Feasibility and Cost Analysis of Ambulatory Endovascular Aneurysm Repair
Bibliographic record
Abstract
PURPOSE: We sought to compare the costs of ambulatory endovascular aneurysm repair (a-EVAR) and inpatient EVAR (i-EVAR) at up to 1-year of follow-up. MATERIALS AND METHODS: A retrospective cohort study of consecutive patients undergoing elective EVAR between April 2016 and December 2018 at two academic centers. Patients planned for a-EVAR were compared with i-EVAR. Costs at 30 days and 1 year were extracted. These included operating room (OR) use, bed occupancy, laboratory and imaging, emergency department (ED) visits, readmissions, and reinterventions. Baseline characteristics were compared. Multiple regression model was used to identify predictors of increased EVAR costs. Repeated measures analysis of variance (ANOVA) was used to compare cost differences at 30 days and 1 year via an intention-to-treat analysis. Bonferroni post hoc test compared between-group differences. A p value<0.05 was considered statistically significant. RESULTS: One hundred seventy patients were included. Most underwent percutaneous EVAR (>94%) under spinal anesthesia (>84%). Ambulatory endovascular aneurysm repair was successful in 84% (84/100). Ambulatory endovascular aneurysm repair patients (76±8 years) were younger than i-EVAR (78±9 years). They also had a smaller mean aneurysm diameter (56±6 mm) compared with i-EVAR (59±6 mm). Emergency department visits, readmissions, and reinterventions were similar up to 1 year (all p=NS). Ambulatory endovascular aneurysm repair costs showed a non-statistically significant reduction in total costs at 30 days and 1 year by 27% and 21%, respectively. Patients younger than 85 years and males had a 30-day cost reduction by 34% (p=0.027) and 33% (p=0.035), respectively with a-EVAR. CONCLUSIONS: Same-day discharge is feasible and successful in selected patients. Patients younger than 85 years and males have a short-term cost benefit with EVAR done in the ambulatory setting without increased complications or reinterventions. CLINICAL IMPACT: This study shows the overall safety of ambulatory EVAR with proper patient selection. These patient had similar post-intervention complications to inpatients. Same day discharge also resulted in short-term reduction in costs in male patients and patients younger than 85 years.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".