Outcome Stratified Analysis of Biomarker Trajectories for Patients With SARS-CoV-2 Infection
Click for External Resource*
Click to read full article*
*The link above may share a zip file (.zip) hosted on repository.netecweb.org. Zip files will download automatically.
Longitudinal trajectories of vital signs and biomarkers during admission remain poorly characterized for COVID-19 patients despite their potential to provide critical insights about disease progression. We studied 1884 patients with SARS-CoV2 infection from 3/4/2020-6/25/2020 within one Maryland hospital system and used a retrospective longitudinal framework with linear mixed-effects models to investigate relevant biomarker trajectories leading up to three critical outcomes: mechanical ventilation, discharge, and death. Trajectories of four vital signs (respiratory rate, SpO2/FiO2, pulse, and temperature) and four lab values (C-reactive protein (CRP), absolute lymphocyte count (ALC), estimated glomerular filtration rate (eGFR), and D-dimer) clearly distinguished the trajectories of COVID-19 patients. Prior to any ventilation, log-CRP, log-ALC, respiratory rate, and SpO2/FiO2 trajectories diverge approximately 8-10 days before discharge or death. Following ventilation, log-CRP, log-ALC, respiratory rate, SpO2/FiO2, and eGFR trajectories again diverge 10-20 days prior to death or discharge. Trajectories improved until discharge and remained unchanged or worsened until death. Our approach characterizes the distribution of biomarker trajectories leading up to competing outcomes of discharge versus death. Moving forward, this model can contribute to quantifying the joint probability of future biomarkers and outcomes provided clinical data up to a given moment.
Keywords: COVID-19; case-control design; linear mixed effects models; longitudinal data.