Association of Kidney Function With Major Postoperative Events After Noncardiac Ambulatory Surgeries
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to estimate the association between estimated glomerular filtration rate (eGFR) and acute myocardial infarction (AMI) or death after ambulatory noncardiac surgery. SUMMARY BACKGROUND DATA: People with chronic kidney disease (CKD) commonly undergo surgical procedures. Although most are performed in an ambulatory setting, the risk of major perioperative outcomes after ambulatory surgery for people with CKD is unknown. METHODS: In this retrospective population-based cohort study using administrative health data from Alberta, Canada, we included adults with measured preoperative kidney function undergoing ambulatory noncardiac surgery between April 1, 2005 and February 28, 2017. Participants were categorized into 6 eGFR categories (in mL/min/1.73m 2 )of ≥60 (G1-2), 45 to 59 (G3a), 30 to 44 (G3b), 15 to 29 (G4), <15 not receiving dialysis (G5ND), and those receiving chronic dialysis (G5D). The odds of AMI or death within 30 days of surgery were estimated using multivariable generalized estimating equation models. RESULTS: We identified 543,160 procedures in 323,521 people with a median age of 66 years (IQR 56-76); 52% were female. Overall, 2338 people (0.7%) died or had an AMI within 30 days of surgery. Compared with the G1-2 category, the adjusted odds ratio of death or AMI increased from 1.1 (95% confidence interval: 1.0-1.3) for G3a to 3.1 (2.6-3.6) for G5D. Emergency Department and Urgent Care Center visits within 30 days were frequent (17%), though similar across eGFR categories. CONCLUSIONS: Ambulatory surgery was associated with a low risk of major postoperative events. This risk was higher for people with CKD, which may inform their perioperative shared decision-making and management.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".