[Effect of native aortic valve sparing aortic root reconstruction surgery on short- and long-term prognosis in Marfan syndrome patients:a meta-analysis].
Bibliographic record
Abstract
OBJECTIVE: This meta-analysis was performed to analyze the effect of preserving the native aortic valve on short- and long-term prognosis post aortic root reconstruction surgery for patients with Marfan syndrome. METHODS: Database including Pubmed,Embase, Cochrane library, CNKI, Wanfang,VIP and CBM were searched to collect studies comparing clinical results of valve sparing surgery with composite valve graft surgery for patients with Marfan syndrome. Study quality was assessed by Newcastle-Ottawa Scale and publication bias was assessed by visual inspection of the funnel plot together with Egger test. Clinical outcomes data was extracted from the manuscripts and analyzed with Revman 5.0 supplied by Cochrane collaboration. RESULTS: Seven clinical trials with 690 patients were included. Meta- analysis demonstrated that valve sparing surgery was associated with a lower incidence of re-exploration (RR = 0.51, 95%CI:0.29- 0.90, P < 0.05), thromboembolism (RR = 0.17, 95%CI:0.05-0.57, P < 0.01), endocarditis (RR = 0.31, 95%CI:0.11-0.94, P < 0.05) and significantly lower long-term death rate (RR = 0.37, 95%CI:0.18-0.74, P < 0.01). Reoperation rate was similar between the two groups (RR = 1.07, 95%CI:0.35-3.27, P > 0.05). CONCLUSION: Valve sparing aortic root reconstruction surgery is a superior procedure to composite valve graft surgery in term of improving the short- and long-term prognosis for patients with Marfan syndrome.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.051 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".