Journal of Clinical and Translational Science (Jan 2023)

Fibrosis-4 (FIB-4) index as a predictor for mechanical ventilation and 30-day mortality across COVID-19 variants

  • Priyanka Parajuli,
  • Roy Sabo,
  • Rasha Alsaadawi,
  • Amanda Robinson,
  • Evan French,
  • Richard K. Sterling

DOI
https://doi.org/10.1017/cts.2023.594
Journal volume & issue
Vol. 7

Abstract

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Abstract Background: The Fibrosis-4 (FIB-4) index, a simple index that includes age, liver enzymes, and platelet count has been studied as a tool to identify patients at a risk of requiring mechanical ventilation due to its high negative predictive value. It is unknown if FIB-4 remains useful to predict the severity of respiratory disease requiring mechanical ventilation amongst new Coronavirus disease 2019 (COVID-19) variants and whether a relationship also exists between FIB-4 and 30-day mortality. The main objective was to determine if FIB-4 can predict mechanical ventilation requirements and 30-day mortality from COVID-19 across variants including Alpha, Delta, and Omicron. Methods: This was a population-based, retrospective cohort analysis of 232,364 hospitalized patients in the National COVID-19 Cohort Collaborative between the age of 18–90 who tested positive for COVID-19 between April 27, 2020 and June 25, 2022. The primary outcome was association between FIB-4 and need for mechanical ventilation. Secondary measures included the association of FIB-4 with 30-day mortality. Results: A FIB-4 > 2.67 had 1.8 times higher odds of requiring mechanical ventilation across all variants of COVID-19 (OR 1.81; 95% CI: [1.76, 1.86]). The area under the ROC curve showed high diagnostic accuracy with values ranging between 0.79 (Omicron wave) and 0.97 (delta wave). Increased FIB-4 was associated with 30-day mortality across the variates. Conclusion: The FIB-4 was consistently associated with both increased utilization of mechanical ventilation and 30-day mortality among COVID-19 patients across all waves in both adjusted and unadjusted models. This provides a simple tool for risk-stratification for front-line health care professionals.

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