Accuracy of prediction of walking for young stroke patients by use of the FIM.

Abstract

Clinical prediction of walking outcome after a stroke is essential for effective discharge planning. However, its accuracy has hardly been explored. This study took place in a regional unit admitting patients with complex neurological disabilities for specialist inpatient rehabilitation. The aim was to compare predicted outcome (goal score) with achieved outcome (discharge score) on the seven-point locomotion subscale of the Functional Independence Measure (FIM), to evaluate its precision and identify factors influencing accuracy. Admission, goal and discharge scores were analysed retrospectively for 141 subjects (90 M; 51 F) admitted consecutively to the Unit with median age 54 years (range 15-68 years) with median length of stay 13.6 weeks (range 3-35 weeks). Ninety subjects (64%) gained from two to six points; 50 subjects (35%) gained one point or showed no change. One patient deteriorated by two points. Excluding patients admitted with the highest score (FIM level 7), the overall level of agreement between predicted and discharge scores was moderate (weighted kappa 0.47). Prediction was accurate to +/- 1 point in 113 subjects (80%). Overprediction by > or = 2 points occurred in 16 subjects (11%) and underprediction by > or = 2 points in 12 subjects (9%). Analysis of the most-disabled cohort, admitted with FIM levels 1 or 2 scores, revealed a higher sensitivity for predicting 'independence' (FIM levels 5-7) (78%) than 'dependence' (FIM levels 1-4) (65%). Accuracy was not affected by age, gender or side of stroke. Inaccurate predictions were associated with lower admission FIM level scores (p = -0.26; p = 0.002) and a greater length of stay (p = 0.36; p < 0.001). Subjects with quadriplegia were more likely to have inaccurate outcome predictions made than those with hemiplegia (p = 0.025) and those with neglect were more likely to have inaccurate outcome predictions made than those without neglect (p = 0.017). Further investigation into clinical prediction and the variables which confound accuracy is needed for effective planning.