Changing trends in rectal cancer surgery in Ontario: 2002–2009
Bibliographic record
Abstract
AIM: The safety and efficacy of laparoscopic surgery for colon cancer have been demonstrated in large, multicentre clinical trials. The study aimed to determine the use of laparoscopic surgery for rectal cancer in Ontario over a 7-year period. METHOD: We conducted a retrospective study examining rates of elective rectal cancer surgery among 10.5 million adults in Ontario, Canada, from 1 April 2002 to 31 March 2009. We linked the Canadian Institute for Health Information Discharge Abstract Database, the Registered Persons Database and the database of the Ontario Cancer Registry to assess procedures used over the period. Data on demographics were collected. Trends were assessed using time series analysis. RESULTS: Over the 7-year period, 8189 open and 1079 laparoscopic elective operations for rectal cancer were identified. The annual rate of laparoscopic rectal cancer procedures increased from 0.60 per 100,000 population in 2003 to 2.24 per 100,000 population in 2008 (P < 0.01). Laparoscopic patients were similar to open with respect to age (66.5 ± 11.8 vs 66.2 ± 12.1 years; standardized difference 0.02), gender (63.2%vs 59.4%; standardized difference 0.08), Charlson Comorbidity Index score (standardized difference < 0.1) and socioeconomic status (standardized difference < 0.1). CONCLUSION: Laparoscopic rectal cancer surgery rates are increasing in Ontario. Ongoing research regarding the long-term safety and effectiveness of the laparoscopic approach for rectal cancer surgeries may lead to greater increases in its utilization.
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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 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".