Abstract 11695: Long-Term Clinical Outcomes of Minimally Invasive Aortic Valve Surgery in Patients With Aortic Valve Disease
Bibliographic record
Abstract
Introduction: We aim to analyze multicenter long-term clinical outcomes of minimally invasive aortic valve replacement (MI-AVR) in patients with aortic valve disease. Hypothesis: We hypothesize that MI-AVR provides good long-term clinical outcomes in patients undergoing aortic valve surgery. Methods: All consecutive 1,972 patients undergoing MI-AVR with either ministernotomy (n= 986) or right anterior minithoracotomy (RAM, n=986) between 1999 and 2019, were included. Primary outcomes were all-cause mortality and cardiac death. Results: Preoperatively, mean age was 72.1 (±13.7) year-old, and mean STS-PROM risk score was 0.38%. Intraoperatively, mean operative time (min) was 213.97 (± 56.9), while 313 (15.9%) patients were converted to full sternotomy. Postoperatively, 69 (3.5%) patients had prolonged mechanical ventilation (< 24 hours), 59 (3%) patients had re-exploration for bleeding, 10 (0.5%) patients had paravalvular leak (moderate/severe), 22 (1.1%) patients had non-fatal stroke, and 28 (1.4%) patients had non-fatal myocardial infarction. Mean intensive care unit stay was 14.45 (± 10.15) hours, and mean hospital length of stay (LOS) was 7 (± 3.5) days. Thirty-day all-cause mortality occurred in 39 (2%) patients while 30-day cardiac-death occurred in 23 (1.2%) patients. Thirty-day predictors for all-cause mortality included age <75-years, post-operative LOS, peri-operative stroke, and RAM. Mean follow-up time was 10-years. At 20-year follow-up, all-cause death and CV-death incidence were 1156 (60%) and 170 (8.8%) patients, respectively. Valve-related deaths occurred in 33 (1.7%) patients. Long-term predictors for all-cause mortality included age <75-years, chronic kidney failure, mechanical ventilation <12 hours, RAM, and hospital LOS <10 days. Conclusions: MI-AVR is a safe, valid, and reproducible surgical procedure for patients with aortic valve disease. In addition, it provides good long-term outcomes.
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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 | 0.002 |
| 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 | 0.000 |
| 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".