No decrease in incidence of arthroscopic meniscectomy in a Canadian province
Bibliographic record
Abstract
Abstract Purpose Arthroscopic meniscectomy (APM) is the most common procedure in orthopedic surgery, despite increasing evidence questioning its benefit over conservative management for treatment of degenerative meniscal tears. The purpose of this study is to determine the epidemiology and trends of APM in Saskatchewan, a Canadian province, over a 20 year period. Methods Physician billing codes were used to identify patients who underwent APM in Saskatchewan between January 1, 1998 and December 31, 2017. Records were obtained from eHealth Saskatchewan, a provincial health database. Data was analyzed for overall incidence and age‐specific trends of APM. Results A total of 35,099 APMs were performed during the study period. The population of Saskatchewan ranged from 992,314 to 1,150,782 (median 1,017,368) during this time interval, with 81 orthopedic surgeons performing APM. Overall incidence rate of APM did not change significantly over time. No decrease was observed in patients presumed to have degenerative tears (≥ 50 years). The number of meniscectomies in patients ≥ 50 years was significantly greater during the second decade of study compared to the first (OR 1.48, p < 0.01). Conversely, the increase in incidence rate among older patients was not statistically significant (R2 = 0.125, n.s.). Conclusion Overall incidence rate of APM in Saskatchewan has not decreased during the last 20 years. Furthermore, APM frequency increased over time for individuals ≥ 50 years. Several regional factors may have contributed to these findings, including the large proportion of Saskatchewan residents engaged in physically demanding work and barriers to accessing physiotherapy services. Given recent evidence disputing the benefit of APM over conservative measures, this study highlights the need for improved dissemination of evidence, as well as the importance of an individualized treatment plan to address patient‐specific factors. Level of evidence Level IV
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".