Establishment and verification of a nomogram model for predicting the risk of post-stroke depression.

ABSTRACT:

Objective

The purpose of this study was to establish a nomogram predictive model of clinical risk factors for post-stroke depression (PSD).

Patients and methods

We used the data of 202 stroke patients collected from Xuanwu Hospital from October 2018 to September 2020 as training data to develop a predictive model. Nineteen clinical factors were selected to evaluate their risk. Minimum absolute contraction and selection operator (LASSO, least absolute shrinkage and selection operator) regression were used to select the best patient attributes, and seven predictive factors with predictive ability were selected, and then multi-factor logistic regression analysis was carried out to determine six predictive factors and establish a nomogram prediction model. The C-index, calibrati

SUBMITTER: Luo S 

PROVIDER: S-EPMC9899426 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature