A Canadian population-based description of the indications for lower-extremity amputations and outcomes
Bibliographic record
Abstract
BACKGROUND: To our knowledge, there have been no previously published reports characterizing lower-extremity amputations in Canada. The objective of this study was to describe the indications and outcomes of lower-extremity amputations in the Canadian population. METHODS: We performed a retrospective cohort study of all adult patients who underwent lower-extremity amputation in Canada between 2006 and 2009. Patients were identified from the Canadian Institute for Health Information's Discharge Abstract Database, which includes all hospital admissions across Canada with the exception of the province of Quebec. Pediatric, trauma, and outpatients were excluded. RESULTS: During the study period, 5342 patients underwent lower-extremity amputations in 207 Canadian hospitals. The mean age was 67 ± 13 years, and 68% were men. Amputations were most frequently indicated after admission for diabetic complications (81%), cardiovascular disease (6%), or cancer (3%). In total, 65% of patients were discharged to another inpatient or long-term care facility, and 26% were discharged home with or without extra support. Most patients were diabetic (96%) and most (65%) required a below-knee amputation. Predictors of prolonged (> 7 d) hospital stay included amputation performed by a general surgeon; cardiovascular risk factors, such as diabetes, hypertension, ischemic heart disease, congestive heart failure, or hyperlipidemia; and undergoing the amputation in the provinces of Newfoundland and Labrador, New Brunswick, or British Columbia. CONCLUSION: There is variability in the delivery of lower-extremity amputations and postoperative hospital discharges among surgical specialists and regions across Canada. Future work is needed to investigate the reasons for this variability and to develop initiatives to shorten postoperative hospital stays.
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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 | 0.005 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".