Cause of Death Following Surgery for Acute Type A Dissection
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Surgery confers the best chance of survival following acute Type A dissection (ATAD), yet perioperative mortality remains high. Although perioperative risk factors for mortality have been described, information on the actual causes of death is sparse. In this study, we aimed to characterize the inciting events causing death during surgical repair of ATAD. METHODS: Nine centers participated in the study. We included all patients who died following surgical repair for ATAD between January 2007 and December 2013. An aortic surgeon at each site determined the primary cause of death from seven predetermined categories: cardiac, stroke, hemorrhage, other organ ischemia (peripheral, renal, or visceral), multiorgan failure, sepsis, or other causes. Additional characteristics and variables were analyzed to delineate potential modifiable factors for mortality. RESULTS: Of the 692 surgeries for ATAD, there were 123 deaths (17.8% mortality rate). Mean age at death was 66 years. Events contributing to death were: cardiac (25%), stroke (22%), hemorrhage (21%), multiorgan failure (12%), other organ ischemia (11%), sepsis (4%), and other causes (5%). Neurologic injury at presentation was a predictor of stroke as the inciting cause of death (p = 0.04). Peripheral, renal, or visceral ischemia at presentation was highly predictive of death due to these presenting ischemic conditions (p = 0.004). We found no associations between cardiogenic shock, tamponade, or cardiopulmonary bypass duration and cardiac death. CONCLUSION: Operative mortality for ATAD remains high in Canada. Nearly 70% of deaths arise from cardiac failure, stroke, or hemorrhage. Therefore, novel surgical, hybrid, and endovascular strategies should target these three areas.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it