P1-94 The epidemiology and costs of ankle injuries: a review of the literature
Bibliographic record
Abstract
Introduction Ankle sprains are one of the most common injuries presenting to emergency departments, representing 3% to 5% of all visits in the UK, and 10% of all injury-related visits in the USA. Ankle injuries have significant physical and economic consequences for the affected individuals. Objectives To describe the epidemiology of ankle sprains and fractures among the general population; and to determine the direct and indirect costs related to the diagnosis and treatment of ankle injuries. Methods A comprehensive literature review of Ovid MEDLINE, EMBASE, Cochrane DSR, ACP Journal Club, AMED, Ovid Healthstar, and CINAHL was conducted for English-language studies on ankle sprains and fractures published from 1980 to 2010. Results The search identified 2394 studies of which 47 were selected for analysis. A majority of the studies were published in the last decade. The incidence of ankle sprains was 2 to 7 per 1000 person-years, while the incidence of ankle fractures was 1 per 1000 person-years. The costs of emergency ankle sprain management ranged from 126.13 to 2356.21 per patient (2009 CAD), depending on sprain severity. The management costs were higher for ankle fractures: 1692.82 to 15 802.26 (2009 CAD) per patient. The economic evaluations were conducted from the societal or healthcare system perspective. Conclusions Information on the epidemiology of ankle sprains and fractures may help plan for health policy and the provision of health services. Moreover, the cost data may inform future studies undertaking economic evaluations of the diagnosis and treatment of ankle injuries.
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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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.022 | 0.028 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".