Appendectomies in rural hospitals. Safe whether performed by specialist or GP surgeons.
Bibliographic record
Abstract
OBJECTIVE: To compare outcomes of appendectomies performed in rural hospitals by specialist surgeons and GP surgeons. DESIGN: Retrospective analysis of the Canadian Institute for Health Information's (CIHI) Discharge Abstract Database (DAD) 1996-1999. SETTING: Rural hospitals in Ontario, Saskatchewan, Alberta, and British Columbia. PARTICIPANTS: All surgeons who performed appendectomies in these hospitals during the study period. MAIN OUTCOME MEASURES: Mortality; diagnostic accuracy, perforation, and repeat laparotomy rates; length of stay; and need for transfer to another acute-care institution. RESULTS: Specialist surgeons performed 3624 appendectomies; GP surgeons performed 963. Rates of comorbidity, diagnostic accuracy, and transfer, and mean lengths of stay were similar for patients of GP and specialist surgeons. Patients operated on by specialists were older and more likely to have perforations and to require second intra-abdominal or pelvic procedures. Triage to a specialist, older age, and comorbidity all independently predicted perforation. Only perforation predicted a second intra-abdominal or pelvic procedure. CONCLUSION: Appendectomy is a safe procedure in rural hospitals, whether performed by specialist or GP surgeons. Some difficult cases are routinely referred to specialists.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".