Bibliographic record
Abstract
Total arch repair (TAR) has traditionally been performed with a zone 3 distal anastomosis. In recent years, proximalization of the distal anastomosis has been utilized with proposed benefits including an easier distal anastomosis, reduced risk of bleeding, and lower rates of recurrent laryngeal nerve injury. While there have been several comparisons between more proximal distal anastomoses and the traditional zone 3 anastomosis, there have been limited comparisons between proximal anastomoses in zones 0-2. TAR with a frozen elephant trunk (FET) in zone 0 or 1 generally requires debranching of the head vessels proximally or a combination of head vessel bypasses with deployment of the FET across the aortic arch. Select hybrid arch FET devices are available in trifurcated configurations specifically made for a zone 0 distal anastomosis. A zone 2 arch can often be performed with a branched or straight graft and with head vessel anastomoses in the aortic arch. In four studies published to date comparing outcomes following proximal (zone 0/1) or more distal (zone 2) anastomoses, the majority of outcomes, including mortality, stroke, and aortic remodeling, were not significantly different. Rates of major bleeding were more common with a zone 2 distal anastomosis. Proximalization of the distal anastomosis at the time of TAR carries several benefits. Rates of bleeding were lower with a more proximal anastomosis, suggesting improved safety with a zone 0 or 1 anastomosis, without added risk in other metrics.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.512 | 0.312 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".