Association Between SARS-CoV-2 Cycle Threshold Values at Hospital Admission and Clinical Outcomes in COVID-19 Patients: A Retrospective Cohort Study.
DOI:
https://doi.org/10.63682/jns.v13i1.10123Keywords:
SARS-CoV-2, COVID-19, RT-qPCR, Cycle Threshold, Prognosis, Research Methodology, Symptom Onset, Confounding FactorsAbstract
Background: Cycle Threshold (Ct) values from SARS-CoV-2 RT-qPCR tests have been widely investigated as prognostic markers. However, the interpretation of Ct values is fundamentally dependent on the time of sampling relative to symptom onset a low value may indicate normal early replication or, conversely, a failure of viral clearance later in the disease course. Many studies fail to account for this critical confounder.
Objective: Using a real-world cohort, we demonstrate how the absence of symptom onset data renders prognostic analysis of Ct values uninterpretable and provide a framework for mandatory reporting.
Methods: We conducted a retrospective analysis of 455 hospitalized COVID-19 patients (04.08.2020–11.01.2021) with admission RT-qPCR results (RdRp and N gene targets). Symptom onset data was unavailable. We performed standard prognostic analyses: Ct values were correlated with clinical outcomes, inflammatory markers (IL-6, D-dimer, CRP), and organ dysfunction. Univariate analysis, ROC (Receiver Operating Characteristic) curve analysis (for mortality), and multivariate regression were conducted as if symptom onset were unknown simulating a common methodological flaw.
Results: In this cohort (61.8% male, mortality 10.2%), lower Ct values (indicating higher viral RNA) showed statistically significant inverse correlations with key severity markers: IL-6 (r = -0.239, p<0.001), creatinine (r = -0.235, p<0.001), and need for oxygen (p<0.001). ROC analysis for mortality yielded an AUC (Area Under the Curve) of 0.746 with an optimal Ct cut-off value 24.5. A multivariate model identified IL-6, creatinine, and SpO2 as significant correlates of Ct but explained only 14.2% of variance (R²=0.142), suggesting missing critical explanatory variables.
Conclusion: This study replicates common analytical approaches and yields seemingly significant associations between Ct values and disease severity. However, in the definitive absence of symptom onset data, the key to contextualizing viral load and these results are clinically uninterpretable and potentially misleading. We propose that any study investigating Ct values as a prognostic biomarker must explicitly report and adjust for time since symptom onset; failure to do so constitutes a fundamental methodological error. Our findings serve as a critical case study for standardizing future research
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