Bibliographic record
Abstract
Blunt traumatic thoracic aortic injury (BTTAI) is a lethal injury associated with a prehospital mortality of 80% to 90%. Patients arriving in the emergency room and considered appropriate to undergo emergency open surgical repair still have a mortality rate of 15% to 30% because of severe associated injuries. Conventional open surgical repair requires a left thoracotomy, single lung ventilation, aortic-cross clamping and unclamping, with or without the adjunct use of partial or full cardiopulmonary bypass and systemic heparinization. All this leads to significant physiological stress and surgical trauma resulting in perioperative complications such as major blood loss, coagulopathy, myocardial infarction, stroke, respiratory failure, renal failure, bowel infarction, and paraplegia. Despite advances in anesthesia, critical care medicine, and surgical techniques, a recent meta-analysis showed no definite improvement in operative mortality over the past decade, following open surgical repair in patients with BTTAI. Endovascular repair of BTTAI does not require a thoracotomy, single lung ventilation, aorticcross clamping and unclamping, or systemic heparinization. As a result, endovascular repair of BTTAI has emerged as an effective, minimally invasive treatment alternative, especially in patients with severe concomitant injuries, which may be prohibitive to open surgical repair. Recent published studies have shown that endovascular repair of BTTAI is associated with lower morbidity, mortality, stroke, and paraplegia/paraparesis rates, when compared with open surgical repair of BTTAI.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".