Severe stroke patients are known to be associated with larger rehabilitation length of stay (LOS) but other factors besides severity may be contributing. We aim to identify LOS predictors within a population of mostly severe patients and analyze the impact of socioeconomic situation in functionality at admission. A retrospective observational cohort study was conducted including 172 inpatients admitted to a rehabilitation center between 2007 and 2019. Associations with LOS were examined among 30 potential predictor variables using bivariate correlations. Significantly correlated ( P < .002, Bonferroni adjustment) variables were entered into 9 different multiple linear regression models. No mild participants were included, 63.37% severe and 36.63% moderate. Most significant LOS determinants were: 1) total functional independence measure (FIM) ( P < .001) and hemiparesis ( P = .0108) (adjusted R 2 = 0.24), 2) cognitive FIM ( P = .002) and severity ( P = .001) (adjusted R 2 = 0.22), and 3) home accessibility ( P = .043) and hemiparesis ( P = 0.032) (adjusted R 2 = 0.19). Known LOS predictors (e.g., depression, ataxia) within the full stroke severities were not found significant in our dataset. Socioeconomic situation was found moderately correlated with total FIM (r = −0.32, P < .0001). When stratifying the patients’ socioeconomic situation into mild, important, and severe social risk, their respective median total FIM at admission were 61.5, 50, and 41, with significant differences between the mild and important group ( P < .001); also significant differences were found between mild and severe groups ( P < .001). A few of the variables identified in the literature as significant predictors of LOS within the full stroke population were also significant for our dataset (National Institutes of Health Stroke Scale, FIM, home accessibility) explaining less than 25% of the LOS variance. Most of the 30 analyzed known predictors were not significant (e.g., depression, age, recurrent stroke, ataxia, orientation, verbal communication, etc) suggesting that factors outside functional, socioeconomic, medical, and demographics not included in this study (e.g., rehabilitation sessions intensity) have important influences on LOS for severe patients. Patients at mild social risk obtained significantly higher total FIM at admission than patients at important and severe social risk. The importance of socioeconomic situation has been scarcely studied in the literature in relation to functionality at admission; our results suggest that it requires to be considered.

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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 χ 2 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.

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