Permanent stoma use in rectal cancer surgery in Canada: A population-based analysis.
Bibliographic record
Abstract
6622 Background: Sphincter preservation is important for many patients with rectal cancer; avoidance of a permanent stoma (either colostomy or ileostomy) is a well-accepted quality indicator of rectal cancer care. This study describes, at a population level, the frequency of permanent stoma (PS) use in rectal cancer surgery in Canada. In addition, this study examines potential disparities in PS use related to income, geography and immigration status. Methods: Patients undergoing resection for primary adenocarcinoma of the rectum in Canada during fiscal years 2007/08-2011/12 with a valid postal code were included; procedure codes from the discharge abstract database were used to categorize surgery as involving either a permanent stoma (PS), temporary stoma (TS) or no stoma (NS). Income for urban Canada was categorized according to neighbourhood income quintile, and immigration density represented the percentage of immigrant/non-permanent populations living in a dissemination area based on census information. Geography was examined according to province of residence, statistical area classification (SAC) of urban/rural, and travel time (in minutes) to nearest hospital Results: Among the 10,559 patients undergoing rectal cancer resection, 3,895 (36.9 %) underwent a PS, 3,501 (33.2 %) a TS, and 3,163 (30.0%) had NS. Significant variation in PS rates was identified among 9 Canadian provinces (range 35.1%- 51.4%; p<0.0001). The table below shows increased rates of PS among patients living in rural/remote areas, low income neighbourhoods, and those with longer travel time to hospital. Lower rates of PS were seen among patients residing in areas of higher immigration density. Conclusions: Significant variation exists in the use of PS for rectal cancer in Canada, particularly related to geography. Better understanding of root causes of such variation will be important to guide targeted initiatives aimed at optimizing the quality of rectal cancer care at a population level. % with PS P value SAC 0.0003 Urban 35.9 Rural 36.1 Rural - remote 40.1 Rural - very remote 41.9 Travel time (minutes) <0.0001 0-39 35.9 40-179 41.9 ≥ 180 42.6 Immigrant density <0.0001 Low 37.9 Middle 35.7 High 30.3 Income 0.003 Lowest quintile 38.5 Highest quintile 35.4
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".