Inequity in rehabilitation interventions after hip fracture: a systematic review
Bibliographic record
Abstract
OBJECTIVE: to determine the extent to which equity factors contributed to eligibility criteria of trials of rehabilitation interventions after hip fracture. We define equity factors as those that stratify healthcare opportunities and outcomes. DESIGN: systematic search of MEDLINE, Embase, CINHAL, PEDro, Open Grey, BASE and ClinicalTrials.gov for randomised controlled trials of rehabilitation interventions after hip fracture published between 1 January 2008 and 30 May 2018. Trials not published in English, secondary prevention or new models of service delivery (e.g. orthogeriatric care pathway) were excluded. Duplicate screening for eligibility, risk of bias (Cochrane Risk of Bias Tool) and data extraction (Cochrane's PROGRESS-Plus framework). RESULTS: twenty-three published, eight protocol, four registered ongoing randomised controlled trials (4,449 participants) were identified. A total of 69 equity factors contributed to eligibility criteria of the 35 trials. For more than 50% of trials, potential participants were excluded based on residency in a nursing home, cognitive impairment, mobility/functional impairment, minimum age and/or non-surgical candidacy. Where reported, this equated to the exclusion of 2,383 out of 8,736 (27.3%) potential participants based on equity factors. Residency in a nursing home and cognitive impairment were the main drivers of these exclusions. CONCLUSION: the generalisability of trial results to the underlying population of frail older adults is limited. Yet, this is the evidence base underpinning current service design. Future trials should include participants with cognitive impairment and those admitted from nursing homes. For those excluded, an evidence-informed reasoning for the exclusion should be explicitly stated. PROSPERO: CRD42018085930.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".