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10.1093/cid/ciaa1382

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suck abstract from ncbi


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pmid33532847      Clin+Infect+Dis 2021 ; 73 (9): e3042-e3046
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  • The Limit of Detection Matters: The Case for Benchmarking Severe Acute Respiratory Syndrome Coronavirus 2 Testing #MMPMID33532847
  • Arnaout R; Lee RA; Lee GR; Callahan C; Cheng A; Yen CF; Smith KP; Arora R; Kirby JE
  • Clin Infect Dis 2021[Nov]; 73 (9): e3042-e3046 PMID33532847show ga
  • BACKGROUND: Resolving the coronavirus disease 2019 (COVID-19) pandemic requires diagnostic testing to determine which individuals are infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The current gold standard is to perform reverse-transcription polymerase chain reaction (PCR) on nasopharyngeal samples. Best-in-class assays demonstrate a limit of detection (LoD) of approximately 100 copies of viral RNA per milliliter of transport media. However, LoDs of currently approved assays vary over 10,000-fold. Assays with higher LoDs will miss infected patients. However, the relative clinical sensitivity of these assays remains unknown. METHODS: Here we model the clinical sensitivities of assays based on their LoD. Cycle threshold (Ct) values were obtained from 4700 first-time positive patients using the Abbott RealTime SARS-CoV-2 Emergency Use Authorization test. We derived viral loads from Ct based on PCR principles and empiric analysis. A sliding scale relationship for predicting clinical sensitivity was developed from analysis of viral load distribution relative to assay LoD. RESULTS: Ct values were reliably repeatable over short time testing windows, providing support for use as a tool to estimate viral load. Viral load was found to be relatively evenly distributed across log10 bins of incremental viral load. Based on these data, each 10-fold increase in LoD is expected to lower assay sensitivity by approximately 13%. CONCLUSIONS: The assay LoD meaningfully impacts clinical performance of SARS-CoV-2 tests. The highest LoDs on the market will miss a majority of infected patients. Assays should therefore be benchmarked against a universal standard to allow cross-comparison of SARS-CoV-2 detection methods.
  • |*COVID-19[MESH]
  • |*SARS-CoV-2[MESH]
  • |Benchmarking[MESH]
  • |COVID-19 Testing[MESH]
  • |Humans[MESH]
  • |Limit of Detection[MESH]
  • |RNA, Viral[MESH]


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