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Background and aims Clinical predictive models for stroke recovery could offer the opportunity of targeted early intervention and more specific information for patients and carers. In this study, we developed and validated a patient-specific prognostic model for monitoring recovery after stroke and assessed its clinical utility. Methods Four hundred and ninety-five patients from the population-based South London Stroke Register were included in a substudy between 2002 and 2004. Activities of daily living were assessed using Barthel Index) at one, two, three, four, six, eight, 12, 26, and 52 weeks after stroke. Penalized linear mixed models were developed to predict patients' functional recovery trajectories. An external validation cohort included 1049 newly registered stroke patients between 2005 and 2011. Prediction errors on discrimination and calibration were assessed. The potential clinical utility was evaluated using prognostic accuracy measurements and decision curve analysis. Results Predictive recovery curves showed good accuracy, with root mean squared deviation of 3 Barthel Index points and a R 2 of 83% up to one year after stroke in the external cohort. The negative predictive values of the risk of poor recovery (Barthel Index <8) at three and 12 months were also excellent, 96% (95% CI [93.6-97.4]) and 93% [90.8-95.3], respectively, with a potential clinical utility measured by likelihood ratios (LR+:17 [10.8-26.8] at three months and LR+:11 [6.5-17.2] at 12 months). Decision curve analysis showed an increased clinical benefit, particularly at threshold probabilities of above 5% for predictive risk of poor outcomes. Conclusions A recovery curves tool seems to accurately predict progression of functional recovery in poststroke patients.

Background and Purpose: Basic activities of daily living measures are often supplemented by extended activities of daily living. We compared the Frenchay Activities Index (FAI) and Nottingham Extended Activities of Daily Living (NEADL) with the Barthel Index (BI) in terms of distribution of scores, concurrent validity, reliability, and their agreement and investigated the predictors of scales outcomes., Methods: Two hundred thirty-eight patients from the population-based South London Stroke Register were assessed with the BI, FAI, and NEADL 3 months after a first-ever stroke. The pairwise relationship was studied using correlations, fractional polynomial regression, and Bland and Altman plot; the baseline predictors, for example, sociodemography, case severity: National Institutes of Health Stroke Scale, and 7-day Abbreviated Memory Test, comorbidities, and acute treatments by negative binomial regression., Results: The BI was highly affected by a ceiling effect (33% had the highest score), FAI was only affected by floor effect (19%), but NEADL was symmetrical with only 4% highest and lowest score. Despite high concurrent validity of the scales (r ≥0.80, P<0.001), they agreed poorly only for the highest and the lowest level of activities. The association and agreement of NEADL with BI was higher than that of FAI with BI. Severe stroke patients (National Institutes of Health Stroke Scale >13) had 28% lower BI (79% lower FAI and 62% lower NEADL) score than nonsevere patients (P≤0.001). Cognitively intact patients (Abbreviated Memory Test: 8-10) had 2.3 times greater FAI values (65% higher NEADL) compared with impaired patients (P<0.001)., Conclusions: The NEADL scale was symmetrical, concurrently valid with no floor and ceiling effects. It corresponded better with BI than FAI did confirming its basic activities of daily living properties, yet it is a more sensitive tool for extended activities of daily living without the floor and ceiling effects. Future functional status could be predicted by the acute stage National Institutes of Health Stroke Scale score, whereas only extended activities of daily living status could be predicted by the Abbreviated Memory Test score. Predicting future functional status at the acute stage may decrease unnecessary length of stay in acute care settings.

Background and Purpose: Data are lacking on the differences in hemorrhagic stroke incidence between black Caribbean (BC), black African (BA), and white ethnic groups. We estimated the incidence for primary intracerebral hemorrhage (PICH) and subarachnoid hemorrhage (SAH) and the associated risk factors for BCs, BAs, and whites., Methods: First-ever stroke patients were drawn from a prospective community stroke register based in a multiethnic population in South London with 9% BCs, 15% BAs, and 63% whites. Incidence rates were standardized to European and world populations and adjusted for age and sex. Incidence rate ratios (IRRs) relative to whites were calculated by Poisson regression., Results: Between 1995 and 2004, 566 incident stroke patients were registered: 395 PICHs and 171 SAHs. For PICH, age- and sex-adjusted IRRs were higher in BAs (IRR, 2.80; 95% CI, 2.00 to 3.91) than in BCs (IRR, 1.46; 95% CI, 1.07 to 1.99) and were particularly pronounced for patients age 0 to 64 years: IRR=3.95 (95% CI, 2.65 to 5.87) in BAs and 2.38 (95% CI, 1.50 to 3.80) in BCs. For those <65 years, prestroke hypertension was more prevalent in BAs and BCs (P=0.049). For SAH, the IRR was higher in BCs (IRR; 1.62; 95% CI, 1.05 to 2.48) than in BAs (IRR, 0.80; 95% CI, 0.43 to 1.46)., Conclusions: The higher incidence of PICH observed in BCs and BAs could be explained by prestroke hypertension being more common among young blacks. The different incidences of SAH in BCs and BAs suggest that the baseline risk of stroke for distinct black ethnic groups is not homogeneous.