key: cord-0748643-3fcuihr6
authors: Galmiche, S; Fernandes-Pellerin, S; Ungeheuer, MN; Schwartz, O; Attia, M; Hoen, B
title: High negative predictive value of RT-PCR in patients with high likelihood of SARS-CoV-2 infection
date: 2021-11-24
journal: Infect Dis Now
DOI: 10.1016/j.idnow.2021.11.005
sha: 9e531127bf2d94d91a562491862386f712850d86
doc_id: 748643
cord_uid: 3fcuihr6

nan

All four participants had been tested in the same participating center for symptoms compatible with COVID-19 (including one with anosmia and ageusia), two of whom also reported contact with a confirmed case of SARS-CoV-2 infection. None of them had to be hospitalized. In these four participants, time from symptom onset to RT-PCR test ranged from 2 to 11 days and blood sampling for serology was performed between 21 and 29 days after symptom onset and between 10 and 21 days after RT-PCR test.

In a population with high pre-test probability of SARS-CoV-2 infection, the negative predictive value of SARS-CoV-2 RT-PCR was high. The serology technique we used has a very high sensitivity, which makes it very unlikely that a seropositive participant went undetected [5] .

sampling. However, this is unlikely given the short time interval between RT-PCR and serology samplings. Furthermore, all seropositive participants had symptoms compatible with COVID-19 at the time of RT-PCR testing, including one with anosmia and ageusia, two symptoms that have a high positive predictive value for COVID-19 diagnosis [6, 7] . A systematic review of falsenegative results of SARS-CoV-2 RT-PCR showed that the probability of false-negative results decreases from the day of exposure to 3 days after symptom onset and then increases again over the following days [8] . Three of the four false-negative patients of this study were tested at least 5 days after symptom onset, which may help explain the false-negative results. As all seropositive participants underwent RT-PCR testing in a single center, we may raise the hypothesis of swab performance or defective RT-PCR kit issues. Other possible explanations for false-negative RT-PCR tests include the absence of detectable viral shedding throughout the disease or a swab for RT-PCR testing performed outside the time period of detectable viral Page 5 of 6 J o u r n a l P r e -p r o o f 5 shedding (especially in the two participants in whom swabs were performed respectively 8 and 11 days after symptom onset) [9] . As many countries have implemented mitigation strategies, resulting in bringing incidence rates at lower levels than those observed during the study period, the current negative predictive value is probably even higher than estimated here.

Limitations of this study include the absence of repeated RT-PCR tests, which could have identified a transient detectable viral shedding period, and the lack of detailed information on the RT-PCR kits used in the various centers.

The negative predictive value of SARS-CoV-2 RT-PCR in patients with a high pre-test probability of having SARS-CoV-2 infection was high. This finding supports strategies based on isolation of patients when COVID-19 is suspected and on lifting isolation if the RT-PCR test is negative.

False-negative results of initial RT-PCR assays for COVID-19: A systematic review

Estimating the burden of SARS-CoV-2 in France

Immune response following infection with SARS-CoV-2 and other coronaviruses: A rapid review

A comparison of four serological assays for detecting anti-SARS-CoV-2 antibodies in human serum samples from different populations

Serologic responses to SARS-CoV-2 infection among hospital staff with mild disease in eastern France

Characteristics Associated with Olfactory and Taste Disorders in COVID-19

Utility of hyposmia and hypogeusia for the diagnosis of COVID-19

Variation in False-Negative Rate of Reverse Transcriptase Polymerase Chain Reaction-Based SARS-CoV-2 Tests by Time Since Exposure

SARS-CoV-2 detection, viral load and infectivity over the course of an infection

We would like to thank collaborators at the Institut Pasteur, Linda Sangari, Sophie Chaouche, Dr Charlotte Renaudat at the ICAReB platform, Thomas Obadia at the Bioinformatics and Biostatistics Hub, Cassandre von Platen and Tan-Phuc Buivan at the Center for Translational Sciences.