Transcatheter Closure vs Surgical Closure of Ventricular Septal Defect in China: A Meta-Analysis
Bibliographic record
Abstract
Objective: To compare the curative effect, safety and medical cost of transcatheter closure and surgical closure in ventricular septal defect in China，so as to provide references for treatment plans of ventricular septal defect in clinic medicine. Methods: Chinese literature databases such as CBM, VIP, CNKI, Wan Fang and English literature databases such as PubMed, Ovid and EBSCO were searched from the date of their establishment to June 2015 for collecting the related articles, the collected articles were screened, extracted, evaluated, and analyzed by using Revman5. 3 software. Results: 23 articles (16 Chinese articles, 7 English articles) met the inclusion criteria，transcatheter closure (TC) group included 2801 cases，surgical closure (SC) group included 3,086 cases. Meta-analysis results showed as following：(a) operation success rate：TC group was lower than SC group (RR=0.98, 95% CI=0.96~0.99, P = 0.008)；(b) operation complication rate：TC group was lower than SC group (RR=0.62, 95% CI=0.46~0.84, P=0.002)；(c) operation immediate residual shunt rate：TC group was lower than SC group (RR=0.69, 95% CI = 0.51~ 0.95, P=0.02)；(d) operation time：TC group was shorter than SC group (SMD= -2.87, 95% CI = -3.60 ~ -2.13, P<0.00001)；(e) length of hospital stay：TC group was shorter than SC group (SMD= -1.55, 95% CI=-2.14 ~ -0.95, P<0.00001)；(6) hospitalization expenses：TC group was higher than SC group (SMD=1.02, 95% CI=0.12~1.93, P=0.03). Conclusion: TC is lower than SC in operation success rate，operation complication rate and operation immediate residual shunt rate; and TC is shorter than SC in operation time and length of hospital stay；but TC is higher than SC in the hospitalization expenses. Thus, transcatheter closure can be used as an alternative to surgical treatment in the range of indication.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.035 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".