Factors associated with prolonged post-operative acute care length of stay in limb amputation patients in Saskatchewan, Canada
Bibliographic record
Abstract
BACKGROUND: The effect of predisposing factors on post-operative acute care length of stay (POALOS) after lower extremity amputation (LEA) has been sparsely studied with reports largely focused on major (through/proximal to the ankle) LEA specifically due to diabetes mellitus (DM). Although valuable, the narrow focus disregards the impact of other causes and minor levels (distal to the ankle) of LEA. To address this gap, this study aimed to identify predisposing factors associated with prolonged POALOS after index LEA stratified by amputation level in Saskatchewan. METHODS: The study used Saskatchewan's provincial linked administrative health data and demographic factors between 2006 and 2019. Amputation levels, identified as major or minor, were derived from the amputation procedure codes. POALOS was calculated by subtracting patients' intervention date from discharge date, recorded in days, and categorized as short (< 7 days) or prolonged (> 7 days). Multivariable logistic regression was performed to identify predictors associated with prolonged POALOS. RESULTS: Of the 3123 LEA cases 1421 (45.5%) had prolonged POALOS. The median POALOS for the entire cohort was 7 days (IQR 3 to 16 days); 5 days (IQR 1 to 10 days) for minor LEA and 11 days (IQR 5 to 23 days) for major LEA. Predictors of prolonged POALOS after minor LEA were diabetes (AOR = 2.47, 95% CI: 1.87-3.27) and general surgeon (AOR = 1.52, 95% CI: 1.21-1.91). Minor LEA performed by orthopedic surgeons were half (AOR = 0.49, 95% CI: 0.35-0.70) as likely to experience prolonged POALOS. Predictors of prolonged POALOS after major LEA were diabetes (AOR = 1.34, 95% CI: 1.04-1.71), general surgeon (AOR = 1.91, 95% CI: 1.45-2.49), urban residence (AOR = 1.58, 95% CI: 1.25-1.99), Resident Indian (RI) status (AOR = 1.57, 95% CI: 1.15-2.15), and age with the likelihood of prolonged POALOS after LEA attenuating with increasing age: 35-54 years (AOR = 2.73, 95% CI: 1.56-4.76); 55-69 years (AOR = 2.65, 95% CI: 1.54-4.58); and 70+ years (AOR = 1.81, 95% CI: 1.05-3.11). CONCLUSION: This study identified only diabetes and surgical specialty predicted prolonged POALOS after both major and minor LEA in Saskatchewan while residence, RI status, and age were predictors of POALOS after major LEA. These findings shed light on the need for further research to identify confounding factors. It is not clear if general surgeons care for more unplanned, emergent cases with poor entry-level health while specialty surgeons perform more scheduled procedures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".