Abstract 15834: The Utility of Intra-Operative Coronary Doppler Profiles in Predicting Early and Late Major Adverse Cardiovascular Events After Arterial Switch Operation
Bibliographic record
Abstract
Introduction: Coronary artery transfer is the most important technical point in the arterial switch operation (ASO). Intra-operative echocardiography identifies aberrancies in coronary artery Doppler profiles guiding immediate surgical management. Objective: We sought to determine whether abnormal intra-operative coronary artery Doppler profiles are associated with major adverse cardiovascular events (MACE; death, transplantation, heart failure, arrhythmia, need for coronary re-intervention) following ASO at 30-days, 5 & 10 years. Methods: Single centre retrospective review of patients undergoing ASO between 2009 - 2022. Transesophageal or epicardial intra-operative coronary artery Doppler profiles were analysed. Patient variables were abstracted from records. Freedom from MACE was estimated using Kaplan-Meier methods. Results: 347 patients were included. Coronary anatomy was usual (1LCx2R) in 237 (68%), single sinus ostia in 24 (7%), intramural in 14 (4 %). Overall 30-day MACE was 11.2% [8.3%, 15.1%], increasing to 25% [12.1, 47.4%] with single sinus ostia & 35.7% [16.7%, 65.7%] with intramural. Overall 5 & 10-year MACE was 16.5% [12.9, 20.9%], 33.8% [18.5%, 56.4%] with single sinus ostia & 50.0% [27.8%, 77.1%] with intramural. A higher probability of MACE was seen with coronary Doppler reverse flow, absence of normal pattern (Table 1) and a higher peak velocity (Figure 1). Overall 30-day mortality was 1.2% [95%CI 0.4%, 3.0%] and at 5 & 10 years was 6.5% [4.3%, 9.8%]. Conclusions: Intra-operative abnormal coronary artery Doppler profiles during ASO may identify those at highest risk of early and late adverse events, guiding follow-up surveillance strategies.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| 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".