Abstract 4367239: Combination of High-Sensitive Troponin I and NT-proBNP for Mortality Risk Stratification in Hospitalized COVID-19 Across Pandemic Waves: Pooled Analysis from COVID-MI Registry Cohort-1 and Cohort-2
Background: Hospitalized Coronavirus disease 2019 (COVID-19) patients continue to experience high mortality, and while either high-sensitive troponin I (HsTnI) or N-terminal pro-B-type natriuretic peptide (NT-proBNP) alone can stratify mortality risk, it is uncertain whether a combined approach retains prognostic power across evolving pandemic waves. We established two registries that enrolled consecutive COVID-19 patients admitted between July 2020 and September 2021 (Cohort-1, 917 patients) and between October 2021 and October 2022 (Cohort-2, 1,102 patients). Hypothesis: Combining HsTnI and NT-proBNP at prespecified low and high cutoff values predicts all-cause death more accurately than either biomarker alone, irrespective of pandemic waves. Aims: We sought to assess the performance of the dual-biomarker risk model using prespecified cutoff values in an initial cohort (Cohort-1) and in a second cohort (Cohort-2). Method: Additional measurements using blood serum banks were performed on blood tests at admission, and both HsTnI and NT-proBNP were available in 921 patients. (Cohort-1: 530 patients, and Cohort-2: 391 patients). Within each cohort, we divided patients into four groups using low-cutoff values of HsTnI at 5 ng/L and NT-proBNP at 125 pg/mL or high-cutoff values at the 99th upper reference limit (URL) for HsTnI and 900 pg/mL for NT-proBNP. The primary outcome measure was all-cause death during follow-up. Results: The median follow-up period was 29 days. In low-cutoff strata, the double-positive stratum (LS3: HsTnI ≥5 ng/L and NT-proBNP >125 pg/mL) showed the highest incidence of mortality relative to the other groups. In the high-cutoff strata, the double-negative stratum (HS0: HsTnI Conclusions: Using a dual-biomarker strategy that combines HsTnI and NT-proBNP, a double-negative result at prespecified cutoff values reliably identifies low-risk hospitalized COVID-19 patients across different pandemic waves. These findings may help guide early triage and management decisions on patients with COVID-19.