Is Partially Thrombosed False Lumen Really a Predictor for Adverse Events in Uncomplicated Type B Aortic Dissection: A Systematic Review and Meta-Analysis?
Bibliographic record
Abstract
Objective: This meta-analysis and systematic review investigated whether partial thrombosed false lumen was a predictor for adverse events in uncomplicated Type B aortic dissection (TBAD). Methods: We performed the current systematic review of the medical literature according to the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The Newcastle-Ottawa Scale was used to evaluate the quality of individual studies. Search terms based on the MEDLINE database included “type B aortic dissection,” “false lumen” and “thrombosis.” The primary outcomes included mortality, intervention, and aortic growth. Results: Six studies were included in this systematic review, with a total number of 692 patients, including 197 patency (28.5%), 214 partial thrombosis (30.9%), and 281 complete thrombosis (40.6%). Due to the insufficient data for quantitative analysis, we only conducted a scoping review for mortality and intervention. For aortic growth, we conducted a meta-analysis based on Standardized Mean Difference (SMD). The SMD of PT vs. P by random effect model was −0.05 (random effect model) [95% confidence interval (CI), −0.39 to 0.29]. The 95% CI crossed with the null line of 0, indicating no significant difference. The SMD was 0.37 (fixed effects model) (95% CI, 0.03–0.71) and 0.70 (fixed effects model) (95% CI, 0.37–1.04) for PT vs. CT, and P vs. CT, respectively. Conclusions: Current researches on partial thrombosis of TBAD are inconsistent. Partial thrombosis is not associated with a faster aortic growth rate. Until more solid evidence is available, we do not recommend partial thrombosis as a surgical indication or high-risk profile for TBAD. Systematic Review Registration: Unique Identifier: CRD42019121912 .
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.006 |
| Bibliometrics | 0.001 | 0.003 |
| 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".