ArticleScientific reports2023
Comparing the contribution of each clinical indicator in predictive models trained on 980 subacute stroke patients: a retrospective study.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A Pilot Study on the Short-Term Effects of an Electric Knee-Ankle-Foot Orthosis on Gait Performance and Physiological Cost Index in Patients With Hemiplegia: Influence of Initial Balance Ability Assessed by the Berg Balance Scale.BioMed research international · 2026Trial
- Motor Impairment Is the Key Determinant of the 1-Year Modified Rankin Scale Score in Intracerebral Haemorrhage.Cerebrovascular diseases (Basel, Switzerland) · 2026Article
- Explainable machine learning prediction of functional independence measure scores and gain in subacute stroke survivors.Journal of neuroengineering and rehabilitation · 2026Article
- Article
- Association between performance of basic movements at admission and socioenvironmental factors and returning home following inpatient stroke rehabilitation.Journal of physical therapy science · 2025Article
- Longitudinal Changes in Factors Associated with Walking Independence at Hospital Discharge in Patients with Stroke: A Retrospective Study.Journal of clinical medicine · 2024Article
- Logistic regression analysis and machine learning for predicting post-stroke gait independence: a retrospective study.Scientific reports · 2024Article
- Prognostic Value of Dysphagia for Activities of Daily Living Performance and Cognitive Level after Stroke.Progress in rehabilitation medicine · 2024Article
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Authors and funding
7 authors.
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Abstract
Post-stroke disability affects patients' lifestyles after discharge, and it is essential to predict functional recovery early in hospitalization to allow time for appropriate decisions. Previous studies reported important clinical indicators, but only a few clinical indicators were analyzed due to insufficient numbers of cases. Although review articles can exhaustively identify many prognostic factors, it remains impossible to compare the contribution of each predictor. This study aimed to determine which clinical indicators contribute more to predicting the functional independence measure (FIM) at discharge by comparing standardized coefficients. In this study, 980 participants were enrolled to build predictive models with 32 clinical indicators, including the stroke impairment assessment set (SIAS). Trunk function had the most significant standardized coefficient of 0.221. The predictive models also identified easy FIM sub-items, SIAS, and grip strength on the unaffected side as having positive standardized coefficients. As for the predictive accuracy of this model, R
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