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When to rule out COVID-19: How many negative RT-PCR tests are needed?

ABSTRACT: Amidst the COVID-19 pandemic, clinicians have been plagued with dilemmas related to the uncertainty about diagnostic testing for the virus. It has become commonplace for a patient under investigation (PUI) to repeatedly test negative but have imaging findings that are consistent with COVID-19. This raises the question of when the treating team should entertain alternative diagnoses. We present such a case to help provide a framework for how to weigh repeatedly negative test results in clinical decision making when there is ongoing concern for COVID-19.

SUBMITTER: Isikbay M

PROVIDER: S-EPMC7434325 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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When to rule out COVID-19: How many negative RT-PCR tests are needed?

Isikbay Masis M Henry Travis S TS Frank James A JA Hope Michael D MD

Respiratory medicine case reports 20200818

Amidst the COVID-19 pandemic, clinicians have been plagued with dilemmas related to the uncertainty about diagnostic testing for the virus. It has become commonplace for a patient under investigation (PUI) to repeatedly test negative but have imaging findings that are consistent with COVID-19. This raises the question of when the treating team should entertain alternative diagnoses. We present such a case to help provide a framework for how to weigh repeatedly negative test results in clinical d ...[more]

PMID: 32837902

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Project description:BackgroundThe emergency of new COVID-19 variants over the past three years posed a serious challenge to the public health. Cities in China implemented mass daily RT-PCR tests by pooling strategies. However, a random delay exists between an infection and its first positive RT-PCR test. It is valuable for disease control to know the delay pattern and daily infection incidences reconstructed from RT-PCR test observations.MethodsWe formulated the convolution model between daily incidences and positive RT-PCR test counts as a linear inverse problem with positivity restrictions. Consequently, the Richard-Lucy deconvolution algorithm was used to reconstruct COVID-19 incidences from daily PCR tests. A real-time deconvolution was further developed based on the same mathematical principle. The method was applied to an Omicron epidemic data set of a bar outbreak in Beijing and another in Wuxi in June 2022. We estimated the delay function by maximizing likelihood via an E-M algorithm.ResultsThe delay function of the bar-outbreak in 2022 differs from that reported in 2020. Its mode was shortened to 4 days by one day. A 95% confidence interval of the mean delay is [4.43,5.55] as evaluated by bootstrap. In addition, the deconvolved infection incidences successfully detected two associated infection events after the bar was closed. The application of the real-time deconvolution to the Wuxi data identified all explosive incidence increases. The results revealed the progression of the two COVID-19 outbreaks and provided new insights for prevention and control strategies, especially for the role of mass daily RT-PCR testing.ConclusionsThe proposed deconvolution method is generally applicable to other infectious diseases if the delay model can be assumed to be approximately valid. To ensure a fair reconstruction of daily infection incidences, the delay function should be estimated in a similar context in terms of virus variant and test protocol. Both the delay estimate from the E-M algorithm and the incidences resulted from deconvolution are valuable for epidemic prevention and control. The real-time feedback is particularly useful during the epidemic's acute phase because it can help the local disease control authorities modify the control measures more promptly and precisely.

Project description:BackgroundA false-negative case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is defined as a person with suspected infection and an initial negative result by reverse transcription-polymerase chain reaction (RT-PCR) test, with a positive result on a subsequent test. False-negative cases have important implications for isolation and risk of transmission of infected people and for the management of coronavirus disease 2019 (COVID-19). We aimed to review and critically appraise evidence about the rate of RT-PCR false-negatives at initial testing for COVID-19.MethodsWe searched MEDLINE, EMBASE, LILACS, as well as COVID-19 repositories, including the EPPI-Centre living systematic map of evidence about COVID-19 and the Coronavirus Open Access Project living evidence database. Two authors independently screened and selected studies according to the eligibility criteria and collected data from the included studies. The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. We calculated the proportion of false-negative test results using a multilevel mixed-effect logistic regression model. The certainty of the evidence about false-negative cases was rated using the GRADE approach for tests and strategies. All information in this article is current up to July 17, 2020.ResultsWe included 34 studies enrolling 12,057 COVID-19 confirmed cases. All studies were affected by several risks of bias and applicability concerns. The pooled estimate of false-negative proportion was highly affected by unexplained heterogeneity (tau-squared = 1.39; 90% prediction interval from 0.02 to 0.54). The certainty of the evidence was judged as very low due to the risk of bias, indirectness, and inconsistency issues.ConclusionsThere is substantial and largely unexplained heterogeneity in the proportion of false-negative RT-PCR results. The collected evidence has several limitations, including risk of bias issues, high heterogeneity, and concerns about its applicability. Nonetheless, our findings reinforce the need for repeated testing in patients with suspicion of SARS-Cov-2 infection given that up to 54% of COVID-19 patients may have an initial false-negative RT-PCR (very low certainty of evidence).Systematic review registrationProtocol available on the OSF website: https://tinyurl.com/vvbgqya.

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When to rule out COVID-19: How many negative RT-PCR tests are needed?

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When to rule out COVID-19: How many negative RT-PCR tests are needed?

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