A predictive model for respiratory distress in patients with COVID-19: a retrospective study.

ABSTRACT:

Background

Coronavirus disease 2019 (COVID-19), associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global public health crisis. We retrospectively evaluated 863 hospitalized patients with COVID-19 infection, designated IWCH-COVID-19.

Methods

We built a successful predictive model after investigating the risk factors to predict respiratory distress within 30 days of admission. These variables were analyzed using Kaplan-Meier and Cox proportional hazards (PHs) analyses. Hazard ratios (HRs) and performance of the final model were determined.

Results

Neutrophil count >6.3×10⁹/L, D-dimer level ≥1.00 mg/L, and temperature ≥37.3 °C at admission showed significant positive association with the outcome of respiratory distress

SUBMITTER: Zhang X 

PROVIDER: S-EPMC7791231 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature