Anatomical variation in the branching pattern of the aortic arch: a literature review
Bibliographic record
Abstract
BACKGROUND: Many anatomical variations of the branching pattern of the aortic arch have been documented in the literature. These find their origin in alterations to the embryological development of the arch and have significant implications for surgical and radiological interventions. METHODS: Embase and Medline database searches were carried out in June 2021 and identified 1197 articles, of which 24 were considered eligible. RESULTS: Twenty-eight variations were found. The prevalence of the six main variations found is as follows: normal configuration (61.2-92.59%); bovine arch type 1 (4.95-31.2%); bovine arch type 2 (0.04-24%); origin of left vertebral artery (0.17-15.3%); aberrant right subclavian artery (0.08-3.33%); thyroid ima artery (0.08-2%). Concomitant variations present in conjunction with these variations are also documented, as were other variations which could not be classified into these six groups. CONCLUSIONS: Anatomical variations in the branching pattern of the aortic arch are present in over one-third of individuals in some populations. These are important pre- and intra-operatively during thoracic, neck and thyroid surgery. A greater effort should be employed to construct an official classification to facilitate greater understanding among clinicians.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".