Tissue versus mechanical mitral valve replacement in patients aged 50–70: a propensity-matched analysis
Bibliographic record
Abstract
OBJECTIVES: There remains debate over the optimal mitral valve replacement (MVR) option for patients aged 50-70 years. The objective of this study was to retrospectively compare the long-term outcomes of mechanical and bioprosthetic MVR in this patient population. METHODS: Data from patients undergoing MVR between 2004 and 2018 were retrospectively reviewed. The primary outcome was all-cause mortality. Secondary outcomes included perioperative and late morbidity. RESULTS: Two hundred and eight-six propensity-matched patients (n = 143 mechanical; n = 143 bioprosthetic) aged 50-70 years were included in the final analysis. Maximum follow-up was 15.8 years. There was no significant difference in all-cause mortality between the groups at 30 days, 1 year, 5 years, 10 years, and at the longest follow-up. Patients who underwent mechanical MVR experienced significantly lower rates of postoperative atrial fibrillation (P = 0.001). There were no significant differences in rates of sepsis, acute kidney injury, superficial and deep sternal wound infection, mediastinal bleeding, and permanent pacemaker implantation. At the longest follow-up, there were no differences in myocardial infarction, stroke, heart failure or overall rehospitalization. At the same time point, there was an increased rate of MVR in patients receiving a bioprosthetic valve (P = 0.015). CONCLUSIONS: Survival following mechanical and bioprosthetic MVR in patients 50-70 years of age is similar to up to 15 years of follow-up. Bioprosthetic MVR is associated with an increased risk of repeat MVR. Mechanical MVR is not associated with an increased risk of stroke. Valve selection in this patient population requires diligent consideration of structural valve deterioration and subsequent reoperation risk as well as bleeding and thromboembolic risk.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| 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".