Abstract
Making a diagnosis is moving from possibilities to high or low probabilities. Based on history and physical examination, we think of one or more possibilities. Some, we think, are more likely than others, while some may have to be ruled out. We do diagnostic tests to increase the probability of more likely ones to nearly 95 % or above and decrease the probability of the ‘rule out’ diagnoses to near ‘zero’ or less than 5 %. Thus, the function of a diagnostic test is to increase or decrease (in one word, revise) the probability of the diseases under consideration. The probability of a disease we consider before ordering a diagnostic test (called ‘pretest probability’) should substantially change after the test. The probability we get after the test result is called ‘posttest probability’. Pretest probability is usually based on history and physical examination. In fact, it develops through several revisions, starting with some probability with the first symptom and changing the probability as newer findings emerge on history and physical examination. For example, as soon as a patient complains of chest pain of 2 h of duration (without history of trauma), we think of certain possibilities – like acute myocardial infarction (MI), pericarditis, pneumonia, pleurisy and dissection of aorta. Looking at his age of, say, 60 years, and considering the frequency, we think MI more likely than others. We ask about the characteristics of pain (onset, character, radiation, etc.) and risk factors (like diabetes, hypertension, smoking, hyperlipidemia) and accordingly revise the probability of MI to a high level (say, 60 %). Then we do certain tests like ECG and serum CPK or Trop-T. Each revises the probability further. If CK and ECG changes are borderline, the probability may not change much, but if ECG shows ST–T changes, the probability goes up, and if CK is also raised 2× normal, then the probability is nearly 99–100 % and the diagnosis is confirmed. The tests in this case are revising the pretest probability of 60 % to a posttest probability of 99–100 %. The example illustrates that the function of a diagnostic test is to revise the pretest probability of the diseases which are being considered in the differential diagnosis (7.1).
Keywords
- Positive Predictive Value
- Negative Predictive Value
- Acute Appendicitis
- Pretest Probability
- Test Prediction
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Further Reading
Guyatt G, Rennie D, editors. User’s guides to the medical literature: a manual for evidence-based clinical practice. Chicago: AMA Press; 2002. (www.ama-assn.org).
Hlatky MA, Pryor DB, Harrell FE. Factors affecting sensitivity and specificity of exercise electrocardiography. Am J Med. 1984;77:64–71.
Sox HC, Hickam DH, Marton KI, et al. Using the patient's history to estimate the probability of coronary artery disease: a comparison of primary care and referral practices. Am J Med. 1990;89:7–14.
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Prasad, K. (2014). Diagnostic Test: Fundamental Concepts. In: Fundamentals of Evidence Based Medicine. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0831-0_7
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DOI: https://doi.org/10.1007/978-81-322-0831-0_7
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