The Potential of Artificial Intelligence in Predicting Post-Stroke Rehabilitation Outcomes: Statistical Analysis Considering Rivermead Motor Assessment and Activities of Daily Living Indicators and Selected Demographic Variables DOI Creative Commons
Małgorzata Kuźnar, Augustyn Lorenc

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11806 - 11806

Published: Dec. 17, 2024

Strokes are currently the third most common cause of death worldwide and leading disability in people over 50 years age. The functioning post-stroke patients depends primarily on well-conducted rehabilitation, both stationary conditions at home. aim this study was to evaluate functional outcomes after ischemic stroke who underwent home rehabilitation. RMA (Rivermead Motor Assessment) ADL (activities daily living) scales were used for evaluation. A total 20 a 4-week rehabilitation program Cracow. In studied group, showed improvement period. Predictive models created (Net1, Net2, Net3) using artificial intelligence algorithms, including regression classification methods. analysis results indicate that best predicting indicators. For prediction accuracy indicator 94.4%, which is significantly higher compared other RMA1-3 indicators achieved relatively low rates 38.9–44.4%. contrast, Net3, high accuracy, achieving 89.1–91.3% correct results. conclusions suggest combination Net2 Net3 can contribute optimizing process, allowing therapy be tailored individual needs patients. research proves it possible predict effect by AI. implementation such solutions increase effectiveness particularly through personalization dynamic monitoring patient progress.

Language: Английский

Bidirectional relationship between depression and activities of daily living and longitudinal mediation of cognitive function in patients with Parkinson’s disease DOI Creative Commons
Yue Xu, Durong Chen,

Meiqi Dong

et al.

Frontiers in Aging Neuroscience, Journal Year: 2025, Volume and Issue: 17

Published: Feb. 12, 2025

Objective To investigate the bidirectional relationship between depression and activities of daily living (ADL) in Parkinson’s disease (PD) patients explore mediating role cognitive function over time. Methods Data from 892 PD Progression Markers Initiative (PPMI) database were included this study, depression, function, ADL measured using Geriatric Depression Scale (GDS-15), Montreal Cognitive Assessment (MoCA), Unified Disease Rating Scale, Part II (UPDRS II) respectively. The cross-lagged panel model (CLPM) was employed to analyze reciprocal ADL. Then, we explored with PD, mediation effect test carried out a bias-corrected nonparametric percentile bootstrap approach. Results predicted their subsequent ( β = 0.079, p < 0.01), also 0.069, 0.05), In addition, Bootstrap analysis showed that played significant prediction 0.006, 0.074, 95%CI 0.001 ~ 0.014), 0.067, 0.013). Conclusion There is PD. Furthermore, found mediates exists Interventions aimed at enhancing could potentially lessen vicious cycle thus improving patient quality life (QOL).

Language: Английский

Citations

0
Interaction effects of sleep duration and activities of daily living on depressive symptoms among Chinese middle-aged and older adult individuals: evidence from the CHARLS DOI Creative Commons

Tianmeng Wang,

Wenjin Han, Caihua Wang

et al.

Frontiers in Public Health, Journal Year: 2025, Volume and Issue: 13

Published: March 12, 2025

Objectives Evidence on the combined effect of sleep duration and activities daily living (ADL) depressive symptoms is scarce. This study aimed to explore interaction effects between ADL limitations among Chinese individuals aged ≥45 years. Methods Data were extracted from China Health Retirement Longitudinal Study (CHARLS) wave 2020. Sleep was self-reported. The Center for Epidemiological Studies Depression Scale a 12-item scale employed estimate limitations, respectively. Logistic regression analysis conducted examine symptoms. Results found that short (OR = 1.69, 95% CI: 1.57–1.83), long 0.87, 0.79–0.95), [basic (BADL), OR 1.82, 1.66–2.01; instrumental (IADL), 1.88, 1.71–2.07] associated with Furthermore, synergistic risk identified IADL (RERI 1.08, 0.57–1.59) or BADL 1.13, 0.60–1.65). Conversely, antagonistic observed 0.88, 0.39–1.38) 0.76, 0.25–1.27) Conclusion revealed significant interactions symptoms, suggesting enhancing ADL’s function ensuring adequate could effectively prevent

Language: Английский

Citations

0
The Potential of Artificial Intelligence in Predicting Post-Stroke Rehabilitation Outcomes: Statistical Analysis Considering Rivermead Motor Assessment and Activities of Daily Living Indicators and Selected Demographic Variables DOI Creative Commons
Małgorzata Kuźnar, Augustyn Lorenc

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11806 - 11806

Published: Dec. 17, 2024

Strokes are currently the third most common cause of death worldwide and leading disability in people over 50 years age. The functioning post-stroke patients depends primarily on well-conducted rehabilitation, both stationary conditions at home. aim this study was to evaluate functional outcomes after ischemic stroke who underwent home rehabilitation. RMA (Rivermead Motor Assessment) ADL (activities daily living) scales were used for evaluation. A total 20 a 4-week rehabilitation program Cracow. In studied group, showed improvement period. Predictive models created (Net1, Net2, Net3) using artificial intelligence algorithms, including regression classification methods. analysis results indicate that best predicting indicators. For prediction accuracy indicator 94.4%, which is significantly higher compared other RMA1-3 indicators achieved relatively low rates 38.9–44.4%. contrast, Net3, high accuracy, achieving 89.1–91.3% correct results. conclusions suggest combination Net2 Net3 can contribute optimizing process, allowing therapy be tailored individual needs patients. research proves it possible predict effect by AI. implementation such solutions increase effectiveness particularly through personalization dynamic monitoring patient progress.

Language: Английский

Citations

1