Development of a Prognostic Prediction Score for Functional Outcomes in Ischemic Stroke Patients for Home Care Planning
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Abstract
Background: Ischemic stroke is a leading cause of disability in Thailand. Effective homecare planning is crucial for improving outcomes. This study aimed to develop a prognostic model to predict functional outcomes in ischemic stroke patients using pre-discharge data, with outcomes assessed by the modified Rankin Scale (mRS) at six months post-discharge.
Design: Bidirectional Observational Cohort Study
Methods: A total of 548 ischemic stroke patients from Naresuan University Hospital (January 2019 - September 2023) were studied. Logistic regression was used to identify relevant predictors and develop a scoring model. Model accuracy was assessed using AuROC and calibration plots, with internal validation performed via bootstrapping.
Results: The scoring model included five predictors: initial mRS, atrial fibrillation, hospital stay longer than four days, pre-discharge NIHSS, and pre-discharge mRS. The model achieved an AuROC of 0.88 and demonstrated good calibration. Internal validation confirmed the model’s robustness. A cut-off score > 4, which demonstrated good performance, was identified as appropriate for identifying high-risk patients.
Conclusions: This prognostic model, based on pre-discharge data, provides valuable guidance for healthcare professionals in primary care, supporting home care planning for ischemic stroke patients.
Keywords: prognosis, ischemic stroke, functional outcome, home care planning
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