Predicting COVID-19 prognosis in hospitalized patients based on early status

mBio. 2023 Oct 31;14(5):e0150823. doi: 10.1128/mbio.01508-23. Epub 2023 Sep 8.

Abstract

COVID-19 remains the fourth leading cause of death in the United States. Predicting COVID-19 patient prognosis is essential to help efficiently allocate resources, including ventilators and intensive care unit beds, particularly when hospital systems are strained. Our PLABAC and PRABLE models are unique because they accurately assess a COVID-19 patient's risk of death from only age and five commonly ordered laboratory tests. This simple design is important because it allows these models to be used by clinicians to rapidly assess a patient's risk of decompensation and serve as a real-time aid when discussing difficult, life-altering decisions for patients. Our models have also shown generalizability to external populations across the United States. In short, these models are practical, efficient tools to assess and communicate COVID-19 prognosis.

Keywords: ICU; SARS-CoV-2 infection; biomarkers; coagulation; coagulopathy; hospital medicine; machine learning; pneumonia; renal failure; viral infections.

MeSH terms

  • COVID-19* / diagnosis
  • Humans
  • Intensive Care Units
  • Prognosis
  • SARS-CoV-2
  • United States