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A brief note about likelihood ratios

Published online by Cambridge University Press:  21 May 2015

Andrew Worster  and
Christopher Carpenter
Andrew Worster
Affiliation:
Division of Emergency Medicine, McMaster University, Hamilton, Ont.
Christopher Carpenter*
Affiliation:
Division of Emergency Medicine, Evidence Based Medicine, Washington University School of Medicine in St. Louis, St. Louis, Miss.
*
Division of Emergency Medicine, Evidence Based Medicine, Washington University School of Medicine in St. Louis, Box 8072, 660 S. Euclid Ave., St. Louis MO 63110; carpenterc@wusm.wustl.edu

Abstract

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Type
Education • Enseignment
Information
Canadian Journal of Emergency Medicine , Volume 10 , Issue 5 , September 2008 , pp. 441 - 442
Copyright
Copyright © Canadian Association of Emergency Physicians 2008

References

1.Azzam, MH, Lang, E, Segal, E. Terminating resuscitation for out-of-hospital cardiac arrest? CJEM 2008;10:474–7.CrossRefGoogle ScholarPubMed
2.Morrison, LJ, Visentin, LM, Kiss, A, et al.Validation of a rule for termination of resuscitation in out-of-hospital cardiac arrest. N Engl J Med 2006;355:478–87.CrossRefGoogle ScholarPubMed
3.Hayden, SR, Brown, MD. Likelihood ratio: a powerful tool for incorporating the results of a diagnostic test into clinical decision making. Ann Emerg Med 1999;33:575–80.Google Scholar
4.Altman, DG, Bland, JM. Diagnostic tests 2: predictive values. BMJ 1994;309:102.CrossRefGoogle ScholarPubMed
5.Sackett, DL, Straus, S, Richardson, WS, et al.Evidence-based medicine. How to practise and teach EBM. 2nd ed. Edinburgh: Churchill Livingstone; 2000: 67–93.Google Scholar
6.Jaeschke, R, Guyatt, GH, Sackett, DL. Users’ guides to the medical literature. III. How to use an article about a diagnostic test. B. What are the results and will they help me in caring for my patients? The Evidence-Based Medicine Working Group. JAMA 1994;271:703–7.CrossRefGoogle Scholar
7.Fagan, TJ. Nomogram for Bayes Theorem. N Engl J Med 1975;293:257.Google Scholar
8.Sotos, JG. Simplified calculations using likelihood ratios. ACP J Club 2007;146:A10.Google Scholar
9.Perera, R. Making sense of diagnostic tests with likelihood ratios. ACP J Club 2007;146:A8–9.Google Scholar
10.Deeks, JJ, Altman, DG. Diagnostic tests 4: likelihood ratios. BMJ 2004;329:168–9.CrossRefGoogle ScholarPubMed
11.Brown, MD, Reeves, MJ. Interval likelihood ratio: another advantage for the evidence-based diagnostician. Ann Emerg Med 2003;42:292–7.CrossRefGoogle ScholarPubMed
12.Gallagher, EJ. The problem with sensitivity and specificity. Ann Emerg Med 2003;42:298–303.Google Scholar
13.Phelps, MA, Levitt, A. Pretest probability estimates: A pitfall to the clinical utility of evidence-based medicine? Acad Emerg Med 2004;11:692–4.Google Scholar
14.Scott, IA. Estimating disease likelihood: a case of rubbery figures. Med J Aust 2004;180:438–9.Google Scholar
15.Richardson, WS, Polashenski, WA, Robbins, BW. Could our pretest probabilities become evidence based? J Gen Intern Med 2003;18:203–8.CrossRefGoogle ScholarPubMed