Total Arch vs Hemiarch Repair in Acute Type A Aortic Dissection: Systematic Review and Meta-Analysis of Comparative Studies
Bibliographic record
Abstract
Background: We aimed to compare the short- and long-term outcomes of total arch replacement (TAR) vs hemiarch replacement (HAR) in the management of acute type A aortic dissection. Methods: We searched the literature for studies directly comparing TAR to HAR in acute type A aortic dissection. Hazard ratios (HRs) were extracted from digitized Kaplan-Meier curves. Results: A total of 6526 patients were identified, of which 2060 (32%) had received a TAR. A total of 37% of patients were female, and the mean age (standard deviation) of the cohort was 59.8 ± 11.8 years. TAR patients had a higher prevalence of preoperative malperfusion (34% vs 26%). The TAR group had higher odds of 30-day mortality (4404 patients; odds ratio [OR] 1.79, 95% confidence interval [CI] 1.29-2.49), renal failure requiring dialysis (3475 patients; OR 1.34, 95% CI 1.02-1.76), and a trend toward higher rates of stroke (3292 patients; OR 1.49, 95% CI 0.93-2.39). No significant differences were observed in prevalence of permanent spinal cord injury, visceral ischemia, or reoperation for bleeding. The TAR group had a non-statistically significant increase in long-term mortality (4408 patients; HR 1.25, 95% CI 0.99-1.57), but showed a trend toward improved freedom from long-term aortic reoperation (1359 patients; HR 0.53; 95% CI 0.18-1.59). In a subgroup analysis, the hazard ratio of long-term mortality favoured TAR in only the subgroup of studies in which the difference in malperfusion was > 10% between groups. Conclusions: TAR could be associated with improved freedom from long-term aortic reoperation but with potentially increased perioperative risks. We recommend a tailored surgical approach.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".