Description
Book SynopsisNow in its fourth edition, Rational Diagnosis and Treatment: Evidence-Based Clinical Decision-Making is a unique book to look at evidence-based medicine and the difficulty of applying evidence from group studies to individual patients.
The book analyses the successive stages of the decision process and deals with topics such as the examination of the patient,the reliability of clinical data, the logic of diagnosis, the fallacies of uncontrolled therapeutic experience and the need for randomised clinical trials and meta-analyses. It is the main theme of the book that, whenever possible, clinical decisions must be based on the evidence from clinical research, but the authors also explain the pitfalls of such research and the problems involved in applying evidence from groups of patients to the individual patient.
For this new edition, the sections on placebo and meta-analysis and on alternative medicine have been thoroughly updated, and there is more focus
Trade Review
"An extremely interesting and intellectually stimulating book … .I would recommend this book, particularly to medical students and junior doctors." (Evidence Based Medicine, December 2008)
Table of Contents
Preface.
Introduction.
1 The Foundation of Clinical Decisions.
The clinical decision process.
Clinical data.
Scales of measurement.
Taking the history.
The physical examination.
Paraclinical findings.
Global assessments.
2 Reliability and relevance of clinical data.
Clinical data on an interval scale.
Clinical data on an ordinal scale.
Clinical data on a binary scale.
Descriptive paraclinical findings.
Descriptive physical signs.
The statistical concept of normality.
The concept of disease.
Interpretation and relevance.
Indicators.
3 The disease classification.
The historical perspective.
The seventeenth and eighteenth centuries.
The nineteenth and twentieth centuries.
The theoretical perspective.
The mechanical model of disease.
Molecular biology.
Disease and the environment.
The practical perspective.
Name of disease.
Definition.
Causes of disease (aetiology and pathogenesis).
The clinical picture.
Diagnosis and treatment.
4 Diagnosis.
The diagnostic universe.
Diagnosis of diseases with an accessible defining criterion.
The direct method for assessing the accuracy of test results.
The indirect method for assessing the accuracy of test results.
Terminological confusion.
Quantitative data.
Diagnosis of diseases with a concealed defining criterion.
Syndrome diagnosis.
Three patients.
Diagnosis in practice.
Frequential and subjective probabilities.
Diagnostic strategy.
5 Uncontrolled experience.
Uncontrolled experience in a pre-scientific era.
The numerical method.
The era of laboratory research.
The spontaneous course of the disease.
Regression towards the mean.
Run of luck.
Bias.
The placebo effect.
The need for controlled experience.
Alternative medicine: pseudoscientific thinking.
6 The randomized clinical trial.
Selection of patients.
Randomization.
Choice of treatment in the control group.
Principles of blinding.
Cross-over trials.
Measures of benefits and harms.
Stopping rules.
Assessment of the results.
Statistical analysis.
Hypothesis testing.
Estimation.
Other statistical measures of effect.
Subgroup analyses.
Systematic reviews.
From trials to practice.
Evidence-based medicine and commercial pressures.
7 Medicine and the humanities.
The four components of clinical reasoning.
The empathic-hermeneutic component.
The ethical component.
Three kinds of norms.
The foundation of health care ethics.
The structure of ethical reasoning.
Assessment of the facts of the case.
Consequential considerations.
Deontological considerations.
The ethical decision.
Quality of life.
Autonomy and paternalism.
Clinical examples.
Clinical research ethics.
8 Critical reading of medical journals.
Logical analysis of medical papers.
Assets and limitations of cohort studies.
Assets and limitations of case-control studies.
Other designs.
Descriptive statistics.
Estimation.
Testing Hypotheses.
Psuedohypothetico-deductive logic.
Wrong sampling unit.
Sample size calculations.
Interpretation of P-values.
Statistical tests.
Examples.
Correlation analysis.
Life table analysis.
References.
Index.
