Dataset Information

Association Between SARS-CoV-2 Cycle Threshold Values and Clinical Outcomes in Patients With COVID-19: A Systematic Review and Meta-analysis.

ABSTRACT: Cycle threshold (C_T) values are correlated with the amount of viral nucleic acid in a sample and may be obtained from some qualitative real-time polymerase chain reaction tests used for diagnosis of most patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, C_T values cannot be directly compared across assays, and they must be interpreted with caution as they are influenced by sample type, timing of sample collection, and assay design. Presently, the correlation between C_T values and clinical outcomes is not well understood. We conducted a systematic review and meta-analysis of published studies through April 19, 2021, that reported an association between C_T values and hospitalization, disease severity, and mortality in patients ≥18 years old with SARS-CoV-2. A meta-analysis of 7 studies showed no significant difference in mean C_T values between hospitalized and nonhospitalized patients. Among hospitalized patients, those with C_T values <25 had a high risk of more severe disease and mortality than patients with C_T values >30 (odds ratio [OR], 2.31; 95% CI, 1.70 to 3.13; and OR, 2.95; 95% CI, 2.19 to 3.96; respectively). The odds of increased disease severity and mortality were less pronounced in patients with C_T values of 25-30 compared with >30.

SUBMITTER: Shah VP

PROVIDER: S-EPMC8465328 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Association Between SARS-CoV-2 Cycle Threshold Values and Clinical Outcomes in Patients With COVID-19: A Systematic Review and Meta-analysis.

Shah Vishal P VP Farah Wigdan H WH Hill James C JC Hassett Leslie C LC Binnicker Matthew J MJ Yao Joseph D JD Murad M Hassan MH

Open forum infectious diseases 20210831 9

Cycle threshold (C<sub>T</sub>) values are correlated with the amount of viral nucleic acid in a sample and may be obtained from some qualitative real-time polymerase chain reaction tests used for diagnosis of most patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, C<sub>T</sub> values cannot be directly compared across assays, and they must be interpreted with caution as they are influenced by sample type, timing of sample collection, and assay design. Presentl ...[more]

PMID: 34584900

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Project description:BackgroundThe distribution of population-level real-time reverse transcription-polymerase chain reaction (RT-PCR) cycle threshold (Ct) values as a proxy of viral load may be a useful indicator for predicting COVID-19 dynamics.ObjectiveThe aim of this study was to determine the relationship between the daily trend of average Ct values and COVID-19 dynamics, calculated as the daily number of hospitalized patients with COVID-19, daily number of new positive tests, daily number of COVID-19 deaths, and number of hospitalized patients with COVID-19 by age. We further sought to determine the lag between these data series.MethodsThe samples included in this study were collected from March 21, 2021, to December 1, 2021. Daily Ct values of all patients who were referred to the Molecular Diagnostic Laboratory of Iran University of Medical Sciences in Tehran, Iran, for RT-PCR tests were recorded. The daily number of positive tests and the number of hospitalized patients by age group were extracted from the COVID-19 patient information registration system in Tehran province, Iran. An autoregressive integrated moving average (ARIMA) model was constructed for the time series of variables. Cross-correlation analysis was then performed to determine the best lag and correlations between the average daily Ct value and other COVID-19 dynamics-related variables. Finally, the best-selected lag of Ct identified through cross-correlation was incorporated as a covariate into the autoregressive integrated moving average with exogenous variables (ARIMAX) model to calculate the coefficients.ResultsDaily average Ct values showed a significant negative correlation (23-day time delay) with the daily number of newly hospitalized patients (P=.02), 30-day time delay with the daily number of new positive tests (P=.02), and daily number of COVID-19 deaths (P=.02). The daily average Ct value with a 30-day delay could impact the daily number of positive tests for COVID-19 (β=-16.87, P<.001) and the daily number of deaths from COVID-19 (β=-1.52, P=.03). There was a significant association between Ct lag (23 days) and the number of COVID-19 hospitalizations (β=-24.12, P=.005). Cross-correlation analysis showed significant time delays in the average Ct values and daily hospitalized patients between 18-59 years (23-day time delay, P=.02) and in patients over 60 years old (23-day time delay, P<.001). No statistically significant relation was detected in the number of daily hospitalized patients under 5 years old (9-day time delay, P=.27) and aged 5-17 years (13-day time delay, P=.39).ConclusionsIt is important for surveillance of COVID-19 to find a good indicator that can predict epidemic surges in the community. Our results suggest that the average daily Ct value with a 30-day delay can predict increases in the number of positive confirmed COVID-19 cases, which may be a useful indicator for the health system.

Dataset Information

Association Between SARS-CoV-2 Cycle Threshold Values and Clinical Outcomes in Patients With COVID-19: A Systematic Review and Meta-analysis.

Publications

Association Between SARS-CoV-2 Cycle Threshold Values and Clinical Outcomes in Patients With COVID-19: A Systematic Review and Meta-analysis.

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