Contributors to Davidson’s Principles and Practice of Medicine, 23rd Edition
The core of this book is based on the contents of Davidson’s Principles and Practice of Medicine, with material extracted and re-edited to make a uniform presentation to suit the format of this book. Although some chapters and topics have, by necessity, been cut or substantially edited, contributors of all chapters drawn upon have been acknowledged here in recognition of their input into the totality of the parent textbook.
Brian J Angus BSc, DTM&H, FRCP, MD, FFTM(Glas)
Associate Professor, Nuffield Department of Medicine, University of Oxford, UK
Quentin M Anstee BSc(Hons), PhD, MRCP
Senior Lecturer, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne; Honorary Consultant Hepatologist, Freeman Hospital, Newcastle upon Tyne, UK
Leslie Burnett MBBS, PhD, FRCPA, FHGSA
Medical Director, Garvan Institute of Medical Research, Sydney; Conjoint Professor, St Vincent’s Clinical School, Faculty of Medicine, University of New South Wales; Honorary Professor in Pathology and Genetic Medicine, Faculty of Medicine, Sydney Medical School; Honorary Associate of the School of Information Technologies, University of Sydney, Australia
Mark Byers OBE, MRCGP, MCEM, MFSEM, DA(UK)
General Practitioner, Ministry of Defence, Royal Centre for Defence Medicine, University Hospitals Birmingham, UK
Harry Campbell MD, FRCPE, FFPH, FRSE
Professor of Genetic Epidemiology and Public Health, Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, UK
Gavin PR Clunie BSc, MD, FRCP
Consultant Rheumatologist and Metabolic Bone Physician, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke’s Hospital, Cambridge, UK
Lesley A Colvin BSc, FRCA, PhD, FRCPE, FFPMRCA
Consultant, Department of Anaesthesia, Critical Care and Pain Medicine, Western General Hospital, Edinburgh; Honorary Professor in Anaesthesia and Pain Medicine, University of Edinburgh, UK
Bryan Conway MB, MRCP, PhD
Senior Lecturer, Centre for Cardiovascular Science, University of Edinburgh; Honorary Consultant Nephrologist, Royal Infirmary of Edinburgh, UK
Nicola Cooper FAcadMEd, FRCPE, FRACP
Consultant Physician, Derby Teaching Hospitals NHS Foundation Trust, Derby; Honorary Clinical Associate Professor, Division of Medical Sciences and Graduate Entry Medicine, University of Nottingham, UK
Alison L Cracknell FRCP
Consultant, Medicine for Older People, Leeds Teaching Hospitals NHS Trust, Leeds; Honorary Clinical Associate Professor, University of Leeds, UK
Dominic J Culligan BSc, MD, FRCP, FRCPath
Consultant Haematologist, Aberdeen Royal Infirmary, Aberdeen; Honorary Senior Lecturer, University of Aberdeen, UK
Graham G Dark FRCP, FHEA
Senior Lecturer in Medical Oncology and Cancer Education, Newcastle University, Newcastle upon Tyne, UK
Richard J Davenport DM, FRCPE, BMedSci
Consultant Neurologist, Royal Infirmary of Edinburgh and Western General Hospital, Edinburgh; Honorary Senior Lecturer, University of Edinburgh, UK
David H Dockrell MD, FRCPI, FRCPG, FACP
Professor of Infection Medicine, Medical Research Council/University of Edinburgh Centre for Inflammation Research, University of Edinburgh, UK
Emad El-Omar BSc(Hons), MD(Hons), FRCPE, FRSE
Professor of Medicine, St George and Sutherland Clinical School, University of New South Wales, Sydney, Australia
Marie Fallon MD, FRCP
St Columba’s Hospice Chair of Palliative Medicine, University of Edinburgh, UK
David R FitzPatrick MD, FRCPE
Professor, Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, UK
Neil R Grubb MD, FRCP
Consultant in Cardiology, Royal Infirmary of Edinburgh; Honorary Senior Lecturer in Cardiovascular Sciences, University of Edinburgh, UK
Sally H Ibbotson BSc(Hons), MD(with commendation), FRCPE
Professor of Dermatology, University of Dundee, UK
J Alastair Innes BSc, PhD, FRCPE
Consultant, Respiratory Unit, Western General Hospital, Edinburgh; Honorary Reader in Respiratory Medicine, University of Edinburgh, UK
Sara J Jenks BSc(Hons), MRCP, FRCPath
Consultant in Metabolic Medicine, Department of Clinical Biochemistry, Royal Infirmary of Edinburgh, UK
Sarah L Johnston FCRP, FRCPath
Consultant Immunologist, Department of Immunology and Immunogenetics, North Bristol NHS Trust, Bristol, UK
David EJ Jones MA, BM, PhD, FRCP
Professor of Liver Immunology, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne; Consultant Hepatologist, Freeman Hospital, Newcastle upon Tyne, UK
Peter Langhorne PhD, FRCPG
Professor of Stroke Care, Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
Stephen M Lawrie MD(Hons), FRCPsych, FRCPE(Hon)
Professor of Psychiatry, University of Edinburgh, UK
John Paul Leach MD, FRCPG, FRCPE
Consultant Neurologist, Institute of Neuroscience, Southern General Hospital, Glasgow; Head of Undergraduate Medicine and Honorary Associate Clinical Professor, University of Glasgow, UK
Gary Maartens MBChB, FCP(SA), MMed
Professor of Medicine, University of Cape Town, South Africa
Lucy Mackillop BM, MA(Oxon), FRCP
Consultant Obstetric Physician, Oxford University Hospitals NHS Foundation Trust, Oxford; Honorary Senior Clinical Lecturer, Nuffield Department of Obstetrics and Gynaecology, University of Oxford, UK
Michael J MacMahon FRCA, FICM, EDIC
Consultant in Anaesthesia and Intensive Care, Victoria Hospital, Kirkcaldy, UK
Rebecca Mann BMedSci MRCP, FRCPCh
Consultant Paediatrician, Taunton and Somerset NHS Foundation Trust, Taunton, UK
Lynn M Manson MD, FRCP, FRCPath
Consultant Haematologist, Scottish National Blood Transfusion Service, Edinburgh; Honorary Clinical Senior Lecturer, Department of Transfusion Medicine, Royal Infirmary of Edinburgh, UK
Sara E Marshall FRCP, FRCPath, PhD
Professor of Clinical Immunology, Medical Research Institute, University of Dundee, UK
Amanda Mather MBBS, FRACP, PhD
Renal Staff Specialist, Department of Renal Medicine, Royal North Shore Hospital, Sydney; Conjoint Senior Lecturer, Faculty of Medicine, University of Sydney, Australia
Simon R Maxwell BSc, MD, PhD, FRCP, FRCPE, FHEA
Professor of Pharmacology, Clinical Pharmacology Unit, University of Edinburgh, UK
David A McAllister MSc, MD, MRCP, MFPH
Wellcome Trust Intermediate Clinical Fellow and Beit Fellow, Senior Clinical Lecturer in Epidemiology, and Honorary Consultant in Public Health Medicine, University of Glasgow, UK
Rory J McCrimmon MD, FRCPE
Reader, Medical Research Institute, University of Dundee, UK
Mairi McLean MRCP, PhD
Senior Clinical Lecturer in Gastroenterology, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen; Honorary Consultant Gastroenterologist, Aberdeen Royal Infirmary, UK
Francesca EM Neuberger MRCP(UK)
Consultant Physician in Acute Medicine and Obstetric Medicine, Southmead Hospital, Bristol, UK
David E Newby BA, BSc(Hons), PhD, BM DM DSc, FMedSci, FRSE, FESC, FACC
British Heart Foundation John Wheatley Professor of Cardiology, British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, UK
John DC Newell-Price MA, PhD, FRCP
Reader in Endocrinology, Department of Human Metabolism, University of Sheffield, UK
John Olson MD, FRPCE, FRCOphth
Consultant Ophthalmic Physician, Aberdeen Royal Infirmary; Honorary Reader, University of Aberdeen, UK
Ewan R Pearson PhD, FRCPE
Clinical Reader, Medical Research Institute, University of Dundee, UK
Paul J Phelan BAO, MD, FRCPE
Consultant Nephrologist and Renal Transplant Physician, Royal Infirmary of Edinburgh; Honorary Senior Lecturer, University of Edinburgh, UK
Stuart H Ralston MRCP, FMedSci, FRSE
Arthritis Research UK Professor of Rheumatology, University of Edinburgh; Honorary Consultant Rheumatologist, Western General Hospital, Edinburgh, UK
Peter T Reid MD, FRCPE
Consultant Physician, Respiratory Medicine, Lothian University Hospitals, Edinburgh, UK
Jonathan AT Sandoe PhD, FRCPath
Associate Clinical Professor, University of Leeds, UK
Gordon R Scott BSc, FRCP
Consultant in Genitourinary Medicine, Chalmers Sexual Health Centre, Edinburgh, UK
Alan G Shand MD, FRCPE
Consultant Gastroenterologist, Western General Hospital, Edinburgh, UK
Robby M Steel MA, MD, FRCPsych
Consultant Liaison Psychiatrist, Department of Psychological Medicine, Royal Infirmary of Edinburgh; Honorary (Clinical) Senior Lecturer, Department of Psychiatry, University of Edinburgh, UK
Grant D Stewart BSc(Hons), FRCSE(Urol), PhD
University Lecturer in Urological Surgery, Academic Urology Group, University of Cambridge; Honorary Consultant Urological Surgeon, Department of Urology, Addenbrooke’s Hospital, Cambridge; Honorary Senior Clinical Lecturer, University of Edinburgh, UK
Peter Stewart MBBS, FRACP, FRCPA, MBA
Associate Professor in Chemical Pathology, University of Sydney; Area Director of Clinical Biochemistry and Head of the Biochemistry Department, Royal Prince Alfred and Liverpool Hospitals, Sydney, Australia
Mark WJ Strachan BSc(Hons), MD, FRCPE
Consultant Endocrinologist, Metabolic Unit, Western General Hospital, Edinburgh; Honorary Professor, University of Edinburgh, UK
David R Sullivan MBBS, FRACP, FRCPA, FCSANZ
Clinical Associate Professor, Faculty of Medicine, University of Sydney; Physician and Chemical Pathologist, Department of Clinical Biochemistry Royal Prince Alfred Hospital, Sydney, Australia
Shyam Sundar MD, FRCP(London), FAMS, FNASc, FASc, FNA
Professor of Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
Victoria R Tallentire BSc(Hons), DipMedEd, MRCP, MD
Consultant Physician, Western General Hospital, Edinburgh; Honorary Senior Lecturer, University of Edinburgh, UK
Katrina Tatton-Brown BA, MD, FRCP(Paeds)
Consultant and Reader in Clinical Genetics and Genomic Education, South West Thames Regional Genetics Service, St George’s Universities Hospital NHS Foundation Trust, London, UK
Simon HL Thomas MD, FRCP, FRCPE
Professor of Cellular Medicine, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK
Henry G Watson MD, FRCPE, FRCPath
Consultant Haematologist, Aberdeen Royal Infirmary, UK
Julian White MB, BS, MD, FACTM
Head of Toxinology, Women’s and Children’s Hospital, North Adelaide; Professor, University of Adelaide, Australia
John PH Wilding DM, FRCP
Professor of Medicine, Obesity and Endocrinology, University of Liverpool, UK
Miles D Witham PhD, FRCPE
Clinical Senior Lecturer in Ageing and Health, University of Dundee, UK
List of abbreviations
ABGs arterial blood gases
ACE angiotensin-converting enzyme
ACTH adrenocorticotrophic hormone
ADH antidiuretic hormone
AIDS acquired immunodeficiency syndrome
ANA antinuclear antibody
ANCA antineutrophil cytoplasmic autoantibody
ANF antinuclear factor
ANP atrial natriuretic peptide
APECED Autoimmune polyendocrinopathycandidiasis-ectodermal dystrophy
APS Antiphospholipid syndrome
APTT activated partial thromboplastin time
ARDS acute respiratory distress syndrome
ASO antistreptolysin O
AST aspartate aminotransferase
AXR abdominal X-ray
BCG Calmette–Guérin bacillus
BMI body mass index
BP blood pressure
CK creatine kinase
CNS central nervous system
CPAP continuous positive airways pressure
CRH corticotrophinreleasing hormone
CRP C-reactive protein
CSF cerebrospinal fluid
CT computed tomography/tomogram
CVP central venous pressure
CXR chest X-ray
DEXA dual-energy X-ray absorptiometry
DIC disseminated intravascular coagulation
DIDMOAD diabetes insipidus, diabetes mellitus, optic atrophy, deafness
dsDNA double-stranded deoxyribonucleic acid
DVT deep venous thrombosis
ECG electrocardiography/ electrocardiogram
ELISA enzyme-linked immunosorbent assay
ERCP endoscopic retrograde cholangiopancreatography
ESR erythrocyte sedimentation rate
FBC full blood count
FDA Food and Drug Administration
FEV1/FVC forced expiratory volume in 1 sec/forced vital capacity
FFP fresh frozen plasma
5-HT 5-hydroxytryptamine; serotonin
FOB faecal occult blood
GI gastrointestinal
GMC General Medical Council
GU genitourinary
HDL high-density lipoprotein
HDU high-dependency unit
HIV human immunodeficiency virus
HLA human leucocyte antigen
HRT hormone replacement therapy
ICU intensive care unit
IL interleukin
IM intramuscular
INR International Normalised Ratio
IV intravenous
IVU intravenous urogram/ urography
JVP jugular venous pressure
LDH lactate dehydrogenase
LDL low-density lipoprotein
LFTs liver function tests
MRA magnetic resonance angiography
MRC Medical Research Council
MRCP magnetic resonance cholangiopancreatography
MRI magnetic resonance imaging
MRSA meticillin-resistant Staphylococcus aureus
MSU mid-stream sample of urine
NG nasogastric
NICE National Institute for Health and Care Excellence
NIV non-invasive ventilation
NSAID non-steroidal antiinflammatory drug
PA postero-anterior
PCR polymerase chain reaction
PE pulmonary embolism
PET positron emission tomography
PTH parathyroid hormone
RBC red blood count
RCT randomised controlled clinical trial
SPECT single-photon emission computed tomography
STI sexually transmitted infection
TB tuberculosis
TFTs thyroid function tests
TNF tumour necrosis factor
U&Es urea and electrolytes
USS ultrasound scan
VTE venous thromboembolism
WBC/WCC white blood/cell count
WHO World Health Organization
Clinical decision making
How doctors think, reason and make decisions is arguably their most critical skill. Knowledge is necessary, but not sufficient, for good safe care.
The problem of diagnostic error
It is estimated that the diagnosis is wrong in 10% to 15% of cases in many specialties, causing much preventable morbidity.
Diagnostic error has been defined as ‘a situation in which the clinician has all the information necessary to make the diagnosis but then makes the wrong diagnosis’. Root causes include:
• No fault—for example, rare or atypical presentation.
• System error—for example, results not available, poorly trained staff.
• Human cognitive error—for example, inadequate data gathering, errors in reasoning.
Clinical reasoning
‘Clinical reasoning’ describes the thinking and decision-making processes associated with clinical practice. Errors may occur because of lack of knowledge, misinterpretation of diagnostic tests and cognitive bias (e.g. accepting another’s diagnosis unquestioningly). Other key elements include patient-centred evidence-based medicine and shared decision making with patients and/or carers.
Clinical skills and decision making
Despite diagnostic technology, the history remains crucial; studies show that physicians make a diagnosis in 70% to 90% of cases from the history alone.
Additional knowledge is needed for correct interpretation of the history and examination. For example, students learn that meningitis presents with headache, fever and meningism (photophobia, nuchal rigidity). However, the frequency with which patients present with particular features and the diagnostic weight of each feature are important in clinical reasoning.
The likelihood ratio (LR) is the probability of a finding in someone with a disease (judged by a diagnostic standard, e.g. lumbar puncture in meningism) divided by the probability of that finding in someone without disease.
An LR greater than 1 increases the probability of disease; an LR of less than 1 reduces that probability. For example, in a person presenting with headache and fever, the clinical finding of nuchal rigidity (neck stiffness) may carry little diagnostic weight, because many patients with meningitis do not have classical signs of meningism (LR of around 1).
LRs do not determine the prior probability of disease, only how a single clinical finding changes it. Clinicians have to take all available information from the history and physical examination into account. If the prior probability is high, a clinical finding with an LR of 1 does not change this.
‘Evidence-based history and examination’ is a term used to describe how clinicians incorporate knowledge about the prevalence and diagnostic weight of clinical findings into the history and physical examination.
Use and interpretation of diagnostic tests
No diagnostic test is perfect. To correctly interpret test results requires understanding of the following factors:
Normal values
Many quantitative measurements in populations have a Gaussian or ‘normal’ distribution, in which the normal range is defined as that which includes 95% of the population (±2 SD around the mean). Because 2.5% of the normal population will be above, and 2.5% below the range, it is better described as the ‘reference range’ rather than the ‘normal range’.
Results in abnormal populations also have a Gaussian distribution, with a different mean and standard deviation, although sometimes there is overlap with the reference range. The greater the difference between the result and the limits of the reference range, the higher the chance of disease.
Clinical context can affect interpretation. For example, a normal PaCO2 in the context of a severe asthma attack indicates life-threatening asthma. A low ferritin level in a young menstruating woman is not considered to be pathological.
Factors other than disease that influence results
These include: • age • ethnicity • pregnancy • sex • technical factors (e.g., high K+ in haemolysed sample).
Operating characteristics
Tests may be affected or rendered nondiagnostic by: • Patient motivation and technique (e.g. spirometry) • Operator skill • Patient’s body habitus and clinical state (e.g. echocardiography) • Paroxysmal illness (e.g. normal EEG between fits in epilepsy) • The incidental discovery of a benign abnormality
Test results should always be interpreted in the light of the patient’s history and examination.
1.1 Sensitivity and specificity
Disease No disease
Positive test A B (True positive) (False positive)
Negative test C D (False negative) (True negative)
Sensitivity = A/(A+C) × 100
Specificity = D/(D+B) × 100
Sensitivity and specificity
Sensitivity is the ability to detect true positives; specificity is the ability to detect true negatives. Even a very good test with 95% sensitivity will miss 1 in 20 people with the disease. Every test therefore has ‘false positives’ and ‘false negatives’ (Box 1.1).
A very sensitive test detects most cases of disease but generates abnormal findings in healthy people. A negative result reliably excludes disease, but a positive result does not mean disease is present. Conversely, a very specific test may miss significant pathology, but can firmly establish the diagnosis if positive. Clinicians need to know the sensitivity and specificity of the tests they use.
In choosing how a test is used, there is a trade-off between sensitivity and specificity. This is illustrated by the receiver operating characteristic curve of the test (Fig. 1.1).
An extremely important concept is this: the probability that a person has a disease depends on both the pretest probability and the sensitivity and specificity of the test. In a patient whose history suggests a high pretest probability of disease, a normal test result does not exclude the condition, but in a low-probability patient, it makes it very unlikely. This principle is illustrated in Fig. 1.2.
Prevalence of disease
The prevalence of disease in the patient’s population subgroup should inform the doctor’s estimate of pretest probability. Prevalence also influences the chance that a positive test result indicates disease. Consider a test with a false- positive rate of 5% for a disease whose prevalence is 1:1000. If 1000 people are tested, there will be 51 positive results: 50 false positives and one true positive. The chance that a person found to have a positive result actually has the disease is only 1/51, or 2%.
Predictive values combine sensitivity, specificity and prevalence, allowing doctors to address the question: ‘What is the probability that a person with a positive test actually has the disease?’. This is illustrated in Box 1.2.
Sensitivity
Fig. 1.1 Receiver operating characteristic graph illustrating the trade- off between sensitivity and specificity for a given test. The curve is generated by ‘adjusting’ the cut- off values defining normal and abnormal results, calculating the effect on sensitivity and specificity and then plotting these against each other. The closer the curve lies to the top left- hand corner, the more useful the test. The red line illustrates a test with useful discriminant value, and the green line illustrates a less useful, poorly discriminant test.
Dealing with uncertainty
Clinicians must frequently deal with uncertainty. By expressing uncertainty as probability, new information from diagnostic tests can be incorporated more accurately. However, intuition and subjective estimates of probability can be unreliable.
Knowing the patient’s true state is often unnecessary in clinical decision making. The requirement for diagnostic certainty depends on the penalty for being wrong. Different situations require different levels of certainty before starting treatment. How we communicate uncertainty to patients will be discussed later in this chapter (p. 8).
The treatment threshold combines factors such as the risks of the test and the risks versus benefits of treatment. A less effective or high risk test increases the treatment threshold.
Cognitive biases
Human thinking and decision making are prone to error. Cognitive biases are subconscious errors that lead to inaccurate judgement and illogical interpretation of information.
Humans have two distinct types of processes when it comes to thinking and decision making: type 1 and type 2 thinking.
34.6% chance of having the disease if the test is negative
90% chance of having the disease before the test is done
Patient A
50% chance of having the disease before the test is done
5.6% chance of having the disease if the test is negative
Patient B
98.3% chance of having the disease if the test is positive
86.4% chance of having the disease if the test is positive
Fig. 1.2 The interpretation of a test result depends on the probability of the disease before the test is carried out. In the example shown, the test being carried out has a sensitivity of 95% and a specificity of 85%. Patient A has very characteristic clinical findings, which make the pretest probability of the condition for which the test is being used very high—estimated as 90%. Patient B has more equivocal findings, such that the pretest probability is estimated as only 50%. If the result in Patient A is negative, there is still a significant chance that he has the condition for which he is being tested; in Patient B, however, a negative result makes the diagnosis very unlikely.
Type 1 and type 2 thinking
Cognitive psychology identifies two distinct processes when it comes to decision making: intuitive (type 1) and analytical (type 2). This has been termed ‘dual process theory’. Box 1.3 explains this in more detail.
Psychologists estimate that we spend 95% of our daily lives engaged in type 1 thinking—the intuitive, fast, subconscious mode of decision making. Learning to drive involves moving from the deliberate, conscious, slow and effortful first lesson to the automatic, fast and effortless process of an experienced driver. The same applies to medical practice, and intuitive thinking is highly efficient in many circumstances; however, in others it is prone to error.
1.2 Predictive values:
‘What is the probability that a person with a positive test actually has the disease?’
Disease
No disease
Positive test A B
(True positive) (False positive)
Negative test C D (False negative) (True negative)
Positive predictive value = A/(A+B) × 100
Negative predictive value = D/(D+C) × 100
1.3 Type 1 and type 2 thinking
Type 1
Intuitive, heuristic (pattern recognition)
Automatic, subconscious
Fast, effortless
Low/variable reliability
Vulnerable to error
Highly affected by context
High emotional involvement
Low scientific rigour
Type 2
Analytical, systematic
Deliberate, conscious
Slow, effortful
High/consistent reliability
Less prone to error
Less affected by context
Low emotional involvement
High scientific rigour
Clinicians use both type 1 and type 2 thinking. When encountering a familiar problem, clinicians employ pattern recognition and reach a differential diagnosis quickly (type 1 thinking). When encountering a problem that is more complicated, they use a slower, systematic approach (type 2 thinking). Both types of thinking interplay—they are not mutually exclusive in the diagnostic process. Errors can occur in both type 1 and type 2 thinking; for example, people can apply the wrong rules or make errors in their application while using type 2 thinking. However, it has been argued that the common cognitive biases encountered in medicine tend to occur when clinicians are engaged in type 1 thinking.
Common cognitive biases in medicine
These include:
• Overconfidence bias—the tendency to believe we know more than we actually do • Availability bias—the likelihood of diagnosing recently seen conditions • Ascertainment bias—seeing what we expect to see • Confirmation bias—only looking for evidence to support a theory, not to refute it
