Systematic review on the inclusion of patients with cognitive impairment in hip fracture trials: a missed opportunity?
Bibliographic record
Abstract
BACKGROUND: More than 320 000 hip fractures occur annually in North America. An estimated 30% of this population have cognitive impairment. We sought to determine the extent to which patients with cognitive impairment or dementia have been included in randomized controlled trials (RCTs) assessing hip fracture management. METHODS: We conducted a systematic search of 3 electronic journal databases of articles published between January 2000 and June 2010. Studies were screened in duplicate to collect English-language RCTs assessing operative interventions for femoral head, neck or intertrochanteric fractures. We systematically collected descriptive data and used the χ(2) test for comparison between groups as appropriate. RESULTS: We screened 1201 abstracts, 72 of which were eligible for inclusion in our review. Femoral neck and intertrochanteric fractures were equally represented. Thirty-three (46%) studies did not report the inclusion or exclusion of patients with cognitive impairment. Nineteen (26%) studies explicitly included cognitively impaired patients, whereas 20 (28%) excluded them. Only 2 trials (3%) reported outcomes specific to cognitively impaired patients. Fourteen trials (19.4%) reported the use of a validated cognitive assessment tool. None of the trials that reported inclusion of cognitively impaired patients were from North American centres. CONCLUSION: One in 3 patients with hip fractures have concomitant cognitive impairment, yet 8 of 10 hip fracture trials excluded or ignored this population. The ambiguity or exclusion of these patients misses an opportunity to study outcomes and identify factors associated with improved prognosis.
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 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 | 0.131 | 0.407 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.022 | 0.013 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".