TITLE:
Diagnostic Reliability of Medical Test Results as Routinely Reported to Physicians and Patients by Clinical Laboratories
AUTHORS:
Mark P. Silverman
KEYWORDS:
Medical Risk Factors, Diagnostic Reliability, Diagnostic Clinical Labs, Test Uncertainty, Point Estimate, Information Entropy, Principle of Maximum Entropy, Maximum Entropy Probability, Lipid Panel, Lipoproteins, HDL Cholesterol, LDL Cholesterol, Metabolic Panel, Coefficient of Variation
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.16 No.6,
June
24,
2026
ABSTRACT: Diagnostic clinical labs are frequently requisitioned by healthcare providers to perform tests of medical risk factors of their patients. The result of each test is ordinarily reported as a “point estimate”, i.e. a single numerical value—the “mean” of presumably one measurement—with upper and lower limits of a reference range, but with no accompanying information regarding the uncertainty of the tests, the number of trials, or the correlation of the risk factors. On the basis of such incomplete information, a physician must then gauge whether a patient is or is not at risk for the illnesses or conditions associated with the measured factor. In this article rigorous methods drawn from statistical physics (Principle of Maximum Entropy) are employed to derive the least biased, most probable predictive distribution of medical test results consistent with the information reported by clinical labs, as described above. Among other things, one can predict the probability that a repeat test result obtained from the same sample falls within or outside the reference range. It is shown theoretically and by specific examples of risk factors in the standard Lipid and Metabolic Panels how unreliable would be diagnostic inferences based on these routine clinical laboratory reports. Suggestions are made to rectify this unnecessary deficiency, which can lead to serious misdiagnoses.