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Time‑dependent ROC Curve Analysis to Determine the Predictive Capacity of Seven Clinical Scales for Mortality in Patients with COVID‑19: Study of a Hospital Cohort with Very High Mortality

Biomedical reports(2024)

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Abstract
Clinical data from hospital admissions are typically utilized to determine the prognostic capacity of Coronavirus disease 2019 (COVID-19) indices. However, as disease status and severity markers evolve over time, time-dependent receiver operating characteristic (ROC) curve analysis becomes more appropriate. The present analysis assessed predictive power for death at various time points throughout patient hospitalization. In a cohort study involving 515 hospitalized patients (General Hospital Number 1 of Mexican Social Security Institute, Colima, Mexico from February 2021 to December 2022) with COVID-19, seven severity indices [Pneumonia Severity Index (PSI) PaO2/FiO2 arterial oxygen pressure/fraction of inspired oxygen (Kirby index), the Critical Illness Risk Score (COVID-GRAM), the National Early Warning Score 2 (NEWS-2), the quick Sequential Organ Failure Assessment score (qSOFA), the Fibrosis-4 index (FIB-4) and the Viral Pneumonia Mortality Score (MuLBSTA were evaluated using time-dependent ROC curves. Clinical data were collected at admission and at 2, 4, 6 and 8 days into hospitalization. The study calculated the area under the curve (AUC), sensitivity, specificity, and predictive values for each index at these time points. Mortality was 43.9%. Throughout all time points, NEWS-2 demonstrated the highest predictive power for mortality, as indicated by its AUC values. PSI and COVID-GRAM followed, with predictive power increasing as hospitalization duration progressed. Additionally, NEWS-2 exhibited the highest sensitivity (>96% in all periods) but showed low specificity, which increased from 22.9% at admission to 58.1% by day 8. PSI displayed good predictive capacity from admission to day 6 and excellent predictive power at day 8 and its sensitivity remained >80% throughout all periods, with moderate specificity (70.6-77.3%). COVID-GRAM demonstrated good predictive capacity across all periods, with high sensitivity (84.2-87.3%) but low-to-moderate specificity (61.5-67.6%). The qSOFA index initially had poor predictive power upon admission but improved after 4 days. FIB-4 had a statistically significant predictive capacity in all periods (P=0.001), but with limited clinical value (AUC, 0.639-0.698), and with low sensitivity and specificity. MuLBSTA and IKIRBY exhibited low predictive power at admission and no power after 6 days. In conclusion, in COVID-19 patients with high mortality rates, NEWS-2 and PSI consistently exhibited predictive power for death during hospital stay, with PSI demonstrating the best balance between sensitivity and specificity.
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Key words
COVID-19,severity of illness index,hospital mortality,ROC curve,sensitivity,specificity
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