CareLit Fachartikel
Predicting Fall Rate in Neurorehabilitation: Combining Physical and Cognitive Parameters
Winter, R.; Maguire, C.; Jansen, B.; Swinnen, E. · physioscience · 2025 · Heft S 03 · S. 1 bis 1
Dokument
569808
CareLit-ID
Jahr
2025
Publikation
PDF
nein
Metadaten
DOI
ja
zitierfähig
Bibliografische Angaben
Zusammenfassung
Background Falls pose a significant health challenge in neurological populations. In Switzerland, approximately 286. 000 people fall annually, with up to 50% of neurological inpatients experiencing falls. These incidents lead to increased morbidity, healthcare costs, and psychological consequences. Current fall-risk assessments have limitations in discriminative capabilities, often underestimating the impact of psychological and cognitive factors, and are frequently restricted to binary outcomes (fall/no fall). Additionally, these tools are predominantly developed for elderly cohorts, which may not generalize to…
Schlagworte
Sturzrisiko
Neurorehabilitation
kognitive Faktoren
physische Faktoren
Patienten
Fallprävalenz
Risikofaktoren
maschinelles Lernen
klinische Daten
geriatrische Population
Falls
Neurologic Disorders
Rehabilitation
Risk Assessment
Cognitive Dysfunction
Machine Learning
