Anomalous aortic origin of a coronary artery: learning from the past to make advances in the future
Bibliographic record
Abstract
PURPOSE OF REVIEW: To review anomalous aortic origin of a coronary artery (AAOCA) anatomy, prevalence, mechanism and risk of ischemia, presentation, evaluation, management, and future directions. RECENT FINDINGS: Although most anatomic variants of AAOCA are benign, a small number are associated with increased risk of sudden death. A complete evaluation, including the use of advanced noninvasive imaging and provocative testing should be performed on nearly every patient with AAOCA. On the basis of recent studies, the ischemic risk appears to be greatest with a left anomalous coronary artery but an anomalous right coronary artery is not benign. Other risk factors include: a left anomalous coronary with an intramural course, high take-off, or slit-like orifice, and a right anomalous coronary with a longer intramural course. Exercise restriction is rarely recommended. Management primarily consists of nonoperative care, or surgical repair in those who are symptomatic or who have high-risk variants. Surgery itself continues to evolve; however, it is not benign, with a higher than expected chance of morbidity. SUMMARY: Advances have been made over the past decade regarding management of patients with AAOCA; however, the mechanism of ischemia and ability to predict risk is still incompletely understood. Management decisions should be based on anatomy, results of investigations, and shared decision-making with patients and their families. Surgery may be recommended for those at higher risk and should be done at centers experienced in AAOCA surgery. Future research should be collaborative in order to share experiences and insights to help advance our understanding of risk and ultimately to improve patient management.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".