Long-term Outcomes Following Mechanical or Bioprosthetic Aortic Valve Replacement in Young Women
Bibliographic record
Abstract
BACKGROUND: Studies performed to date reporting outcomes after mechanical or bioprosthetic aortic valve replacement (AVR) have largely neglected the young female population. This study compares long-term outcomes in female patients aged < 50 years undergoing AVR with either a mechanical or bioprosthetic valve. METHODS: In this propensity-matched study, we compared outcomes after mechanical AVR (n = 57) and bioprosthetic AVR (n = 57) between 2004 and 2018. The primary outcome of this study is survival. Secondary outcomes include the rate of reoperation, stroke, myocardial infarction, rehospitalization for heart failure, and incidence of serious adverse events. Outcomes were measured over 15 years, with a median follow-up of 7.8 years. RESULTS: In patients receiving a mechanical AVR vs a bioprosthetic AVR, overall survival at median follow-up was equivalent, at 93%. There is a lower rate of reoperation in patients receiving a mechanical AVR vs a bioprosthetic AVR (1.8% vs 8.8%). The rate of new-onset atrial fibrillation was significantly higher in the mechanical AVR group vs the bioprosthetic AVR group (18.2% vs 7.3%). No significant difference was seen in the rate of serious adverse events. CONCLUSIONS: These results provide contemporary data demonstrating equivalent long-term survival between mechanical and bioprosthetic AVR, with higher rates of new atrial fibrillation after mechanical AVR, and higher rates of reoperation after bioprosthetic AVR. These results suggest that either valve type is safe, and that preoperative assessment and counselling, as well as the follow-up, medical treatment and indications for intervention, must be a collaborative decision-making process between the clinician and the patient.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".