Comparing stroke rehabilitation inpatients and clinical trials eligibility criteria: A secondary chart review analysis revealing that most patients could have been excluded from rehabilitation trials based on comorbidity status.

Background: The generalizability of treatments examined in rehabilitation randomized controls trials (RCTs) partly depend on the similarity between trial subjects and a stroke rehabilitation inpatient population. The aim of this study was to determine the proportion of stroke rehabilitation inpatients that would have been eligible or ineligible to participate in published stroke RCTs.

Methods: This was a secondary analysis of chart review data collected as part of an independent quality improvement initiative. Data pertaining to the characteristics of stroke rehabilitation inpatients (e.g. age, cognitive impairment, previous stroke, comorbidities) were extracted from the medical charts of patients consecutively admitted to an inpatient stroke rehabilitation unit at a large urban rehabilitation hospital in Canada. Using the exclusion criteria categories of stroke RCTs identified from a systematic scoping review of 428 RCTs, we identified how many stroke rehabilitation inpatients would have been eligible or ineligible to participate in stroke RCTs based on their age, cognitive impairment, previous stroke and presence of comorbidities.

Results: In total, 110 stroke rehabilitation inpatients were included. Twenty-four percent of patients were 80 years of age or older, 84.5% had queries or concerns regarding patient cognitive abilities, 28.0% had a previous stroke, and 31.8% had a severe stroke. Stroke rehabilitation inpatients had six comorbidities on average. Based on these factors, most stroke rehabilitation inpatients could have been excluded from stroke RCTs, with cognitive impairment the most common RCT exclusion criteria.

Conclusions: Changes to the design of RCTs would support the development of clinical practice guidelines that reflect stroke rehabilitation inpatient characteristics, enhancing equity, diversity, and inclusion within samples and the generalizability of results.