Dataset Information

Lack of correlation between the SARS-CoV-2 cycle threshold (C_t ) value and clinical outcomes in patients with COVID-19.

ABSTRACT:

Problem

The utility of the polymerase chain reaction (PCR) cycle threshold (C_t ) values in the management of patients with coronavirus disease 2019 (COVID-19) remains controversial.

Methods

We assessed the correlation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) C_t values in nasopharyngeal swab samples with the oxygen requirements at the time of sample collection. Specimens were tested with the Simplexa PCR platform, which targets the SARS-CoV-2 ORF1ab and S genes.

Results

We identified 23 COVID-19 patients with 49 C_t values available. While C_t values from ORF1ab and S genes were highly correlated for a given specimen, there was no correlation between C_t values for any of these target genes and the oxygen requirements of the patient at the time of sample collection. We found no differences in the initial nor the nadir C_t values between survivors and non-survivors or mild/moderate versus severe/critical illness at the maximum point of illness.

Conclusion

SARS-CoV-2 C_t values have limited value in the management of COVID-19.

SUBMITTER: Camargo JF

PROVIDER: S-EPMC8427039 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Publications

Lack of correlation between the SARS-CoV-2 cycle threshold (C<sub>t</sub> ) value and clinical outcomes in patients with COVID-19.

Camargo Jose F JF Lin Rick Y RY Komanduri Krishna V KV

Journal of medical virology 20210706 10

<h4>Problem</h4>The utility of the polymerase chain reaction (PCR) cycle threshold (C<sub>t</sub> ) values in the management of patients with coronavirus disease 2019 (COVID-19) remains controversial.<h4>Methods</h4>We assessed the correlation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) C<sub>t</sub> values in nasopharyngeal swab samples with the oxygen requirements at the time of sample collection. Specimens were tested with the Simplexa PCR platform, which targets the SARS- ...[more]

PMID: 34196409

Similar Datasets

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.

Project description:BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cycle threshold (Ct) has been suggested as an approximate measure of initial viral burden. The utility of cycle threshold, at admission, as a predictor of disease severity has not been thoroughly investigated.Methods and findingsWe conducted a retrospective study of SARS-CoV-2 positive, hospitalized patients from 3/26/2020 to 8/5/2020 who had SARS-CoV-2 Ct data within 48 hours of admission (n = 1044). Only patients with complete survival data, discharged (n = 774) or died in hospital (n = 270), were included in our analysis. Laboratory, demographic, and clinical data were extracted from electronic medical records. Multivariable logistic regression was applied to examine the relationship of patient mortality with Ct values while adjusting for established risk factors. Ct was analyzed as continuous variable and subdivided into quartiles to better illustrate its relationship with outcome. Cumulative incidence curves were created to assess whether there was a survival difference in the setting of the competing risks of death versus patient discharge. Mean Ct at admission was higher for survivors (28.6, SD = 5.8) compared to non-survivors (24.8, SD = 6.0, P<0.001). In-hospital mortality significantly differed (p<0.05) by Ct quartile. After adjusting for age, gender, BMI, hypertension and diabetes, increased cycle threshold was associated with decreased odds of in-hospital mortality (0.91, CI 0.89-0.94, p<0.001). Compared to the 4th Quartile, patients with Ct values in the 1st Quartile (Ct <22.9) and 2nd Quartile (Ct 23.0-27.3) had an adjusted odds ratio of in-hospital mortality of 3.8 and 2.6 respectively (p<0.001). The discriminative ability of Ct to predict inpatient mortality was found to be limited, possessing an area under the curve (AUC) of 0.68 (CI 0.63-0.71).ConclusionSARS-CoV-2 Ct was found to be an independent predictor of patient mortality. However, further study is needed on how to best clinically utilize such information given the result variation due to specimen quality, phase of disease, and the limited discriminative ability of the test.

Dataset Information

Lack of correlation between the SARS-CoV-2 cycle threshold (C_t ) value and clinical outcomes in patients with COVID-19.

Problem

Methods

Results

Conclusion

Publications

Lack of correlation between the SARS-CoV-2 cycle threshold (C<sub>t</sub> ) value and clinical outcomes in patients with COVID-19.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Lack of correlation between the SARS-CoV-2 cycle threshold (Ct ) value and clinical outcomes in patients with COVID-19.

Problem

Methods

Results

Conclusion

Publications

Lack of correlation between the SARS-CoV-2 cycle threshold (C<sub>t</sub> ) value and clinical outcomes in patients with COVID-19.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Lack of correlation between the SARS-CoV-2 cycle threshold (C_t ) value and clinical outcomes in patients with COVID-19.