External validation of a machine learning-based web application for personalized testing of objective functioning using the five-repetition sit-to-stand test - Scorecard - MDSpire
Clinical Scorecard: Validation of a Machine Learning-Driven Web Tool for Customized Assessment of Objective Functioning via the Five-Repetition Sit-to-Stand Test
At a Glance
Category
Detail
Condition
Objective Functional Impairment (OFI)
Key Mechanisms
Machine learning model incorporating demographic variables to personalize assessment thresholds for the 5R-STS test.
Target Population
Healthy individuals without functional impairment.
Care Setting
Neurosurgical practice and research.
Key Highlights
5R-STS test time over 10.4 seconds indicates objective functional impairment.
Machine learning model improves classification accuracy by personalizing ULN based on demographics.
External validation conducted on a diverse cohort across multiple countries.
Guideline-Based Recommendations
Diagnosis
Use the 5R-STS test to assess functional impairment.
Management
Employ personalized machine learning models for accurate assessment.
Monitoring & Follow-up
Regularly validate models across different demographics and settings.
Risks
Generalized assessment may misclassify patients due to individual factors.
Patient & Prescribing Data
Healthy volunteers from various countries.
Utilization of a web application for automated assessment of 5R-STS test times.
Clinical Best Practices
Incorporate demographic data into functional assessments.
Ensure standardized testing protocols for the 5R-STS test.
by Kenneth Arockia, Massimo Bottini, Anita M. Klukowska, Victor Gabriel El-Hajj, Maria Gharios, Ali Buwaider, Carlo Serra, Luca Regli, Marc L. Schröder, Victor E. Staartjes
