The epidemiology and trends in management of acute Achilles tendon ruptures in Ontario, Canada
Bibliographic record
Abstract
AIMS: The aims of this study were to establish the incidence of acute Achilles tendon rupture (AATR) in a North American population, to select demographic subgroups and to examine trends in the management of this injury in the province of Ontario, Canada. PATIENTS AND METHODS: Patients ≥ 18 years of age who presented with an AATR to an emergency department in Ontario, Canada between 1 January 2003 and 31 December 2013 were identified using administrative databases. The overall and annual incidence density rate (IDR) of AATR were calculated for all demographic subgroups. The annual rate of surgical repair was also calculated and compared between demographic subgroups. RESULTS: A total of 27 607 patients (median age, 44 years; interquartile range 26 to 62; 66.5% male) sustained an AATR. The annual IDR increased from 18.0 to 29.3 per 100 000 person-years between 2003 and 2013. The mean IDR was highest among men between the ages of 40 and 49 years (46.0/100 000 person-years). The annual rate of surgical repair dropped from 20.1 in 2003 to 9.2 per 100 AATRs in 2013. There was a noticeable decline after 2009. CONCLUSION: The incidence of AATR is increasing in Ontario, while the annual rate of surgical repair is decreasing. A sharp decline in the rate of surgical repair was noted after 2009. This coincided with the publication of several high-quality RCTs which showed similar outcomes for the 'functional' non-operative management and surgical repair. Cite this article: Bone Joint J 2017;99-B:78-86.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".