Time trend analysis of mastoidectomy procedures performed in Ontario, 1987–2007
Bibliographic record
Abstract
CONCLUSIONS: There has been a reduction in the number of modified radical mastoidectomy and revision mastoidectomy surgeries per head of population in Ontario between 1987 and 2007, we believe that this represents a true reduction in prevalence of cholesteatoma. The increase of cases performed at the University Hospital Network, Toronto (UHN) may represent a shift to subspecialization in the treatment of chronic ear disease. OBJECTIVE: To analyze the trends in mastoid operations for chronic middle ear disease in the Canadian province of Ontario between 1987 and 2007 and to determine whether an increasing proportion of these procedures are being performed in tertiary referral centres. METHODS: The year on year population and number of mastoid procedures performed per year in Ontario and at the UHN between 1987 and 2007 were obtained from Statistics Canada and the Ministry of Health and Long-Term Care, Ontario, respectively. Population-adjusted rates of mastoid surgery for Ontario and the UHN. These data were collated and graphically represented for trend analysis. RESULTS: The population-adjusted number of mastoid procedures for Ontario declined from 7.1 cases per 100,000 in 1986 to 4.1 cases per 100,000 in 2006. During this time the number of both modified radical mastoidectomies and revision mastoid surgeries at UHN increased.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".