Predicting recovery of ability to walk ten meters or more independently at eight weeks and six months after stroke

Background: Models predicting return to walking after stroke might allow accurate prognostication, and planning of rehabilitation. This study aimed to construct prognostic models to predict ability to walk 10m or more independently at 8weeks and 6months after stroke. Method: All participants (N=593) were enrolled in the “Dopamine Augmented Rehabilitation in Stroke” trial, and were unable to walk 10m or more independently at baseline. Imaging predictor variables (from the first available CT scan) included where relevant: infarct size and location; vascular territory affected; haematoma location and volume; presence of atrophy, white matter hypodensities, old stroke lesions, mass effect, or hydrocephalus. Demographic variables included age, gender, and Oxford Community Stroke Project syndrome. Clinical outcomes recorded at baseline, 8weeks, and 6months included: the Rivermead Mobility Index (RMI); the Montreal Cognitive Assessment (MoCA), General Health Questionnaire-12; presence of musculoskeletal pain. Using forward stepwise binary logistic regression, six models were constructed: models 1 and 2 (walking ability after ischaemic stroke); models 3 and 4 (walking ability after intracerebral haemorrhage); and models 5 and 6 (walking ability in the whole DARS sample). Models 1-4 utilised imaging, demographic, and clinical predictors; models 5 and 6 included demographic and clinical predictors only. Results: No imaging variables predicted outcome. Baseline RMI was most consistently predictive across all models. Baseline MoCA was also predictive, but with a smaller effect size than RMI. Only 68%-73% of patients were correctly classified by the models. The percentage of variance they explained was modest (20-30%). Discussion: This exploratory analysis utilised existing data, excluding predictors that might have explained additional variance. Within these limitations, this study suggests that initial level of mobility offers a more useful prediction of mobility at up to 6months than assessment of structural brain impairment on CT. Resume Francais Contexte: les modeles predisent que le retour a la marche apres un accident vasculaire cerebral pourraient permettre un pronostic precis et la planification de la readaptation. Cette etude visait a construire des modeles pronostiques pour predire la capacite des patients a marcher 10 metres ou plus independamment a 8 semaines et 6 mois apres un accident vasculaire cerebral. Methode: Tous les participants (N = 593) ont ete inscrits dans le proces "Dopamine Augmented Rehabilitation in Stroke", et ont ete incapables de marcher 10 metres independamment au depart. Les variables predictives d'imagerie (a partir de la premiere tomodensitometrie disponible) incluses etaient significatives, et, le cas echeant, la taille et l'emplacement de l'infarctus; Territoire vasculaire affecte; Emplacement et volume de l'hematome; Presence d'atrophie, hyperintensites de la matiere blanche, vieilles lesions d’accident vasculaire cerebral (AVC), effet de masse ou hydrocephalie. Les variables demographiques comprenaient l'âge, le sexe et le syndrome de Oxford Community Stroke Project. Les resultats cliniques enregistres a la ligne de base, 8 semaines et 6 mois comprises: Rivermead Mobility Index (RMI); Evaluation cognitive de Montreal (MoCA); Sante generale. Questionnaire-12; Presence de douleurs musculo-squelettiques. En utilisant la regression logistique binaire progressive par etapes, six modeles ont ete construits: modeles 1 et 2 (capacite de marche apres accident vasculaire ischemique); Modeles 3 et 4 (capacite de marche apres une hemorragie); Et les modeles 5 et 6 (capacite de marche dans l'ensemble de l'echantillon DARS). Les modeles 1-4 utilisaient des predicteurs d'imagerie, demographiques et cliniques; Les modeles 5 et 6 incluaient les predicteurs demographiques et cliniques seulement. Resultats: aucune variable d'imagerie n'a predit de resultat. Le RMI de reference etait la variable predictive la plus constante dans tous les modeles. Le MoCA de base etait egalement predictif, mais avec une taille d'effet plus petite que le RMI. Seulement 68% -73% des patients ont ete correctement classes par les modeles. Le pourcentage de variance qu'ils ont explique etait modeste (20 a 30%). Discussion: Cette analyse exploratoire a utilise les donnees existantes, a l'exclusion des predicteurs qui auraient explique une variance supplementaire. Dans le cadre de ces limites, cette etude suggere que le niveau initial de mobilite offre une prediction plus utile de la mobilite jusqu'a 6 mois que l'evaluation de l'insuffisance cerebrale structurelle sur la tomodensitometrie. Traduit par Dr Collette Isabel Stadler, Academic Clinical Fellow, University of Cambridge.