Diagnostic SARS-CoV-2 Cycle Threshold Value Predicts Disease Severity, Survival, and Six-Month Sequelae in COVID-19 Symptomatic Patients
To date, there is no severe acute respiratory syndrome coronavirus 2-(SARS-CoV-2)-specific prognostic biomarker available. We assessed whether SARS-CoV-2 cycle threshold (Ct) value at diagnosis could predict novel CoronaVirus Disease 2019 (COVID-19) severity, clinical manifestations, and six-month s...
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Veröffentlicht in: | Viruses 2021-02, Vol.13 (2), p.281 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | To date, there is no severe acute respiratory syndrome coronavirus 2-(SARS-CoV-2)-specific prognostic biomarker available. We assessed whether SARS-CoV-2 cycle threshold (Ct) value at diagnosis could predict novel CoronaVirus Disease 2019 (COVID-19) severity, clinical manifestations, and six-month sequelae. Hospitalized and outpatient cases were randomly sampled from the diagnoses of March 2020 and data collected at 6 months by interview and from the regional database for COVID-19 emergency. Patients were stratified according to their RNA-dependent-RNA-polymerase Ct in the nasopharyngeal swab at diagnosis as follows: Group A ≤ 20.0, 20.0 < group B ≤ 28.0, and Group C > 28.0. Disease severity was classified according to a composite scale evaluating hospital admission, worst oxygen support required, and survival. Two hundred patients were included, 27.5% in Groups A and B both, 45.0% in Group C; 90% of patients were symptomatic and 63.7% were hospitalized. The median time from COVID-19 onset to swab collection was five days. Lethality, disease severity, type, and number of signs and symptoms, as well as six-month sequelae distributed inversely among the groups with respect to SARS-CoV-2 Ct. After controlling for confounding, SARS-CoV-2 Ct at diagnosis was still associated with COVID-19-related death (
= 0.023), disease severity (
= 0.023), number of signs and symptoms (
< 0.01), and presence of six-month sequelae (
< 0.01). Early quantification of SARS-CoV-2 may be a useful predictive marker to inform differential strategies of clinical management and resource allocation. |
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ISSN: | 1999-4915 1999-4915 |
DOI: | 10.3390/v13020281 |