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Introduction: Diagnostic tests are never perfect, leading to inaccurate decisions by healthcare workers. Study aimed to compile the evidence and facilitate the epidemiological interpretation of testing available for the COVID-19. Methods: Published systematic reviews, especially Cochrane reviews and evidence summaries were used. Positive-predictive-values (PPV), negative-predictive-values (NPV), and its 95% confidence intervals (CI) were calculated following application to a hypothetical cohort of 1000 patients, the reported sensitivities and specificities and assumed pre-test probability levels. Results: At a low pre-test probability level, PPV is 63.6%(95%CI: 37.8%-83.5%) when assumed 72%sensitivity of the antigen test among symptomatic patients and 60.0% 95%CI: 33.3%-81.8%) when assumed 58% sensitivity of the antigen test among asymptomatic patients. If the sensitivity is low, PPV will become a low value. PPV is high with a higher pre-test probability level; however, the NPV is 78%(95%CI: 75.5%-80.4%) among symptomatic and 70.3%(95%CI: 68%-72.4%) among asymptomatic patients. PPV is 44.4% (95%CI: 28.6%-61.5% at a low pre-test probability level) when assumed 80% sensitivity for the RT-PCR test. Further, assuming that the sensitivity of 95%, PPV is
47.4% (95%CI: 32%-63%). At a higher pre-test probability level, the NPV is 83.2% (95%CI: 80.6%-85.5%) when assumed 80% sensitivity. Further, the sensitivity of the RT-PCR is 95%, NPV is 95.2%(95%CI: 93.1% to 96.7%). Conclusions: With a low pre-test probability, positive results should be interpreted cautiously and need a second specimen tested for confirmation for both Ag and PCR testing. With higher pre-test probability, the confidence in negative COVID-19 test results is low. Therefore, a combination of symptoms, signs, laboratory investigations can be used with antigen and RT-PCR tests, for diagnosis of COVID-19. |
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