Perioperative Outcomes for Centers Routinely Admitting Postoperative Endovascular Aortic Aneurysm Repair to the ICU
Bibliographic record
Abstract
BACKGROUND: Intensive care unit (ICU) admission after endovascular aortic aneurysm repair (EVAR) varies across medical centers. We evaluated the association of postoperative ICU use with perioperative and long-term outcomes after EVAR. STUDY DESIGN: The Vascular Quality Initiative (2003-2019) was queried for index elective EVARs. Included centers were categorized by percentage of patients with EVARs postoperatively admitted to the ICU; routine ICU (rICU) centers as ≥80% ICU admissions and nonroutine ICU (nrICU) centers as ≤20% ICU admissions. Patients admitted preoperatively or with same day discharge were excluded. Perioperative outcomes and survival were compared between rICU and nrICU centers. RESULTS: Of 45,310 EVARs in the database, 35,617 were performed at rICU or nrICU centers - 5,443 (15.3%) at 71 rICU centers and 30,174 (84.7%) at 200 nrICU centers. Overall, mean age was 73.4 years and 81.6% were male. Postoperative myocardial infarction, pulmonary complications, stroke, leg ischemia, and in-hospital mortality were similar between rICU and nrICU centers (all p > 0.05). Postoperative length of stay (LOS) was prolonged at rICU centers (mean) (2.2 ± 3.6 vs 2 ± 4.2 days, p < 0.001). One-year survival was similar between rICU and nrICU centers, respectively, (94.9% vs 95.4%, p = 0.085). When compared with nrICU centers, rICU centers had similar 1-year mortality risk (hazard ratio [HR] 1.15, 95% CI 0.99-1.34, p = 0.076), but were associated with longer postoperative LOS (means ratio 1.1, 95% CI 1.08-1.13, p < 0.001). CONCLUSIONS: Routine ICU use after EVAR was associated with prolonged postoperative LOS, without improved perioperative/long-term morbidity or mortality. Updated care pathways to include postoperative admission to lower acuity care units may reduce costs without compromising care.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".