North American Trends in Utilization and Outcomes of the Ross Procedure: A Word of Caution
Bibliographic record
Abstract
We sought to evaluate contemporary trends in utilization of the Ross procedure in adults and investigate the relationship between surgical volumes and in-hospital mortality. The Society of Thoracic Surgeons Adult Cardiac Surgery Database was queried for patients who underwent the Ross procedure. We used mixed-effects logistic regression to investigate the relationship between Ross volumes and in-hospital mortality. Statistical significance was evaluated using likelihood ratio tests. Between 2008 and 2023, 2,268 Ross procedures were reported. Median age was 43 years (IQR: 32–52), and 1,550 (68%) patients were male. Utilization of the Ross procedure reached a nadir in 2017 (n = 63) before increasing annually, reaching 531 cases in 2023. In 2017, Ross procedures represented 0.9% of all AVRs performed on patients aged ≤60 years; by 2023, this proportion had increased to 7.2%. The risk of in-hospital mortality associated with the Ross procedure declined from 2.8% in 2008 to a nadir of 0.9% in 2020 before increasing to 1.9% in 2023. Compared with centers that performed more than 10 Ross procedures annually, in-hospital mortality was higher in centers that performed only 1 or 2 Ross operations per year (OR 4.5 [95% CI: 1.5–13.2]; p=0.006). Utilization of the Ross procedure is increasing in North America. There is a clear inverse relationship between the volume of Ross procedures and early surgical outcomes. The operative mortality of the Ross procedure is unacceptably high when performed in low-volume centers. The Ross procedure should only be performed in high-volume comprehensive valve centers of excellence.
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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 | 0.030 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".