Aortic valve repair for insufficiency in older children offers unpredictable durability that may not be advantageous over a primary Ross operation
Bibliographic record
Abstract
OBJECTIVES: To evaluate the durability of aortic valve (AoV) repair relative to other strategies for children with significant aortic insufficiency (AI). METHODS: From 2001 to 2012, 90 children with greater than or equal to moderate AI underwent surgery. Resulting procedures were classified according to final operative outcome: AoV repair (repair; n = 46, 51%), Ross procedure (Ross; n = 21, 23%) or replacement with mechanical or tissue prosthesis [aortic valve replacement (AVR); n = 23, 26%]. Repeated measures (n = 1081 echocardiograms) mixed-model analysis and parametric multiphase risk-adjusted hazard analysis were used to evaluate haemodynamic parameters and durability of operations. RESULTS: Mean age at operation was similar for repair and Ross groups, but slightly higher for the AVR group (10.6, 11 and 13.2, respectively; P = 0.04). Baseline annular dimensions were similar among groups. Of 46 repairs, 85% involved pericardial leaflet extensions (commonly with leaflet shaving and/or commisuroplasty). The remaining repairs were commissuroplasties. On multivariable analysis, repair was associated with increased early (∼1-2 years) AI and increased outflow tract peak pressure gradients relative to Ross and AVR procedures. On univariate analysis, repairs tended to have a larger annulus size compared with Ross or AVR; however, this was not significant on multivariable analysis. There were 25 reinterventions (surgical reoperation = 16; transcatheter intervention = 9) for 22 children. Freedom from surgical reoperation was 64, 100 and 51% at 6 years for repairs, Ross and AVR, respectively (P = 0.05); however, three of five reoperations after AVR were for failed bioprosthetic devices. The freedom from reintervention was not significantly influenced by the type of AoV operation (P = 0.43). CONCLUSIONS: Durability of aortic valve repair for children is limited by recurrence of AI and/or stenosis, often within the first few years. After repair, reoperation should be anticipated within ∼7 years.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".