’s survey included some new questions that were not asked and answer options not provided last year. Therefore, not every response has a 2023 comparison.

Information technology

Lab professionals were asked about their LIS platforms, electronic functions performed within these systems, and their lab’s near-term strategic IT priorities.

Compared with the results of the 2023 MLO SOI survey on laboratory data analytics, slightly more lab professionals reported using LIS modules within their enterprisewide EHR systems (65% in 2024 up from 61% in 2023), while fewer reported using stand-alone LIS systems (33% in 2024 down from 39% in 2023). The percentage of those using a cloud-based LIS infrastructure remained unchanged year over year (28%) while fewer reported using in-house software/servers (70% in 2024 down from 73% in 2023).

More labs are using their LIS systems for integration with analyzers (78% in 2024 up from 71% in 2023), electronic orders and results (91% in 2024 up from 87% in 2023), billing/revenue cycle management (60% in 2024 up from 56% in 2023), and customer service (16% in 2024 up from 15% in 2023).

Fewer lab professionals reported processing the following functions electronically in their LIS systems: regulatory compliance/reporting (22% in 2024 down from 31% in 2023), point-of-care test (POCT) management (30% in 2024, down from 34% in 2023), scheduling (29% in 2024 down from 31% in 2023), inventory control/supply chain management (15%

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STATE OF THE INDUSTRY :: LABORATORY DATA ANALYTICS

87% 91%

Electronic orders and results 15% 16%

Customer service

31% 29%

Scheduling

52% 51%

QA/QC 17% 15%

Inventory control/supply chain management

56% 60%

Billing/revenue cycle management Regulatory compliance/reporting

22%

31% 71%

Integration with analyzers 34% 30%

POCT management Other (please specify)

2023 2024

4% 0

in 2024 down from 17% in 2023), and quality assurance/quality control (51% in 2024 down from 52% in 2023).

As with last year’s survey, more than half of respondents (53%) reported interoperability and data integration issues with their LIS or EHR systems as a stumbling block to implementing electronic processes.

When asked for the top strategic IT priority for their organizations in the next three years, topping the list were infrastructure and platform development (23%), new LIS (which jumped to 21% in 2024 from 15% in 2023), and data analytics optimization to support lab management (19%).

Ranking next highest was integration of the EHR system (12%), followed by revenue cycle management optimization (7%), and POCT product (2%).

Additionally, 13% of respondents chose“other” as their response, citing priorities including cybersecurity and the move to a cloud-based LIS system.

Jennifer Sanderson, MS, CTT+, MLS(ASCP)CM, Sr. Global Marketing Manager, Informatics and Services at Siemens Healthineers, commented on the growing trend among lab professionals who want greater access to data from various sources. She stated: “These professionals are interested in using the data for analytics and decision-making to drive operational efficiencies and improve the quality of care provided in their organizations.

78%

% Percent 20

Figure 1: In the 2024 survey, 94 Respondents were asked “what functions are electronic through the LIS?” (check all that apply)

40

60

80

100

To achieve operational efficiency, labs have implemented data analytics programs such as Atellica Process Manager, which consolidates data from the LIS, middleware, and diagnostic equipment to improve resource management and optimize workflow.”

Testing volumes and tracking

Jennifer Sanderson, MS, CTT+, MLS(ASCP)CM, Sr. Global Marketing Manager, Informatics and Services at Siemens Healthineers

When asked for the annual volume of testing performed by their lab, 26% of respondents reported processing between 1,000,001 to over 2,000,0000 tests (35% in 2023), 19% between 500,001 to 1,000,000 tests (16% in 2023), 21% between 100,001 to 500,000 (20% in 2023), and 25% 100,000 or fewer tests per year (29% in 2023).

The percentage of labs tracking the number of influenza tests increased (63% in 2024 up from 17% in 2023), as did the percentage of those tracking COVID-19 test numbers (72% in 2024 up from 54% in 2023).

Among the new conditions queried this year, 59% of lab professionals track the number of RSV tests, 46% the number of strep tests, and 40% the number of STI/HIV tests. An additional 11% said they track the number of tests for other conditions, including avian diseases, MRSA, hepatitis B, hepatitis C, and C. difficile, along with the basic metabolic panel (BMP), complete blood count (CBC), and comprehensive metabolic panel (CMP) tests.

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STATE OF THE INDUSTRY :: LABORATORY DATA ANALYTICS

Infrastructure and platform development

24% 23%

Revenue cycle management optimization

10%

7%

Data analytics optimization to support lab management 15%

New LIS

21%

2% 2%

POCT product Integration of the electronic medical record system

13% 12%

Other (please specify)

12% 13%

0

5

10

15 % Percent

Data analytics

23%

19%

Turning to data and analytics utilization, more lab professionals reported using data analytics for all aspects of lab management compared with last year (17% in 2024 up from 12% in 2023). Fewer respondents said they were utilizing data analytics for some aspects and planning more (36% in 2024 down from 49% in 2023). A lower percentage of respondents reported utilizing data analytics for some aspects and not planning more (10%).

Additionally, 22% of lab professionals surveyed said they have not used data analytics yet in any significant way but want to start (compared with 23% in 2023), and 12% said they were not using data analytics and have no plans to start in the near future.

Among those using data analytics in lab management, 54% reported using a tool integrated with their LIS systems (down from 69% in 2023), and 17% are using a separate tool (down from 31% in 2023). With regards to how often the data used for analytics is refreshed, 24% of respondents said their data was refreshed in real time (down from 31% in 2023), 19% daily (down from 28% in 2023), 14% weekly (down from 32% in 2023), 5% in hours (up from 3% in 2023), and 3% in minutes (down from 5% in 2023).

“Labs are generating more data across a variety of use cases (e.g., synoptic reporting, digital pathology, etc.) and technology has made this data more accessible for analysis,” said Stacia Sump, MS, MBA, Global Product Director, AI and Data Sciences, Clinisys. “Basic analytics is the starting point because it offers awareness and insight. As the old saying goes, ‘what gets measured gets improved.’ But this is just the beginning. Advanced analytics, including AI and ML capabilities, are starting to take hold in certain scenarios, such as digital pathology.”

KPIs

Topping the list of operational key performance indicators (KPIs) measured by the survey respondents’ labs were turnaround time (84% in 2024 up from 72% in 2023), quality improvement initiatives (71% in 2024), and cost per test (54% in 2024 up from 51% in 2023).

Those using KPIs to measure unnecessary tests increased from last year (23% in 2024 up from 16% in 2023), as did measurements of billable tests versus performed tests (40% in 2024 up from 35% in 2023) and medical necessity (37% in 2024 up from 33% in 2023). There was a drop in lab professionals reporting the use of KPIs to measure staff productivity goals (39% in 2024 down from 46% in 2023).

“Lab leaders need KPIs that will enable them to identify bottle necks and operate at peak efficiency without adding additional headcount,” Sump commented.“They need intelligence that proactively alerts them to problem areas that when addressed will give them the biggest bang for their buck, for instance, the same quality issue that has disrupted workflows 20 times.”

Sump also noted how clinical labs are often pressured to justify their existence and explained how utilization of data across disciplines can help lab leaders secure seats at their healthcare organizations’ executive tables.

“Clinisys is uniquely poised to assist here — providing one platform that unites multiple disciplines (e.g., anatomic and clinical pathology, molecular, toxicology, etc.) and reconciles data differences among these systems so they’re all speaking the same language. This approach breaks down the silos that exist today, making it easier for lab leaders to participate in broader initiatives that are important to their organizations, such as research projects and population health management initiatives.”

2023 2024 20

25

Figure 2: In the 2024 survey, 94 Respondents were asked “What is the top strategic IT priority for your organization in the next three years? (Select only one)”

Stacia Sump, MS, MBA, Global Product Director, AI and Data Sciences, Clinisys

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STATE OF THE INDUSTRY :: LABORATORY DATA ANALYTICS

51% 54%

Cost per test Billable tests versus performed tests

35%

40% 72%

Turnaround time 16%

Unnecessary tests

23%

2023 2024

33% 37%

Medical necessity Staff productivity goals

39%

46%

Quality improvement initiatives

71%

0

Figure 3: In the 2024 survey, 94 Respondents were asked “What operational performance indicators does your lab measure (check all that apply)?”

hc1 Insights President Michael Braverman

84%

10

Planning and forecasting

20

30

40 % Percent

Turning to forecasting trends, most respondents do not use an electronic tool for management forecasting (69% in 2024 down from 75% in 2023), while nearly one-quarter said they do perform this task electronically (24% in 2024 down from 25% in 2023).

With regards to the types of management forecasting performed, there was a jump in reported test utilization forecasting compared with last year (66% in 2024 up from 46% in 2023), and a drop in staffing level forecasting (46% in 2024 down from 50% in 2023). Those lab professionals forecasting workloads decreased only slightly (53% in 2024 down from 54% in 2023). As for supply utilization, 36% of respondents reported forecasting of this measurement.

Survey respondents also reported on the challenges their organizations currently face or will face in the short-term in their planning and forecasting environment. Staffing challenges topped the list, with 76% of those surveyed ranking it a 1 or 2 on a scale of 1-5 (this was down from 85% in 2023). Funding ranked next highest on the list, with more than half (54%) of lab professionals ranking it a 1 or 2 on the 5-point scale (down from 56% in 2023).

The next most highly ranked planning and forecasting challenge was ROI/costs, garnering 21% of 1 or 2 rankings (down from 24% in 2023).

This was followed by technology (18%) and training (13% in 2024 down from 19% in 2023). hc1 Insights President Michael Braverman commented on the challenge of staffing issues and how technology solutions that use trained artificial intelligence (AI) models can empower lab leaders to “solve crucial operational problems.” He stated: “We are seeing a growing trend from lab professionals who are challenged to get the right people in the right place at the right time and

50

60

70

80

trying to find ways to pull data from their systems and use it to make confident, proactive decisions.

Having the ability to easily justify staffing needs with dependable operations and financial data, precisely schedule staff by predicting demand for lab services across the organization, and suggesting specific, department-level resource allocations is a game changer when resources are scarce, and caregivers and patients are depending on you.”

Looking ahead

According to Sanderson, the increased desire among lab professionals to leverage data and analytics in their operations ultimately contributes to better patient care delivery and outcomes. She stated: “The momentum toward data-driven decisionmaking in medical laboratories reflects a broader commitment to advancing healthcare through technology and analytics. As this trend continues to evolve, it promises to revolutionize how labs operate, contributing to a more efficient, precise, and patient-centered healthcare ecosystem.”

“Furthermore, laboratories are focusing on patient data analytics to optimize healthcare delivery,” she added. “They are looking to various sources to provide insights into patient data, aiding in more accurate testing protocols, more timely diagnoses and treatment decisions, and for use in predictive analytics that may help identify potential future health risks and enable preventive interventions.”

Kara Nadeau has 20+ years of experience as a healthcare/medical/technology writer, having served medical device and pharmaceutical manufacturers, healthcare facilities, software and service providers, non-profit organizations and industry associations.

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MOLECULAR DIAGNOSTICS :: LIQUID BIOPSY

Liquid biopsy

The rapidly evolving technique in oncology

By Rajasri Chandra, MS, MBA

B

iopsy, generally referred to tissue biopsy, is a procedure where a tissue or a cell is taken from the body and tested for cancer. It uses a morphology-based technique to examine cancer cells. Based on the anatomical site, the specimen is collected using a needle; an image-guided procedure such as CT scan, MRI, or ultrasound; an endoscopic procedure; or surgical procedure.

Tissue biopsy versus liquid biopsy Limitations of tissue biopsies:1,2

• Tissue biopsies are an invasive method and difficult to collect for some anatomical sites.

• They provide very limited information on the intratumoral and intermetastatic genetic heterogeneity and the genetic and epigenetic changes that occur with disease progression. Thus, the therapeutic decisions must be based on historical tissue biopsy results, which may be suboptimal. 2 • They cannot identify any lesions in different locations.

• Surgical biopsies:

Analyte

Application

Circulating tumor cells (CTC)

• Provides information about the tumor’s genetic profile • Assesses metastatic potential • Evaluates drug resistance

Cell-free DNA (cfDNA)

• Provides information about the tumor’s genetic profile • Assesses metastatic potential • Evaluates drug resistance

Extracellular vesicles (EV)

• Offers insights into the tumor’s molecular characteristics • Reveals intercellular communication

Circulating tumor DNA (ctDNA) – subset of cell-free DNA (cfDNA)

• Detects and monitors cancer • Identifies mutations and copy number variations • Aids in treatment selection

MicroRNA (miRNA)

• Identifies disease-associated miRNA expression patterns • May serve as potential biomarkers for cancer and other diseases

Table 1. Analytes and their applications.

• Cannot be repeated or done frequently • Dependent on patient’s age and health condition • Involve high cost • Can cause harmful clinical complications.2 Depending on the tissue biopsy procedure, patients may experience excessive bleeding (hemorrhage), infection puncture damage to nearby tissue or organs, and skin numbness around the biopsy site. 3 On the other hand, liquid biopsy, which is based on the molecular profiling of the biofluids, is able to overcome some of the abovementioned limitations posed by tissue biopsy.1

Advantages of liquid biopsy tests:

• Liquid biopsy is minimally invasive and hence does not pose the challenges to the patient that invasive surgical tissue biopsies may cause.

• Specimens for liquid biopsy are body fluids and can be collected frequently.

• Analysis of liquid biopsy tests can provide various information in real-time including mutations in DNA, copy number alterations (CNA)s of crucial genes, transcriptome/proteome profiling, epigenetic alterations, and metabolite profiling, which would provide crucial longitudinal information and data for more accurate diagnosis by the pathologists regarding both primary and metastasized tumors.4 This information would help to understand the state of the tumor, progressive genetic and epigenetic changes occurring in the tumor, and multiple metastatic alterations, allowing proper therapeutic management of the cancer patient. 2

Background on liquid biopsy

In 1869, Thomas Ashworth discovered“some cells”in the blood of a deceased patient with metastatic cancer that looked like the primary tumor cells.5 They were later called circulating tumor cells (CTCs). CTCs are tumor cells that have detached from the primary tumor or metastatic site and got swept into the circulatory or lymphatic system.6 Catherine Alix-Panabières and Klaus Pantel coined the term“liquid biopsy”in 2010 when studying circulating tumor cells (CTCs) in cancer patients’ blood.7

Analytes for liquid biopsy tests:

Currently liquid biopsy (LB) is not restricted to CTCs only and has extended to other biomolecules. The various analytes for liquid biopsy can be classified into two main categories:1

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MOLECULAR DIAGNOSTICS :: LIQUID BIOPSY • Large or small molecules without cells or without a subcellular structure in the body fluid such as proteins, nucleic acids (e.g., cell-free DNA [cfDNA], cell-free RNA [cfRNA], microRNA), lipids, carbohydrates, and other small metabolites and metal ions • Cellular or subcellular structures such as single or clustered circulating tumor cells (CTCs), circulating cancer-related fibroblasts (CAF), immune cells, tumoreducated platelets (TEP), exosomes or extracellular vesicles (EVs), and circulating mitochondria In addition to blood, liquid biopsies have used other body fluids such as urine, saliva, cerebrospinal fluid (CSF), pleural effusion, bone marrow, sputum, etc.8,9 Tissue biopsy is still considered the gold standard for cancer diagnosis and prognosis. That said, liquid biopsy is rapidly evolving and has already shown great promise in diagnosis and treatment of cancer patients.

Potential applications of liquid biopsy:9,10

• Early detection of cancer using high blood volumes • Identification of minimal residue disease — a small number of cancer cells left in the body after treatment.

These cells have the potential to come back and cause relapse.

• High-risk population screening • Determining stage of cancer and disease recurrence monitoring • Monitoring treatment response • Identifying resistance mechanism Table 1 lists the possible applications based on the type of analyte.9

FDA-approved liquid biopsy tests

Though studies on liquid biopsies have shown promise for various applications, the liquid biopsy assays approved so far by the U.S. Food and Drug Administration (FDA) are used to identify eligibility for certain targeted treatments, gauge the response to therapy, and monitor disease progression in patients with lung, breast, prostate, colorectal, ovarian, and other solid cancers.10 Similarly, even though studies have been conducted using various analytes for the liquid biopsy tests, the liquid biopsy tests that have been approved are based on circulating tumor cells (CTCs), and circulating tumor DNA (ctDNA).10 The list of FDA-approved liquid biopsy tests are as follows:11 • Cell Search® Circulating Tumor Cell (CTC) Test detects CTCs. It is used to predict the likely outcome for people with metastatic breast, prostate, or colon cancer.

• Cobas® EGFR Mutation Test v2 detects ctDNA. It detects a mutation on the EGFR gene in non-small cell lung cancer (NSCLC).

• Guardant360® CDx detects ctDNA. • FoundationOne® Liquid CDx detects ctDNA. Guardant360® CDx and FoundationOne® Liquid are approved for companion diagnostics and general tumor profiling. Table 2 provides details.12 The most common technological methods that have been used for liquid biopsy are as follows:13 • Traditional qPCR mutational testing • Droplet digital PCR (ddPCR) • Next-generation sequencing (NGS) Newer technologies such as nanotechnology are being developed for liquid biopsy applications and have shown valuable promise.13,14

Cancer Type

Genetic change

Corresponding drug

Guardant360 CDx

Nonsmall cell lung cancer

• EGFR exon 19 deletions • L858R mutation • T790M mutation

• Osimertinib

FoundationOne Liquid CDx

Nonsmall cell lung cancer

• EGFR exon 19 deletions • L858R mutation

• Osimertinib • Gefitinib • Erlotinib

FoundationOne Liquid CDx

Prostate cancer

• BRCA1 and BRCA2 alterations

• Rucaparib

Test

Table 2. Liquid biopsy tests are also being used for companion diagnostics and precision medicine.

Limitations of liquid biopsy

Though liquid biopsies have great potential, they do have quite a few limitations. Some of the limitations are as follows:15 • Liquid biopsies are still not considered the primary test for cancer diagnosis and require an initial histologic diagnosis to be obtained by tissue biopsy, the gold standard.

• Assays for ctDNA do not provide any insight into many tumor properties and hence cannot be used to determine the stage and grade of cancer.

• Liquid biopsy is a new technique and hence biomarkers are not yet available for all types of cancers.

• The very low variant frequency in ctDNA can result in both false negatives if numbers are below an assay’s limit of detection and false positives due to background sequencing errors.

Conclusion

According to World Health Organization (WHO), cancer is the second leading cause of death worldwide, and in 2020, 10 million people died from cancer.16 Cancer is a diverse and complicated illness that is caused due to genetic and epigenetic changes in normal cells. By diagnosing cancer early and providing proper treatment, patients can be cured of cancer. Liquid biopsies are showing great promise as a diagnostic tool for early diagnosis of cancer, to monitoring cancer progression and guiding therapy. Moreover, with the integration of various technologies in genomics, proteomics, transcriptomics, and metabolomics that are taking place at a rapid pace in liquid biopsy research, it may not be too far off when liquid biopsies will be considered as the standard of care for cancer diagnosis and will aid in offering personalized therapy to cancer patients.

REFERENCES References listed online at https://mlo-online.com/53083926.

Rajasri Chandra, MS, MBA is a global marketing leader with expertise in managing upstream, downstream, strategic, tactical, traditional, and digital marketing in biotech, in vitro diagnostics, life sciences, and pharmaceutical industries. Raj is an orchestrator of go-to-market strategies driving complete product life cycle from ideation to commercialization.

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SPECIAL FEATURE :: ISO 7101:2023

A new international standard for healthcare organization management

By Dr. Donna M. Gillespie and Sheila Woodcock, MBA

D

uring World War II, to promote cooperation and standardize production among wartime allies, the United States, Canada, and Great Britain formed the United Nations Standards Coordinating Committee (UNSCC).1 When the war ended, 65 delegates representing 25 countries from the UNSCC and the International Federation of the National Standardizing Associations (ISA) met at the Institute of Civil Engineers in London, England.2 After days of intense deliberations, the UNSCC/ISA delegation of global experts established a new international standardizing body with a Central Secretariat (i.e., headquarters) located in Geneva, Switzerland.

Since its inception in 1947, 169 member countries have joined the International Organization for Standardization (ISO) to collectively publish over 25,000 expert consensus International Standards and related documents in technology, management, and manufacturing. 3

ISO 7101:2023

ISO International Standards provide requirements, recommendations, and guidance for industry sectors such as health, information technology, and transportation.

Sector-specific health standards specify requirements to enhance patient safety and encourage innovation in healthcare services, medical devices, and health informatics. On October 3, 2023, ISO published a new International Standard with requirements applicable to any organization that delivers healthcare services.4 ISO 7101:2023 is the first management system standard (MSS) produced by ISO for healthcare organizations using quality management principles (QMPs) for process and performance improvements.

Quality management principles

To build a firm foundation of quality during standards development, ISO Technical Committees (TCs) apply seven basic quality management principles (QMPs). These QMPs are the “fundamental beliefs, norms, rules and values that are accepted as true and can be used as a basis for quality management.”5 ISO 9001:2015, the most popular quality management standard

published by ISO, is based on the following QMPs:5 • QMP 1: Customer focus • QMP 2: Leadership • QMP 3: Engagement of people • QMP 4: Process approach • QMP 5: Improvement • QMP 6: Evidence-based decision making • QMP 7: Relationship management

Management system standards

diagnostic imaging services. Therefore, an organization choosing to demonstrate conformity to the requirements of ISO 7101:2023 needs to engage laboratory and diagnostic service managers in the process. Also, while it is important to read and understand an entire ISO standard, subclauses containing requirements of particular importance to medical laboratories can be found in Clause 7 and Clause 8 of ISO 7101:2023.

Healthcare organizations use management system standards (MSSs) to maintain business continuity and achieve strategic goals and objectives. Healthcare organizations often implement multiple MSSs simultaneously, thereby establishing an integrated management system of coordinated healthcare services. To facilitate this integration, ISO TCs develop MSSs with an identical or harmonized structure of clause numbers, clause titles, document text, common terms, and core definitions.6 For example, both ISO 9001:2015 and ISO 7101:2023 contain the following:7 • Clause 0: Introduction • Clause 1: Scope • Clause 2: Normative references • Clause 3: Terms and definitions • Clause 4: Context of the organization • Clause 5: Leadership • Clause 6: Planning • Clause 7: Support • Clause 8: Operation • Clause 9: Performance evaluation • Clause 10: Improvement The team of global health experts supplemented the harmonized structure of ISO 7101:2023, creating a framework of requirements for operations, quality, and risk management specifically for healthcare organizations.

Clause 7: Support

Applicability of ISO 7101:2023 to diagnostic services

People-centered care requires a culture of engagement and collaboration. Patients, families, and caregivers actively partner to improve the service experience and health outcomes. Diagnostic service managers are expected to undertake comprehensive assessments of a wide range of service-user experiences and include the results in a required management review. Workforce training is to be provided for the delivery of

Diagnostic services are an integral part of healthcare organizations, playing a significant role in the provision of information contributing to patient diagnosis and treatment. Almost all the clauses in ISO 7101:2023 apply not only to direct patient services, but equally to medical laboratories, blood transfusion services, pathology, respiratory therapy, and

The ten clauses of ISO 7101:2023 include subclauses of requirements and notes containing details to ensure consistent and effective implementation of the standard. While the heading of this clause may appear to simplify important requirements that apply to all areas of an organization, subclauses of Clause 7, the Support clause include topics such as personnel competence, orientation, and performance evaluation as well as the need for workforce awareness of the organization’s quality policy and objectives. Other requirements address communication, control of documented information, and the all-important information management systems.

Clause 8: Operation

Clause 8, the Operation clause, has subclauses for identifying and evaluating the characteristic and critical aspects of healthcare operations management, most of which are applicable to all areas of an organization, including diagnostic services. Some of the principles in the subclauses are not yet universally applied in medical laboratories and require additional clarification.

Subclause 8.10: Peoplecentred care

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SPECIAL FEATURE :: ISO 7101:2023 compassionate care, as well as to ensure a culture of inclusivity and diversity.

This subclause also provides requirements for health literacy in healthcare organizations. ISO defines health literacy as the“ability of individuals to gain access to, understand and use information in ways which promote and maintain good health for themselves, their families, and their communities.”4 Research shows low health literacy can delay life-saving healthcare services and contribute to health disparities among vulnerable patient populations.8 Subclause 8.10.5 Health literacy expects healthcare organizations to integrate health literacy into operations to ensure fair and impartial delivery of health services to all service users.

Subclause 8.11: Ethics

This is a small but especially important subclause requiring an organization to have processes and workforce training on how to address ethical dilemmas. In the laboratory setting, this may include such things as managing incidental findings unrelated to an original request or conducting human subject research.

Subclause 8.12: Patient safety

Patient safety is paramount in the delivery of services in all settings. As a minimum, consideration must be given to workforce balance, workload and workflow, institutional capacity, assessing the patient experience, and critical incident reporting.

Subclauses of 8.12 of particular relevance to diagnostic services providers are 8.12.6 Infection prevention and control (IPC), 8.12.8 Diagnostic safety, and 8.12.9 Blood transfusions. The applicability of IPC requirements depends on the extent of laboratory involvement in infection prevention and control. 8.12.8 Diagnostic safety encompasses laboratory testing, pathology, and imaging services, with requirements for accurate and timely services, result reporting, and record keeping. ISO15189 is cited as an international quality and competence document that can apply to not only medical laboratories but also diagnostic imaging, respiratory therapy, physiological sciences, blood banks, and transfusion services. 8.12.9 Blood transfusions speaks to blood transfusion safety, donor education, preparation and administration of blood products, as well as training and education, adverse events, and waste management.

Conformity assessment

To aid agencies auditing healthcare organizations using the ISO 7101:2023 International Standard, there is a

conformity assessment document, ISO/ IEC TS 17021–15: 2023. The intent is to ensure that only auditors demonstrating relevant competence are authorized to perform management system audits.9 This document supplements the requirements of ISO/IEC 17021-1:2015 and ISO/IEC 17021-3:2017.

Sustainable development goals

In addition to providing requirements, recommendations, and guidance, ISO International Standards promote economic, social, and environmental sustainability.10 In 2015, the United Nations (UN) adopted 17 sustainable development goals (SDGs) and 169 targets to promote global sustainable development.11 Through SDG 3 (Good Health and Well-being), the UN intends to “ensure healthy lives and promote well-being for all at all ages”11 and in Target 3.8 intends to “achieve universal health coverage, including financial risk protection, access to quality essential healthcare services and access to safe, effective, quality and affordable essential medicines and vaccines for all.”11 ISO 7101:2023 contributes to Target 3.8 in SDG 3 through Clause 5, the Leadership clause at subclause 5.5 Access to care.ISO 7101:2023 also contributes to SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation and Infrastructure), SDG 10 (Reduced Inequalities), and SDG 11 (Sustainable Cities and Communities).4

Conclusion

“ISO standards on healthcare enhance patient safety, help streamline supply chains, and foster innovation in digital health and sustainable healthcare solutions.”12 ISO 7101:2023 has already been adopted by several countries for use as the preferred standard to ensure quality in healthcare organizations. Conformity assessment to this standard will ensure the inclusion of laboratory and other diagnostic services in healthcare organization decision-making.

Historically, these service areas have been subject to minimal scrutiny and their invaluable contributions to patient care have often been overlooked.

REFERENCES 1. The United Nations standards coordinating committee. Science. 1944;100(2600):379-380. doi:10.1126/science.100.2600.379.b.

2. Latimer J, ed. Recollections from ISO’s First Fifty Years.; 1997. https://www.iso.org/files/ live/sites/isoorg/files/about%20ISO/docs/en/ Friendship_among_equals.pdf.

3. About us. ISO. Published 2023. Accessed January 22, 2024. https://www.iso.org/ about-us.html.

4. ISO 7101:2023. ISO. Published 2023.

Accessed January 22, 2024. https://www.iso. org/standard/81647.html.

5. ISO. Quality Management Principles.

Published 2015. Accessed January 22, 2024. https://www.iso.org/files/live/sites/isoorg/ files/store/en/PUB100080.pdf.

6. ISO/IEC Directives, Part 1. ISO. Published 2023. Accessed December 1, 2023. https:// www.iso.org/resources/publicly-availableresources.html?t=712usHn2eATZXjtj0c3FI J16gvWZXP-_fykOV8H1WAolmA84oAGBwILz OVFUEc46&view=documents#sectionisodocuments-top.

7.

ISO 9001:2015. ISO. Published 2023.

Accessed January 22, 2024. https://www.iso. org/standard/62085.html.

8. Gillespie DM. Reducing Potential Barriers To Cervical Cancer Screening Of Underserved Southeast Asian Women In Milwaukee, Wisconsin by. Hmonglibrary.org.

Accessed January 22, 2024. https://www. hmonglibrary.org/uploads/4/5/8/7/4587788/ v2_proquest_txu002240924_eco_gillespie_ donna_m_amu_dissertation.pdf.

9. Iso/iec ts 17021-15:2023. ISO. Published 2023. Accessed January 22, 2024. https:// www.iso.org/standard/85773.html.

10. Contributing to the UN Sustainable Development Goals with ISO Standards.

Published 2018. Accessed January 22, 2024. https://www.iso.org/files/live/sites/isoorg/ files/store/en/PUB100429.pdf.

11. United Nations. Transforming Our World: The 2030 Agenda for Sustainable Development United Nations. Published 2015. Accessed January 22, 2024. https:// sdgs.un.org/sites/default/files/publications/21252030%20Agenda%20for%20 Sustainable%20Development%20web.pdf.

12. Naden C. Health. ISO. Published 2023.

Accessed January 22, 2024. https://www.iso. org/sectors/health.

Dr. Donna M. Gillespie is an ASCP-certified Specialist in Microbiology with over 40 years of medical laboratory experience. Dr. Gillespie holds business administration degrees in quality systems and healthcare management. Donna is a current member of Technical Committees ISO/TC 304/WG 1 and ISO/TC 304/WG 4 for healthcare organization management and was a contributing member of Working Group (WG) 5, the delegation of global experts that developed ISO 7101:2023.

Sheila Woodcock, MBA was awarded a Distinguished Fellowship by the Canadian Society for Medical Laboratory Science (CSMLS) and has 20 years as a quality management consultant. Sheila represents Canada at ISO, serving on ISO/TC 212/WG 1 for quality and competence in the medical laboratory for 15 years and as Project Leader for ISO15189:2022.

As a member of ISO/TC 304/WG 5, she contributed to ISO 7101:2023; as the Convenor of ISO/CASCO/JWG 63, she was responsible for developing ISO/IEC 17021-15:2023.

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WSLH Proficiency Testing 32 | MARCH 2024 MLO-ONLINE.COM

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INFECTION DIAGNOSTICS :: CERVICAL CANCER Continued from page 18 treat disease earlier, a critical factor in improving cancer patient outcomes. The IMPACT dual-stain clinical trial had representation from diverse patent segments, including 21% Black, 24% Hispanic-Latino and 0.3% American Indian or Alaskan Native participants.

Testing in diverse populations is important as HPV disproportionately impacts Hispanic and Black women.8 Black women are less likely to be diagnosed with cervical cancer, yet they have the highest death rates compared to all other racial and ethnic groups due to profound survival disparities, which may be attributed to a lack of access to timely, high-quality care.9 Other more recent studies demonstrating the efficacy of dual-stain also included diverse populations. The KPNC population includes a diverse population from California, including 24% Hispanic, 18% Asian/Pacific Islander and 8% Black.10 The STRIDES study population includes a diverse population from Mississippi, with 60% being Black women.11

Self-collection

Access to HPV screening through self-collection is likely one of the last hurdles to better detect pre-cancer before it develops into cancer. It offers women an alternative to clinician collection and opens access for women who have never been tested and have no access to healthcare.

Affordable point-of-care and self-testing products are listed as an action item by the Women’s Health Innovation Opportunity Map 2023, 50 High-Return Opportunities to Advance Global Women’s Health R&D from the Innovation Equity Forum sponsored by the Bill & Melinda Gates Foundation and the US National Institutes of Health.12

The concept is for women, with healthcare professional directions, to use a swab or collection device to collect a sample from their vagina that is then sent to a lab for analysis and tested for HPV in the same manner as samples collected from providers. Collecting a sample away from the traditional doctor’s office creates more flexibility for screening to reach different populations.

The following populations may benefit from self-collection: • Women who live in rural or medically underserved areas to travel to screening.

• Women who live in a culture that requires a certain level of privacy that prevents providers from directly taking a sample.

• Women who have undergone physical trauma.

• People with a cervix whose providers believe the test to be appropriate for them.

While no self-collection test has yet been approved by the Food and Drug Administration, they are expected to be part of a future menu of HPV testing, similar to how the tests are currently used in other countries.

Self-collection, dual-stain cytology, and extended genotyping could be technologies that enable providers to make patient care decisions and make sure no women are left behind in cervical cancer screening and early detection.

REFERENCES 1. Vilos G. The history of the papanicolaou smear and the Odyssey of George and Andromache Papanicolaou. Obstet Gynecol.

1998;91(3):479-483. doi:10.1016/s0029-7844(97)00695-9.

2. HPV (human papillomavirus). U.S. Food and Drug Administration.

Published November 1, 2023. Accessed January 26, 2024. https://www. fda.gov/consumers/womens-health-topics/hpv-human-papillomavirus.

3. Saraiya M, Steben M, Watson M, Markowitz L. Evolution of cervical cancer screening and prevention in United States and Canada: implications for public health practitioners and clinicians. Prev Med. 2013;57(5):426-33. doi:10.1016/j.ypmed.2013.01.020.

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4. Rebolj M, Lynge E. Incomplete follow-up of positive HPV tests: overview of randomised controlled trials on primary cervical screening. Br J Cancer. 2010;27;103(3):310-4. doi:10.1038/sj.bjc.6605771.

9 Issues

5. Cervical cancer - statistics. Cancer.net. Published June 25, 2012.

Accessed January 26, 2024. https://www.cancer.net/cancer-types/ cervical-cancer/statistics.

6. CINtec® PLUS Cytology. Package insert. Roche Diagnostics; 2020.

7.

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Safaeian M, Wright TC Jr, Stoler MH, et al. The Improving Primary Screening and Colposcopy Triage trial: human papillomavirus, cervical cytology, and histopathologic results from the baseline and 1-year follow-up phase. Am J Obstet Gynecol. 2021;225(3):278.e1-278.e16. doi:10.1016/j.ajog.2021.03.047.

8. Hispanic or Latino people and cancer. Cdc.gov. Published July 19, 2023. Accessed January 26, 2024. https://www.cdc.gov/cancer/ health-equity/groups/hispanic-latino.htm.

9. Cohen CM, Wentzensen N, Castle PE, et al. Racial and ethnic disparities in cervical cancer incidence, survival, and mortality by histologic subtype. J Clin Oncol. 2023;41(5):1059-1068. doi:10.1200/jco.22.01424.

10. Enduring Guidelines Dual Stain Summary for Public Comment. Asccp.org.

Accessed January 29, 2024. https://www.asccp.org/publiccomments2023.

11. Risley C, Stewart MW, Geisinger KR, et al. STRIDES - Studying risk to improve Disparities in cervical cancer in Mississippi – design and baseline results of a statewide cohort study. Prev Med. 2021;153(106740):106740. doi:10.1016/j.ypmed.2021.106740.

12. Map OM 2023. Women’s health innovation women’s health innovation.

Nih.gov. Accessed January 29, 2024. https://orwh.od.nih.gov/sites/ orwh/files/docs/womens-health-rnd-opportunity-map_2023_508.pdf.

Dr. Allison McMullen is a Scientific Partner for Molecular Diagnostics and Infectious Diseases in Medical and Scientific Affairs at Roche Diagnostics.

She is the subject matter expert for Roche’s sexual health and cervical cancer solutions. Before joining Roche, Allison was the Medical Director of Microbiology at Augusta University Medical Center.

34 | MARCH 2024 MLO-ONLINE.COM 2403MLO_House_Subscription_14v.indd 1

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LAB MANAGEMENT :: PROGNOSTIC TESTING Continued from page 19 Diagnosing, staging, and treating the condition properly is vital to a patient’s survival and quality of life, which is why appropriate, accurate, and comprehensive test results are essential for clinicians to obtain.

Conclusion: CLL prognostics are a vital piece of the treatment puzzle

The clinical staging systems for chronic lymphocytic leukemia were developed 40 years ago and remain the backbone of prognostication in clinical practice and trials. As the decision for treatment initiation is supported by these staging systems, providing greater insight through the development of new techniques like next-generation sequencing has been invaluable in helping patients struggling with this disease.8 These innovations have also led to the identification of a variety of novel prognostic markers, which provide complementary information to the classical staging systems. As one example, cytogenetic and molecular genetic investigations of CLL cells have introduced more precise prognostic factors predicting time to treatment and overall survival.8 A significant percentage of CLL patients have an unsatisfactory response to treatment.9 Improving laboratory techniques and remaining abreast of new innovations can help the emergence of new tailored and targeted therapies. Research will continue to involve old and new prognostic markers, to lend new insights into the mechanisms that contribute to the pathogenesis of CLL and to explore therapeutic agents that increase survival expectancy of patients with aggressive disease.

The clinical value of prognostic biomarkers is undisputed for a variety of cancers, though it remains especially true for CLL. With such a complicated disease affecting so many – particularly older patients – predicting outcomes to better understand what course of treatment to take is critical.

The science around cancer continues to evolve, and clinicians have been doing their best to stay on top of these ever-changing developments. Working together, we can ensure patients receive the best care possible, hopefully bettering outcomes from this potentially deadly disease.

REFERENCES 1. What are the types of leukemia? Memorial Sloan Kettering Cancer Center. Accessed January 29, 2024. https://www.mskcc.org/ cancer-care/types/leukemias/types.

2. About chronic lymphocytic leukemia. American Cancer Society.

Revised January 12, 2021. Accessed July 18, 2022. https://www.cancer. org/content/dam/CRC/PDF/Public/8679.00.pdf.

3. Chronic Lymphocytic leukemia treatment (PDQ®). National Cancer Institute. Published January 26, 2024. Accessed January 29, 2024. https://www.cancer.gov/types/leukemia/hp/cll-treatment-pdq.

4. Eichhorst B, Robak T, Montserrat E, et al. Chronic lymphocytic leukaemia: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2021;32(1):23-33. doi:10.1016/j. annonc.2020.09.019.

5. Ballman KV. Biomarker: Predictive or prognostic? J Clin Oncol.

2015;33(33):3968-3971. doi:10.1200/jco.2015.63.3651.

6. National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®). Chronic lymphocytic leukemia/small lymphocytic lymphoma. Version 3.2022. Published June 3, 2022. Accessed January 29, 2024. https://www.nccn.org/.

7.

Quest Diagnostics: Test Directory. Questdiagnostics.com. Accessed January 29, 2024. https://testdirectory.questdiagnostics.com/test/ test-detail/17239/chronic-lymphocytic-leukemia-cll-prognostic-panelcomprehensive?q=Chronic%20Lymphocytic%20Leukemia%20 (CLL)%20Prognostic%20Panel,%20Comprehensive&cc=MASTER.

8. Eichhorst B, Hallek M. Prognostication of chronic lymphocytic leukemia in the era of new agents. Hematology Am Soc Hematol Educ Program. 2016;2;2016(1):149-155. doi:10.1182/asheducation-2016.1.149.

9. Ivanescu AM, Oprea M, Momanu R, Coles E, Colita A, Lupu AR. Prognosis Factors in Chronic Lymphocytic Leukemia. J Med Life.

2012;5(Spec Issue):48-53.

Mark Kruzel, MD, MBA serves as Medical Director of Oncology for Quest Diagnostics. Dr. Kruzel’s role bridges the gap from assay development to clinical utility, and he works to provide guidance on the appropriate utilization of testing. Dr. Kruzel has extensive research and industry experience ranging from managing an FDA trial site to commercializing a pharmaceutical compound for a start-up company. He has published numerous peer-reviewed journal articles as well as presented abstracts at both local and national conferences. Through his role at Quest, Dr. Kruzel has developed key opinion leader strategies, which help Quest advance the field of precision medicine.

INDEX OF ADVERTISERS Advertiser........................................................................Web........................................................................................................ Page Abbott Diagnostics.........................................................corelaboratory.abbott/hematology............................................................3 Abbott Diagnostics.........................................................diagnostics.abbott..................................................................................... 11 AUDIT MicroControls.....................................................auditmicro.com..........................................................................................33 Cygnus Medical..............................................................cygnusmedical.com....................................................................................5 Diasorin...........................................................................diasorin.com..............................................................................................27 LGP Consulting...............................................................lgpconsulting.com.................................................................................... C3 Nova Biomedical.............................................................novabiomedical.com................................................................................ C4 Sekisui Diagnostics.........................................................sekisuidiagnostics.com/respiratory-health..............................................17 Streck...............................................................................streck.com..................................................................................................25 Sysmex America.............................................................sysmex.com/PhysiciansOffice....................................................................1 Tosoh Bioscience............................................................tosohbioscience.us................................................................................... C2 This index is provided as a service. The p­ ublisher does not assume liability for errors or omissions.

MLO-ONLINE.COM MARCH 2024 | 35

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LABORATORY

INNOVATOR

Innovation is a constant

By Christina Wichmann

Quest Diagnostics’ latest report is on the country’s drug epidemic and the rise in novel psychoactive substances (NPS). Would you elaborate on what NPSs are and what is most concerning about them?

Harvey Kaufman, MD, is Senior Medical Director and head of the Quest Diagnostics Health Trends ® research program at Quest Diagnostics. In his over 30 years with the company, Dr. Kaufman has served in a wide variety of roles including as the first chief laboratory officer, first Six Sigma Quality leader, and first medical director of hospital services, business development, international and clinical trials, health and wellness, general health, sports and human performance diagnostics, point of care, venture informatics, and medical informatics. Dr. Kaufman has led Health Trends since its inception in 2005 and supports relationships with hospital health systems.

You have led Quest Diagnostics Health Trends since its inception. How do you choose the topics to highlight in these reports?

Quest Diagnostics Health Trends topics are selected with expectations that reports may reveal important new novel public health insights. We collaborate with national academic experts and leaders in public health on many of our studies. To find impactful findings, this external input helps shape the objectives and study designs. Many of our studies have been highlighted by premier news outlets, nationally and regionally, and have been integrated into professional guidelines. In 2022, the prestigious New York City Chapter of the Public Relations Society of America awarded Health Trends with numerous Big Apple awards including a Best of Best award.

Novel psychoactive substances (NPS) are synthetic or “designer” versions of established drugs, including opioids, benzodiazepines, cannabis, and cocaine.

They are chemically altered by design to enhance drug effects and elude tracking by law enforcement and, as such, may evade detection by current laboratory test methods. Further, their chemical composition frequently evolves making it a game of cat and mouse to detect. Of grave clinical concern, little is known about their immediate or long-term health effects or true prevalence in communities.

The CDC’s June 2023 Morbidity and Mortality Weekly Report (MMWR) and Quest Diagnostics Health Trends report introduced many of us to a rise in mixing fentanyl with the animal tranquilizer xylazine. Why do you think this drug is becoming more prevalent?

Xylazine is a non-opiate sedative, analgesic, and muscle relaxant only authorized in the United States for veterinary use according to the U.S. Food and Drug Administration. Xylazine is associated with psychoactive effects that for many drug users creates a longer high and has longer-lasting effects than fentanyl alone. Conversely, some drug users try to avoid drug combinations and some state it reduces the euphoric experience of other drugs.

Unfortunately, most drug users are unaware of what they are using. For manufacturers, the advantage is the extremely low cost of xylazine and the impact of its additive properties.

What effects do we know that xylazine has on people?

Human studies on the effects of xylazine have not been conducted so reports from users remain the primary source of information. Effects include drowsiness, hypotension, respiratory depression, soft tissue injuries that can result in amputations, and coma. For patients

in the emergency room, the failure of clinical laboratories to identify xylazine can provide an incomplete picture to their treating physicians. Xylazine has no approved antidote for human use, and as xylazine is not an opioid, naloxone does not reverse its effects.

Fortunately, naloxone administration can still address the effect of an opioid on breathing which may be sufficient to reduce risk of overdose deaths.

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What suggestions could you provide to the healthcare community on helping to combat our country’s drug epidemic?

Our research suggests providers and policy makers will need to adopt more creative solutions to contend with a drug crisis growing increasingly complicated by NPS. Because NPSs change so frequently, clinical laboratories need to continuously reevaluate their test solutions to keep track of them. As an example, our 88-compound NPS test panel is periodically reviewed and updated. This is to ensure the Quest Diagnostics team of toxicologists, medical experts, and data analysts include the most relevant and prevalent substances present in our communities, as reflected by trends in the company’s nationally representative dataset and the latest reports from public health, academic research, and law enforcement organizations.

What else do you do at Quest Diagnostics?

I work closely with many of the hospitals that Quest Diagnostics has established special relationships in New York and New Jersey such as Hackensack Meridian Health, Inspira, Montefiore Nyack, and New York Presbyterian. Solving problems, identifying and building innovative solutions, and serving the needs of patients is an ongoing rewarding opportunity. I also support the Quest Diagnostics collaboration with the Centers for Disease Control and Prevention and efforts in regard to advancing testing for chronic kidney disease and end-stage renal disease.

And I am inspired by my amazingly dedicated and talented colleagues who work daily to create a healthier world, one life at a time. Innovation is constant when we look.

36 | MARCH 2024 MLO-ONLINE.COM

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Today’s Blood Gas/Critical Care Test Menu Must Include iMg ePV BUN Creat/eGFR MCHC Prime Plus provides the most clinical value of any blood gas/critical care analyzer profile by adding essential tests for electrolyte balance (iMg), plasma volume (ePV), kidney function (BUN, Creatinine, eGFR), and differntiating types of anemia (MCHC).

Ionized Magnesium (iMg) Hypomagnesemia is a frequent finding in critically ill patients.1 Magnesium therapy guided by real time ionized magnesium monitoring has been shown to improve outcome in these patients.2

Estimated Plasma Volume (ePV) The plasma volume status of a patient is one of the top priorities in evaluating and treating critical illness including CHF, ARDS, AKI, Surgery, and Sepsis.3-5

BUN, Creatinine and eGFR Over 50% of patients admitted to the ICU develop some degree of acute kidney injury.6 Creatinine, eGFR, and BUN monitoring provides early indication of changes in kidney function and helps guide therapy to prevent AKI.

Test Menu pH PCO2 PO2 SO2% Hct Hb iMg Na K Cl TCO2 iCa ePV GLU Lac BUN Creat/eGFR CO-Ox MCHC

MCHC Mean corpuscular hemoglobin concentration (MCHC) provides insight into chronic low grade blood loss and differentiating types of anemia.

novabiomedical.com References 1. Soliman HM. Development of ionized hypomagnesemia is associated with higher mortality rates. 4. Niedermeyer, et al. Calculated Plasma Volume Status Is Associated With Mortality in Acute Crit Care Med 2003;31(4):1082-7.

Respiratory Distress Syndrome. Critical Care Explorations: September 2021, V3(9):1-9.

2. Wilkes NJ et al. Correction of ionized plasma magnesium during cardiopulmonary bypass reduces 5. Kim HK et al. Prognostic Value of Estimated Plasma Volume Status in Patients with Sepsis. the risk of postoperative cardiac arrhythmia. Anesth and Analg 2002;95(4) 828-834.

J Korea Med Sci 2020;9(37):1-10.

3. Kobayashi M et al. Prognostic Value of Estimated Plasma Volume in Heart Failure in Three 6. Mandelbaum T et al. Outcome of critically ill patients with acute kidney injury using the AKIN Cohort Studies; Clin Res Cardiol 2019;108(5): 549-561. criteria. Crit Care Med 2011;39(12):2659-2664.

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