Clinical Epidemiology & Evidence-Based Medicine: Fundamental Principles of Clinical Reasoning & Research
“The presentation is consistently excellent. One, the writing is lucid and organized in a way that should be very natural for the clinical reader. Two, the text requires no background in mathematics and uses a minimum of symbols. And, three, the methodological concepts and clinical issues are well integrated through a number of carefully prepared and comprehensive examples.” Greg Samsa, Associate Director, Duke Center for Clinical Health Policy Research If a patient is older or younger than, sicker or healthier than, taller or shorter than or simply different from the subjects of a study, do the results pertain? Clinical Epidemiology & Evidence-based Medicine is a resource for all health-care workers involved in applying evidence to the care of their patients. Using clinical examples and citing liberally from the peer-reviewed literature, the book shows how statistical principles can improve medical decisions. Plus, as Katz shows how probability, risk and alternatives are fundamental considerations in all clinical decisions, he demonstrates the intuitive basis for using clinical epidemiolgy as a science underlying medical decisions. After reading this text, the practitioner should be better able to access, interpret, and apply evidence to patient care as well as better understand and control the process of medical decision making.
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absolute risk alternative applied assessed association atrial fibrillation Bayes benefit bias case-control study causality cell Chapter clinical decision clinical practice clinical trial clinician cohort study condition confounding considered coronary disease cost cutoff point decision analysis detect diagnostic test difference disease free drug evidence Evidence-Based Medicine example exposure false negatives false-negative false-positive error rate harm hypothesis testing individual patient interpretation intervention ischemia JAMA likelihood ratio lung cancer mean measure medical literature Medicine Working Group MEDLINE MeSH terms meta-analysis methods myocardial infarction negative predictive value negative test result normal distribution null hypothesis odds outcome effect placebo population positive test result posterior probability potential prevalence prior probability prior probability estimate probability of angina probability of disease probability of ischemia publication bias quantitative random rejection region reliability requires risk factors sample scenario screening statistical significance subjects theorem therapy thrombolysis tion true positives validity variable variation