Efficacy and safety of single-branched stent graft in the treatment of type B aortic dissection: a meta-analysis of cohort studies
Bibliographic record
Abstract
BACKGROUND: Thoracic aortic endovascular repair (TEVAR) is the most commonly employed method for treating type B aortic dissection (TBAD). One of the primary challenges in TEVAR is the reconstruction of the left subclavian artery (LSA). Various revascularization strategies have been utilized, including branch stent techniques, fenestration techniques, chimney techniques, and hybrid techniques. Among these, the single-branched stent graft (SBSG) has emerged as one of the most promising methods. This study employs a meta-analysis to evaluate the efficacy and safety of SBSG in treating TBAD, thereby providing robust evidence to guide clinical practice. METHODS: Published literatures on the treatment of TBAD with SBSG were collected from CNKI, Wanfang Data, VIP, PubMed, Embase, Web of Science and Cochrane Library. The search period ranged from the inception of each database to December 1, 2024. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. Meta-analysis was conducted using RevMan 5.3 software. RESULTS: A total of eight studies involving 660 participants were included in this meta-analysis. The results demonstrated that, compared to other surgical methods, SBSG significantly reduced the perioperative neurological complication rate (OR = 0.23, 95%CI(0.07, 0.76), P = 0.02), type I endoleak rate (OR = 0.30, 95%CI(0.15, 0.61), P = 0.001), and left upper limb ischemia rate (OR = 0.06, 95%CI(0.01, 0.49), P = 0.008). Additionally, SBSG was associated with a shorter operation time (SMD = 0.59, 95%CI(0.04, 1.14), P = 0.04). However, no significant differences were observed between SBSG and other surgical methods in terms of technique success rate (OR = 1.51, 95%CI(0.55, 4.14), P = 0.42), hospital length of stay (OR = 1.51, 95%CI(0.55, 4.14), P = 0.42), aortic false lumen thrombosis rate (OR = 1.30, 95%CI(0.55, 3.07), P = 0.56), pulmonary infection rate (OR = 0.50, 95%CI(0.16, 1.58), P = 0.24), and 30-day postoperative mortality (OR = 0.41, 95%CI(0.12, 1.35), P = 0.41). CONCLUSION: SBSG demonstrates safety and efficacy in the treatment of TBAD by significantly reducing the perioperative neurological complexity rate, type I leakage rate, and left upper limb ischemia rate, while also decreasing operative time.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.055 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".