External validation and extension of the Early Prediction of Functional Outcome after Stroke (EPOS) prediction model for upper limb outcome 3 months after stroke

Abstract

Objective The ‘Early Prediction of Functional Outcome after Stroke’ (EPOS) model was developed to predict the presence of at least some upper limb capacity (Action Research Am Test [ARAT] ≥10/57) at 6 months based on assessments on days 2, 5 and 9 after stroke. External validation of the model is the next step towards clinical implementation. The objective here is to externally validate the EPOS model for upper limb outcome 3 months poststroke in Switzerland and extend the model using an ARAT cut-off at 32 points. Methods Data from two prospective longitudinal cohort studies including first-ever stroke patients admitted to a Swiss stroke center were analyzed. The presence of finger extension and shoulder abduction was measured on days 1 and 8 poststroke in Cohort 1, and on days 3 and 9 in Cohort 2. Upper limb capacity was measured 3 months poststroke. Discrimination (area under the curve; AUC) and calibration obtained with the model were determined. Results In Cohort 1 (N = 39, median age 74 years), the AUC on day 1 was 0.78 (95%CI 0.61, 0.95) and 0.96 (95%CI 0.90, 1.00) on day 8, using the model of day 5. In Cohort 2 (N = 85, median age 69 years), the AUC was 0.96 (95%CI 0.93, 0.99) on day 3 and 0.89 (95% CI 0.80, 0.98) on day 9. Applying a 32-point ARAT cut-off resulted in an AUC ranging from 0.82 (95%CI 0.68, 0.95; Cohort 1, day 1) to 0.95 (95%CI 0.87, 1.00; Cohort 1, day 8). Conclusions The EPOS model was successfully validated in first-ever stroke patients with mild-to-moderate neurological impairments, who were independent before their stroke. Now, its impact on clinical practice should be investigated in this population. Testing the model’s performance in severe (recurrent) strokes and stratification of patients using the ARAT 32-point cut-off is required to enhance the model’s generalizability and potential clinical impact.

Exoskeleton-assisted training to enhance lower limb motor recovery in subacute stroke: does timing matter? A pilot randomized trial

“…Randomization was blocked (2-by-2 ratio) and stratified according to the prognosis for achieving walking independence (i.e., favorable FAC ≥4 or poor FAC <4). Following the validated EPOS (Early Prognosis of functional Outcome after Stroke) model (Veerbeek et al, 2011(Veerbeek et al, , 2022, a favorable prognosis was defined as having sitting balance (i.e., Trunk Control Test sitting item >25) and leg strength (i.e., MI-LE ≥25). A poor prognosis was assigned if either of the determinants were more impaired.…”

Early prediction of upper limb functioning after stroke using clinical bedside assessments: a prospective longitudinal study

“…Recently, a prediction algorithm only including clinical bedside assessment reported an overall accuracy of 61% at predicting upper limb activity capacity at 3 months post stroke, although the sensitivity and specificity varied across the four outcome categories 17 . An external validation of a prediction model for upper limb activity capacity at six months post stroke, discriminating poor outcome (Action Research Arm Test < 10) and using shoulder abduction and finger extension as clinical predictor variables, showed high sensitivity (> 0.80) but lower specificity (0.40–0.70) 18 . For discrimination of a higher outcome level (Action Research Arm Test > 32), likewise, the sensitivity was high (> 0.92) but specificity was lower (0.28–0.60) 18 .…”

“…An external validation of a prediction model for upper limb activity capacity at six months post stroke, discriminating poor outcome (Action Research Arm Test < 10) and using shoulder abduction and finger extension as clinical predictor variables, showed high sensitivity (> 0.80) but lower specificity (0.40–0.70) 18 . For discrimination of a higher outcome level (Action Research Arm Test > 32), likewise, the sensitivity was high (> 0.92) but specificity was lower (0.28–0.60) 18 . These studies confirm that prediction models only using clinical assessments can provide clinically useful information, perform better than a chance alone and could therefore be considered as alternatives for more complex models 17 .…”

External Validation of a Dynamic Prediction Model for Upper Limb Function After Stroke

“…A simple bedside test based on shoulder abduction and finger extension (FE) 72 h, 5, and 9 days after stroke is the Early Prediction of Functional Outcome after Stroke (EPOS model), 7 which was recently externally validated. 8 While the EPOS model performed well in discriminating patients with no and some dexterity 3 and 6 months after stroke, it is still too coarse for clinical application because the outcome categories are too broad to be meaningful at an individual level in the clinical setting.…”

“…This model adds the substantial advantage of time-independent measurements, that is, not dependent on specific time points after stroke as suggested in other models. 8 , 15 In clinical routine, patients may not always be available for assessments on specific days because of other examinations and treatments. An online prediction visualization is available, including 68% and 98% prediction intervals reflecting prediction uncertainty.…”