Analysis of prognostic risk factors and risk management measures for patients with ischemic stroke and bloodstream infection based on machine learning

Key Points

• Prognostic risk factors identified include pneumonia and hypoalbuminaemia, impacting patient outcomes.
• The predictive efficacy of the LASSO regression model demonstrates a strong ability to distinguish risk factors.
• Clinical utility is highlighted through the implementation of targeted risk management strategies using model variables.
• Understanding these factors is vital for enhancing care and outcomes for patients with ischemic stroke and bloodstream infections.