Abstract 115: Assessing the Concordance Between Stroke Rehabilitation Research Participants & ‘Real World’ Stoke Patients
Bibliographic record
Abstract
Stroke rehabilitation programs have been transformed to better align with stroke Clinical Practice Guidelines (CPGs), which prioritize randomized control trials as evidence-based best practices. However, a recent review of stroke rehabilitation randomized control trials (RCTs) found that the RCTS tended to include younger participants, excluded participants based on age related criteria, and often excluded individuals with comorbidities. The objective of this study was to determine the proportion of stroke patients that would meet the enrolment criteria of stroke rehabilitation randomized controlled trials. A retrospective chart audit was conducted for all patients discharged from a high intensity stroke rehabilitation unit for a one-year period (n=110). RCT exclusion criteria were extracted from a recent review that analyzed the study inclusion and exclusions of 428 RCTs (age, cognitive impairment, previous stroke, and comorbidities). These study exclusions were applied to the 110 patients to determine how many patients would have been eligible to participate in the RCTs. Patients admitted to the stroke rehab unit had a mean age of 67.4 years and an average of 6.2 co-morbidities. 60.1% of these patients would have been excluded from participating in the RCTs by one or more exclusion criteria. 5.5% of patients would have been excluded based on age, 84.5% of patients would have been ineligible for 54% of RCTs based on cognitive impairment, 28% of patients would have been ineligible for 36% of RCTs based on a previous stroke, and 4.2% of patients would have been excluded based on the presence of a CCI condition or stroke risk factor. Results highlight the difference between trial subjects and ‘real world’ patients. Based on our understanding of how people accumulate chronic conditions with age, it can be inferred that the high quality evidence may not reflect the clinical reality of stroke rehabilitation. Given the high prevalence of increased age and comorbidities among stroke rehabilitation patients, this study emphasizes the importance of including ‘typical stroke patients’ in research studies or supporting the use of alternative methodologies that addresses application of study results to older patients with comorbidities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.192 | 0.419 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".