The Ross procedure versus mechanical aortic valve replacement in young patients: a decision analysis
Bibliographic record
Abstract
OBJECTIVES: Our goal was to determine the range of perioperative mortality rates associated with the Ross procedure that results in a life expectancy similar to that seen with mechanical aortic valve replacement (mAVR) in young patients with aortic valve disease. METHODS: A fully probabilistic Markov microsimulation model with 1000 outer loops and 10 000 inner loops was constructed to compare gain in life expectancy and quality-adjusted life years between the index treatment with the Ross procedure versus mAVR for a theoretical cohort of young patients with aortic valve disease. Inputs for early deaths and late complications (death, stroke, bleeding, reoperation) were obtained from a single-centre study of 208 propensity score matched patients. In the primary analysis, the perioperative mortality rate for the Ross procedure was varied by increments of 0.5% to determine its impact on life expectancy and quality-adjusted life years. A 2-way sensitivity analysis was conducted to determine simultaneously the impact of the Ross reoperation rate and Ross reoperative mortality rate on life expectancy. RESULTS: Life expectancy was improved with the Ross procedure when the perioperative mortality rate with the Ross procedure was <2.5% and was equivalent to mAVR when the mortality rate was 2.5% to 5%. Similarly, when the perioperative mortality rate of the Ross procedure was between 4% and 5.5%, the quality-adjusted life years gained were similar between the Ross procedure and mAVR. Life expectancy was improved when the Ross procedure reoperative mortality rate was <7% at an incidence of Ross reoperations of 18% at 20 years. CONCLUSIONS: Improved life expectancy can be expected with the Ross procedure when the operative mortality rate is less than 2.5%.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".