Predictive models for independence after stroke rehabilitation: Maugeri external validation and development of a new model

Abstract

BACKGROUND: Many efforts have been devoted to identify predictors of functional outcomes after stroke rehabilitation. Though extensively recommended, there are very few external validation studies. OBJECTIVE: To externally validate two predictive models (Maugeri model 1 and model 2) and to develop a new model (model 3) that estimate the probability of achieving improvement in physical functioning (primary outcome) and a level of independence requiring no more than supervision (secondary outcome) after stroke rehabilitation. METHODS: We used multivariable logistic regression analysis for validation and development. Main outcome measures were: Functional Independence Measure (FIM) (primary outcome), Functional Independence Staging (FIS) (secondary outcome) and Minimal Clinically Important Difference (MCID). RESULTS: Patients with stroke admitted to a rehabilitation center from 2006 to 2019 were retrospectively studied (N = 710). Validation of Maugeri models confirmed very good discrimination: for model 1 AUC = 0.873 (0.833–0.915) and model 2 AUC = 0.803 (0.749–0.857). The Hosmer–Lemeshow χ2 was 6.07(p = 0.63) and 8.91(p = 0.34) respectively. Model 3 yielded an AUC = 0.894 (0.857–0.929) (primary outcome) and an AUC = 0.769 (0.714–0.825) (MCID). CONCLUSIONS: Discriminative power of both Maugeri models was externally confirmed (in a 20 years younger population) and a new model (incorporating aphasia) was developed outperforming Maugeri models in primary outcome and MCID.