Management of acute type A aortic dissection in the elderly: an analysis from IRAD
Bibliographic record
Abstract
OBJECTIVES: We sought to examine management and outcomes of (Stanford) type A aortic dissection (TAAAD) in patients aged >70 years. METHODS: All patients with TAAAD enrolled in the International Registry of Acute Aortic Dissection database (1996-2018) were studied (n = 5553). Patients were stratified by age and therapeutic strategy. Outcomes for octogenarians were compared with those for septuagenarians. Variables associated with in-hospital mortality were identified by multivariable logistic regression. RESULTS: In-hospital mortality for all patients (all ages) was 19.7% (1167 deaths), 16.1% after surgical intervention vs 52.1% for medical management (P < 0.001). Of the study population, 1281 patients (21.6%) were aged 71-80 years and 475 (8.0%) were >80 years. Fewer octogenarians underwent surgery versus septuagenarians (68.1% vs 85.9%, P < 0.001). Overall mortality was higher for octogenarians versus septuagenarians (32.0% vs 25.6%, P = 0.008); however, surgical mortality was similar (25.1% vs 21.7%, P = 0.205). Postoperative complications were comparable between surgically managed cohorts, although reoperation for bleeding was more common in septuagenarians (8.1% vs 3.2%, P = 0.033). Kaplan-Meier 5-year survival was significantly superior after surgical repair in all age groups, including septuagenarians (57.0% vs 13.7%, P < 0.001) and octogenarians (35.5% vs 22.6%, P < 0.001). CONCLUSIONS: When compared with septuagenarians, a smaller percentage of octogenarians undergo surgical repair for TAAAD, even though postoperative outcomes are similar. Age alone should not preclude consideration for surgery in appropriately selected patients with TAAAD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".