Establishing consensus on the definition of an isolated hip fracture for trauma system performance evaluation: A systematic review
Bibliographic record
Abstract
BACKGROUND: Risk-adjusted mortality is widely used to benchmark trauma center care. Patients presenting with isolated hip fractures (IHFs) are usually excluded from these evaluations. However, there is no standardized definition of an IHF. We aimed to evaluate whether there is consensus on the definition of an IHF used as an exclusion criterion in studies evaluating the performance of trauma centers in terms of mortality. MATERIALS AND METHODS: We conducted a systematic review of observational studies. We searched the electronic databases MEDLINE, EMBASE, BIOSIS, The Cochrane Library, CINAHL, TRIP Database, and PROQUEST for cohort studies that presented data on mortality to assess the performance of trauma centers and excluded IHF. A standardized, piloted data abstraction form was used to extract data on study settings, IHF definitions and methodological quality of included studies. Consensus was considered to be reached if more than 50% of studies used the same definition of IHF. RESULTS: We identified 8,506 studies of which 11 were eligible for inclusion. Only two studies (18%) used the same definition of an IHF. Three (27%) used a definition based on Abbreviated Injury Scale (AIS) Codes and five (45%) on International Classification of Diseases (ICD) codes. Four (36%) studies had inclusion criteria based on age, five (45%) on secondary injuries, and four (36%) on the mechanism of injury. Eight studies (73%) had good overall methodological quality. CONCLUSIONS: We observed important heterogeneity in the definition of an IHF used as an exclusion criterion in studies evaluating the performance of trauma centers. Consensus on a standardized definition is needed to improve the validity of evaluations of the quality of trauma care.
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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 | 0.140 | 0.376 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.016 |
| Bibliometrics | 0.023 | 0.017 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".