Nomogram-based prediction model for survival of COVID-19 patients: A clinical study.

ABSTRACT: The study aim to construct an effective model for predicting the survival period of COVID-19 patients.

Methods

Clinical data of 386 COVID-19 patients were collected from December 2022 to January 2023. The patients were randomly divided into training and validation cohorts in a 7:3 ratio. LASSO regression and multivariate Cox regression analyses were used to identify prognostic factors, and a nomogram was constructed. Nomogram was evaluated using decision curve analysis, receiver operating characteristic curve, consistency index (c-index), and calibration curve.

Results

86 patients (22.3%) died. A new nomogram for predicting the survival was established based on age, resting oxygen saturation, Blood urea nitrogen (BUN), c-reactive protein-to-albumin ratio (CAR), and pneumonia

SUBMITTER: Xu J 

PROVIDER: S-EPMC10559916 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature