A Clinical Predictive Score to Predict Functional Outcomes After Intensive Rehabilitation Programs for Patients with Stroke: A Retrospective Cohort Study

Paveenrath Charussuriyong; Rachawan Suksathien

Authors

Paveenrath Charussuriyong Department of Rehabilitation Medicine, Maharat Nakhon Ratchasima Hospital, Nakhon Ratchasima
Rachawan Suksathien Department of Rehabilitation Medicine, Maharat Nakhon Ratchasima Hospital, Nakhon Ratchasima

Keywords:

activities of daily living, rehabilitation outcome, stroke, predictive score

Abstract

Objectives: To develop a clinical predictive score to predict functional outcomes of intensive rehabilitation programs for stroke patients

Study design: A retrospective, observational cohort study

Setting: The inpatient rehabilitation ward of the Maharat Nakhon Ratchasima Hospital

Subjects: Stroke patients aged ≥ 18 years who had undergone admission for intensive rehabilitation

Methods: The study reviewed the demographic data, associated impairment, clinical assessment, and Barthel index (BI) at admis-sion to and at discharge from the rehabilitation ward. The patient’s functional outcome was classified based on the BI at discharge. Predictive variables were identified using stepwise multivariable logistic regression. A predictive score was constructed and validated.

Results: Among 250 patients, 81 achieved a good rehabilitation outcome. Eight variables were predictive of outcome: age < 70 years, interval from onset to intensive rehabilitation admission, neglect syndrome, cognitive impairment, depression, muscle strength of the affected distal upper extremity and proximal lower extremity ≥ grade 3, and Functional Ambulation Categories (FAC). These variables were used to construct a predictive score, resulting in a model with an area under the curve (AUC) of 0.77 (95%CI: 0.71, 0.83). The total score range was from 0 to 33. The Youden index determined a cutoff of 19.5, categorizing patients into two groups: good (> 19.5) and poor rehabilitation outcomes (≤ 19.5). The positive likelihood ratio for good was 2.32 (95%CI: 1.85, 2.90), while for poor rehabilitation outcomes, it was 0.27 (95%CI: 0.17, 0.44). Internal validity confirmed the model’s good discrimination, calibration, and minimal overfitting.

Conclusions: Based on reliable and straightforward admission variables, the clinical predictive score presented in this study could help guide physicians in decision-making regarding selection of patients for admission to intensive rehabilitation programs.

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