Tricuspid Valve Replacement: Mechanical or Biological Prostheses? A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Tricuspid valve replacement (TVR) is seldom performed in cardiac valve surgery, and there currently are no clinical guidelines as to which type of prostheses is better in tricuspid valve position. This meta-analysis was performed to compare the results of mechanical and biological prostheses for TVR. METHODS: We searched the Pubmed, Cochrane, and Embase clinical trial databases to collect all related studies published from January 1, 2000 to July 31, 2020. A random-effects model was used to evaluate the odds ratios (OR) and its 95% confidence intervals (CI) of time-to-event related effects of the surgical procedures; every study's quality was evaluated by the Newcastle-Ottawa Scale (NOS). RESULTS: A total of 13 retrospective studies, including 1453 patients were analyzed. There were no statistically differences between mechanical and biological prostheses with respect to prosthetic valve failure [OR = 0.84, 95% CI(0.54, 1.28), P = .41], bleeding [OR = 0.84, 95% CI(0.54,1.28), P = .41], reoperation [OR = 1.02, 95% CI(0.58,1.78), P = .95], early mortality [OR = 1.35, 95% CI(0.82,2.25), P = .24] and long-time survival [OR = 1.09, 95% CI(0.70, 1.69), P = .70], but a significant difference can be seen in mechanical prostheses with a higher risk of thrombosis [OR = 0.17, 95% CI(0.05, 0.60), P = .006, I2 = 0%]. CONCLUSIONS: In tricuspid valve position, mechanical valve prostheses have a higher risk of thrombosis than biological prostheses, but no statistical differences between mechanical and biological prostheses with respect to prosthetic valve failure, bleeding, reoperation, early mortality, and long-term survival. The valve disease and patient's age and risk factors are the most important considerations in the decision-making process. The more specific conclusion needs to be further proved by large-sample, multi-center, randomized, double-blind and control trials.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".