PulseTrendingJournal ClubResearchersJournalsExplore
Instagram
HomeTrendingJournal ClubExplore
Synapse
⌘+K
Synapse
May 29, 2026Risk Management and Healthcare PolicyOpen Access

Development of a Risk Prediction Model for Post-Stroke Functional Recovery Based on Clinical and Nursing Factors

View Full Paper
Ask AI
Bookmark
Share

Authors

RSRuilin SunZLZhaojun Liu

Discussion

Loading...

Member takes

Overview

Retrospective cohort study develops a model predicting recovery in stroke patients, indicating effective interventions.

Key Points

  • This research aims to create a model to predict functional recovery outcomes in stroke patients based on clinical and nursing factors.
  • Retrospective cohort study of 1340 stroke patients from a tertiary hospital.
  • Data collection included demographic, clinical, imaging, nursing, and psychosocial factors.
  • Developed a nomogram-based risk prediction model using multivariable logistic regression and outcome-stratified sampling.
  • Older age, prior stroke history, and greater neurological deficits significantly predicted unfavorable recovery.
  • Early mobilization within 48 hours and better social support reduced the risk of poor recovery.
  • The model showed strong discrimination and calibration, with favorable predictive performance in all analyzed groups.

Cite This Study

Sun et al. (2026) studied this question.

synapsesocial.com/papers/6a192cd5fab5b468c4415ad7https://doi.org/10.2147/rmhp.s609869
View Full Paper
Ask AI
Bookmark
Share