Does the weekend effect exist for acute type A aortic dissection?—a retrospective case-control study
Bibliographic record
Abstract
Background: The weekend effect refers to the mortality difference for patients admitted/operated on weekends compared to those on weekdays. The study aimed to provide new evidence on the impact of the weekend effect on acute type A aortic dissection (ATAAD). Methods: Primary endpoints were operative mortality, stroke, paraplegia, and continuous renal replacement therapy (CRRT). A meta-analysis of current evidence on the weekend effect was first conducted. Analyses based on single-center data (retrospective, case-control study) were further performed. Results: A total of 18,462 individuals were included in the meta-analysis. The pooled results showed that mortality was not significantly higher for ATAAD on weekends compared to that on weekdays [odds ratio (OR): 1.16, 95% CI: 0.94-1.43]. The single-center cohort included 479 patients, which also showed no significant differences in primary and secondary outcomes between the two groups. The unadjusted OR for weekend group over weekday group was 0.90 (95% CI: 0.40-1.86, P=0.777). The adjusted OR for weekend group was 0.94 (95% CI: 0.41-2.02, P=0.880) controlling for significant preoperative factors, and 0.75 (95% CI: 0.30-1.74, P=0.24) controlling for significant preoperative and operative factors altogether. In PSM matched cohort, the operative mortality was still comparable between the weekend group [10 (7.2%)] and weekday group [9 (6.5%)] (P=1.000). No significant survival difference was observed between the two groups (P=0.970). Conclusions: The weekend effect was not found to be applicable to ATAAD. However, clinicians should be cautious of the weekend effect as it is disease-specific and may vary across healthcare systems.
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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 | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".