Introduction: Predicting upper limb capacity recovery is important to set treatment goals, select therapies and plan discharge. We introduce a prediction model of the patient-specific profile of upper limb capacity recovery up to 6 months poststroke by incorporating all serially assessed clinical information from patients. Methods: Model input was recovery profile of 450 patients with a first-ever ischaemic hemispheric stroke measured using the Action Research Arm Test (ARAT). Subjects received at least three assessment sessions, starting within the first week until 6 months poststroke. We developed mixed-effects models that are able to deal with one or multiple measurements per subject, measured at non-fixed time points. The prediction accuracy of the different models was established by a fivefold cross-validation procedure. Results: A model with only ARAT time course, finger extension and shoulder abduction performed as good as models with more covariates. For the final model, cross-validation prediction errors at 6 months poststroke decreased as the number of measurements per subject increased, from a median error of 8.4 points on the ARAT (Q1-Q3:1.7-28.1) when one measurement early poststroke was used, to 2.3 (Q1-Q3:1-7.2) for seven measurements. An online version of the recovery model was developed that can be linked to data acquisition environments. Conclusion: Our innovative dynamic model can predict real-Time, patient-specific upper limb capacity recovery profiles up to 6 months poststroke. The model can use all available serially assessed data in a flexible way, creating a prediction at any desired moment poststroke, stand-Alone or linked with an electronic health record system.

biomarkers, biostatistics, models, outcome measure, prognosis, stroke, stroke unit, upper extremity
dx.doi.org/10.1136/jnnp-2020-324637, hdl.handle.net/1765/134289
Journal of Neurology, Neurosurgery and Psychiatry: an international peer-reviewed journal for health professionals and researchers in all areas of neurology and neurosurgery
Department of Orthopaedics

Selles, R.W, Andrinopoulou, E-R, Nijland, R.H.M, van der Vliet, R, Slaman, J, van Wegen, E.E.H, … Kwakkel, G. (2020). Computerised patient-specific prediction of the recovery profile of upper limb capacity within stroke services: The next step. Journal of Neurology, Neurosurgery and Psychiatry: an international peer-reviewed journal for health professionals and researchers in all areas of neurology and neurosurgery. doi:10.1136/jnnp-2020-324637