Gallbladder disease in northwestern Ontario: the case for Canada's first rural ERCP program.
Bibliographic record
Abstract
INTRODUCTION: The rate of cholecystectomy in northwestern Ontario is double the provincial rate. This paper explores the demographics of cholecystectomy and the role for rural endoscopic retrograde cholangiopancreatography (ERCP) services in the central part of this region. METHODS: We conducted a literature review of ERCP services and cholecystectomy rates, as well as a hospital chart review of patients who underwent laparoscopic cholecystectomies in Sioux Lookout, Ont. We contacted surgeons and gastroenterologists from referral centres in Winnipeg, Man., and Thunder Bay, Ont., for the charts of patients from our catchment area who underwent ERCP. RESULTS: Patients in our region who require urgent and emergent surgery are flown by fixed-wing aircraft to referral centres in Winnipeg and Thunder Bay for assessment and surgery. The rate of ERCP in our population is 150 in 100 000, which is threefold that of other populations, and our cholecystectomy rate is the highest in Ontario. CONCLUSION: Substantial savings in transportation expenses would offset the development costs of an ERCP program and provide more integrated patient care. The volume of patients would support maintenance of competency. This rural area with a high rate of gallbladder disease would benefit from the development of a rural ERCP program.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".