The seasonal variation of Achilles tendon ruptures in Vancouver, Canada: a retrospective study
Bibliographic record
Abstract
OBJECTIVE: To examine the seasonal distribution of tendon ruptures in a large cohort of patients from Vancouver, Canada. DESIGN: Retrospective chart review. SETTING: Acute Achilles tendon rupture cases that occurred from 1987 to 2010 at an academic hospital in Vancouver, Canada. Information was extracted from an orthopaedic database. PARTICIPANTS: No direct contact was made with the participants. The following information was extracted from the OrthoTrauma database: age, sex, date of injury and season (winter, spring, summer and autumn), date of surgery if date of injury was unknown and type of injury (sport related or non-sport related/unspecified). Only acute Achilles tendon rupture cases were included; chronic cases were excluded along with those that were conservatively managed. PRIMARY AND SECONDARY OUTCOMES: The primary outcome was to determine the seasonal pattern of Achilles tendon rupture. Secondary outcomes, such as differences in gender and mechanism of sport (non-sport vs sport related), were also assessed. RESULTS: There were 543 cases in total; 83% of the cases were men (average age 39.3) and 17% were women (average age 37.3). In total, 76% of cases were specified as sport related. The distribution of injuries varied significantly across seasons (χ(2), p<0.05), with significantly more cases occurring in spring. The increase in the number of cases in spring was due to sport-related injuries, whereas non-sport-related cases were distributed evenly throughout the year. CONCLUSIONS: The seasonality of sport-related Achilles tendon ruptures should be considered when developing preventive strategies and when timing their delivery.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".