Incidence and predictors of myocardial and kidney injury following endovascular aortic repair: a retrospective cohort study
Bibliographic record
Abstract
We performed a retrospective cohort study in patients who underwent endovascular aneurysm repair (EVAR) to determine the incidence and predictors of myocardial injury and acute kidney injury (AKI). We included 267 consecutive patients who underwent EVAR at two tertiary centres in Canada and Poland. The primary outcome was myocardial injury during hospital stay after EVAR defined as a troponin elevation (ultra-sensitivity troponin I Vidas ≥ 19 ng·L −1 , non-high-sensitivity troponin I Vidas ≥ 0.01 µg·L −1 , high-sensitivity troponin T ≥ 20 ng·L −1 , non-high-sensitivity troponin T ≥ 0.03 ng·mL −1 ). The secondary outcome was AKI defined using the stage 1 of the Acute Kidney Injury Network criteria. Myocardial injury occurred in 78/267 patients (29%; 95% confidence interval [CI], 24.1 to 34.9) and with AKI occurring in 25/267 (9.4%; 95% CI, 6.4 to 13.5). In a multivariable analysis, the following variables were associated with an increased risk of myocardial injury: age (adjusted odds ratio [aOR], 1.65 per ten-year increase; 95% CI, 1.09 to 2.49), Revised Cardiac Risk Index score ≥3 (aOR, 2.85; 95% CI, 1.26 to 6.41), The American Society of Anesthesiology physical status score 4 (aOR, 2.24; 95% CI, 1.12 to 4.47), duration of surgery (aOR, 1.27 per each hour; 95% CI, 1.00 to 1.61), and perioperative drop in hemoglobin (aOR, 3.35 per 10 g·dL −1 decrease; 95% CI, 1.00 to 11.3). Predictors of AKI were duration of surgery (aOR, 1.72 per hour; 95% CI, 1.36 to 2.17), a preoperative estimated glomerular filtration rate (eGFR) of 30-59 mL·min −1 (aOR, 3.82; 95% CI, 1.42 to 10.3), and an eGFR < 30 mL·min −1 (aOR, 37.0; 95% CI, 7.1 to 193.8). Myocardial injury and AKI are frequent during hospital stay after EVAR and warrant further investigation in prospective studies.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".