Predicting models for arm impairment: External validation of the Scandinavian models and identification of new predictors in post-acute stroke settings

Article type: Research Article

Authors: García-Rudolph, Alejandro^{a; b; c; *} | Soriano, Ignasi^{a; b; c} | Becerra, Helard^d | Madai, Vince Istvan^{e; f; g} | Frey, Dietmar^e | Opisso, Eloy^{a; b; c} | Tormos, Josep María^{a; b; c} | Bernabeu, Montserrat^{a; b; c}

Affiliations: [a] Department of Research and Innovation, Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Barcelona, Spain | [b] Universitat Autònoma de Barcelona, Bellaterra (Cerdanyola del Vallès), Spain | [c] Fundació Institut d’Investigació en Ciències de la Salut Germans Trias i Pujol, Barcelona, Spain | [d] School of Computer Science, University College Dublin, Dublin, Ireland | [e] CLAIM Charité Lab for AI in Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany | [f] QUEST Center for Transforming Biomedical Research, Berlin Institute of Health (BIH), Berlin, Germany | [g] School of Computing and Digital Technology, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, Birmingham, UK

Correspondence: [*] Address for correspondence: Alejandro García-Rudolph, Department of Research and Innovation, Institut Guttmann – Hospital de Neurorehabilitació, Cami Can Ruti s/n 08916 – Badalona, Barcelona, Spain. E-mail: alejandropablogarcia@gmail.com. ORICD: 0000-0003-0853-8334.

Abstract: BACKGROUND:Post-stroke arm impairment at rehabilitation admission as predictor of discharge arm impairment was consistently reported as extremely useful. Several models for acute prediction exist (e.g. the Scandinavian), though lacking external validation and larger time-window admission assessments. OBJECTIVES:(1) use the 33 Fugl-Meyer Assessment-Upper Extremity (FMA-UE) individual items to predict total FMA-UE score at discharge of patients with ischemic stroke admitted to rehabilitation within 90 days post-injury, (2) use eight individual items (seven from the Scandinavian study plus the top predictor item from objective 1) to predict mild impairment (FMA-UE≥48) at discharge and (3) adjust the top three models from objective 2 with known confounders. METHODS:This was an observational study including 287 patients (from eight settings) admitted to rehabilitation (2009-2020). We applied regression models to candidate predictors, reporting adjusted R2, odds ratios and ROC-AUC using 10-fold cross-validation. RESULTS:We achieved good predictive power for the eight item-level models (AUC: 0.70-0.82) and for the three adjusted models (AUC: 0.85-0.88). We identified finger mass flexion as new item-level top predictor (AUC:0.88) and time to admission (OR = 0.9(0.9;1.0)) as only common significant confounder. CONCLUSION:Scandinavian item-level predictors are valid in a different context, finger mass flexion outperformed known predictors, days-to-admission predict discharge mild arm impairment.

Keywords: Arm recovery, arm functioning, prognostic models, prediction, post-acute

DOI: 10.3233/NRE-220233

Journal: NeuroRehabilitation, vol. 53, no. 1, pp. 91-104, 2023