Global Perspectives on the Ross Procedure: A Comprehensive International Survey
Bibliographic record
Abstract
Objectives Recent data demonstrating superior outcomes and enhanced life expectancy with the Ross procedure (RP) have sparked renewed interest and increased utilization. However, the RP remains technically challenging compared to conventional aortic valve replacement (AVR), necessitating specialized expertise and careful patient selection. This study provides global insights into current RP practices to establish best practices and inform new or evolving programs. Methods A web-based survey (> 60 questions) was distributed globally to cardiac surgeons known to perform the RP from May 1 to June 30, 2023. The survey queried surgeon experience, RP volumes, patient selection criteria, preoperative imaging, intraoperative techniques, and postoperative care practices. Responses were analyzed to identify global trends and optimal approaches for RP management. Results Of the 167 respondents, 123 (74%) performed the RP, with 75% performing 5 to 30 procedures annually. Approximately half involved a second attending surgeon. Most treated younger patients and preferred homografts for right ventricular outflow tract reconstruction. Variations existed in the ventriculoaortic and sinotubular junction support (30% vs 45% always support). Most surgeons (89%) enforce strict blood pressure control postoperatively, with 65% prescribing beta-blockers. About 54% use postoperative inflammatory prophylaxis, and 90% obtain imaging prior to discharge, with 78% performing annual echocardiograms. Conclusions This international survey highlights wide variability in RP practices, underscoring the need for standardized training and procedural protocols. These insights may guide new or evolving RP programs, improve access, and ensure durable outcomes by aligning global practices with contemporary evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".