The Evolution of Stroke Rehabilitation Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: In the interest of prioritizing resources and providing future direction for researchers, a complete overview of the landscape of stroke rehabilitation literature was conducted. AIM: We aimed to examine the evolution of stroke rehabilitation randomized controlled trials, with respect to number, sample size, and methodological quality between 1970 and September 2012. METHODS: Using the Evidence-Based Review of Stroke Rehabilitation (http://www.ebrsr.com), all randomized controlled trials related to stroke rehabilitation interventions were eligible for inclusion and were divided into five groups based on the primary outcome (i.e., motor, cognitive, medical complications, psychosocial, and 'other'). RESULTS: One thousand sixty-three randomized controlled trials met inclusion criteria, with motor studies accounting for 58·8% of the total. The total number of randomized controlled trials grew between 1970 and 2012, with 35·2% of all the studies published in the last five-years. Motor randomized controlled trials had the smallest median sample size compared with cognitive (P < 0·018), medical complications (P < 0·001), psychosocial (P < 0·001), and 'other' (P < 0·001) randomized controlled trials. Between 1973 and 1977 and 2008 and 2012, there was no statistically significant increase in median sample sizes (P = 0·845). Psychosocial randomized controlled trials had higher median Physiotherapy Evidence Database scores when compared with motor (P = 0·002), cognitive (P = 0·035), and 'other' randomized controlled trials (P = 0·036), but not medical complication randomized controlled trials (P = 0·591). Over time, median Physiotherapy Evidence Database scores for all randomized controlled trials significantly increased from 5 (interquartile range 0·5) in 1973-1977 to 7 (interquartile range 3) in 2008-2012 (P = 0·008). CONCLUSIONS: Randomized controlled trials in stroke rehabilitation have increased over the past four decades, with an associated increase in methodological quality, but not sample size.
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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 | 0.647 | 0.842 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.023 | 0.027 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.023 | 0.022 |
| Open science | 0.009 | 0.006 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".