Cognitive Status Predicts Return to Functional Independence After Minor Stroke: A Decision Tree Analysis

Area of Science:

• Neurology
• Rehabilitation Medicine
• Clinical Decision Support

Background:

• Minor stroke patients often face challenges resuming daily activities post-discharge.
• Predicting successful return to pre-stroke function is crucial for effective patient management.

Purpose of the Study:

• To develop and validate a decision tree model for identifying minor stroke patients likely to return to pre-stroke activities.
• To assess the role of cognitive function in post-stroke recovery and independence.

Main Methods:

• Classification and Regression Tree (CART) analysis was used on a construction cohort (n=105) from France.
• The developed decision tree was externally validated on an independent cohort (n=100) from Switzerland.
• Key predictors identified included Montreal Cognitive Assessment (MoCA), NIHSS score, age, and occupational status.

Main Results:

• The decision tree achieved 80% prediction accuracy in the construction cohort and 72% in the validation cohort.
• Cognitive assessment (MoCA) emerged as the primary factor in predicting favorable outcomes.
• 57% of patients in the construction cohort returned to their pre-stroke level of independence.

Conclusions:

• Cognitive function is a critical determinant of successful recovery and return to usual activities after minor stroke.
• The validated decision tree can assist clinicians in tailoring discharge planning and support for minor stroke survivors.
• This tool aids in identifying patients who may require additional interventions to optimize their functional recovery.