ObjectivesTo (1) identify all available rehabilitation impact indices (RIIs) based on their mathematical formula, (2) assess the evidence for independent predictors of each RII and (3) propose a nomenclature system to harmonise the names of RIIs.DesignSystematic review.Data sourcesPubMed and references in primary articles.Study selectionFirst, we identified all available RII through preliminary literature review. Then, various names of the same formula were used to identify studies, limited to articles in English and up to 31 December 2011, including case–control and cohort studies, and controlled interventional trials where RIIs were outcome variable and matching or multivariate analysis was performed.ResultsThe five RIIs identified were (1) absolute functional gain (AFG)/absolute efficacy/total gain, (2) rehabilitation effectiveness (REs)/Montebello Rehabilitation Factor Score (MRFS)/relative functional gain (RFG), (3) rehabilitation efficiency (REy)/length of stay-efficiency (LOS-EFF)/efficiency, (4) relative functional efficiency (RFE)/MRFS efficiency and (5) revised MRFS (MRFS-R). REy/LOS-EFF/efficiency had the most number of supporting studies, followed by REs and AFG. Although evidence for different predictors of RIIs varied according to the RII and study population, there is good evidence that older age, lower prerehabilitation functional status and cognitive impairment are predictive of poorer AFG, REs and REy.Conclusions5 RIIs have been developed in the past two decades as composite rehabilitation outcome measures controlling premorbid and prerehabilitation functional status, rate of functional improvement, each with varying levels of evidence for its predictors. To address the issue of multiple names for the same RII, a new nomenclature system is proposed to harmonise the names based on common mathematical formula and a first-named basis.
Background and Objectives: This paper aims to describe and compare the characteristics of 2 stroke populations in Singapore and in St. Louis, USA, and to document thrombolysis rates and contrast factors associated with its uptake in both populations. Methods: The stroke populations described were from the Singapore Stroke Registry (SSR) in Singapore and the Cognitive Rehabilitation Research Group Stroke Registry (CRRGSR) in St. Louis, MO, USA. The registries were compared in terms of demographics and stroke risk factor history. Logistic regression was used to determine factors associated with thrombolysis uptake. Results: A total of 39,323 and 8,106 episodes were recorded in SSR and CRRGSR, respectively, from 2005 to 2012. Compared to CRRGSR, patients in SSR were older, male, and from the ethnic majority. Thrombolysis rates in SSR and CRRGSR were 2.5 and 8.2%, respectively, for the study period. History of ischemic heart disease or atrial fibrillation was associated with increased uptake in both populations, while history of stroke was associated with lower uptake. For SSR, younger age and males were associated with increased uptake, while having a history of smoking or diabetes was associated with decreased uptake. For CRRGSR, ethnic minority status was associated with decreased uptake. Conclusions: The comparison of stroke populations in Singapore and St Louis revealed distinct differences in clinicodemographics of the 2 groups. Thrombolysis uptake was driven by nonethnicity demographics in Singapore. Ethnicity was the only demographic driver of uptake in the CRRGSR population, highlighting the need to target ethnic minorities in increasing access to thrombolysis.
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