Aortic Valve Intervention During Aortic Root Surgery in Children: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Pediatric aortic root dilatation is a life-threatening condition that lacks guidelines for surgical management. We aimed to analyze the data on aortic valve interventions during root surgery to guide decision-making. METHODS: A search was performed of MEDLINE, Embase, CENTRAL, ClinicalTrials.gov, and WHO ICTRP. Citations were screened in duplicate and independently to identify randomized controlled trials, cohorts, and case series involving populations aged 0 to 18 years, who received valve-sparing and valve-replacing aortic root surgeries between 1999 and 2019. Outcomes considered included mortality (perioperative, one year, five year), reintervention rates. RESULTS: After duplicate removal, 689 citations were screened through abstract and full text review, identifying five eligible studies. All five were observational studies evaluating valve-sparing procedures. There were 81 patients with a mean study age range of 9.9 to 13.9 years. Both reimplantation (74%) and remodeling (26%) subtypes were done. Range of mean duration of follow-up was 1.2 to 4.4 years. There was no mortality reported until the one-year follow-up period. The long-term mortality rate was calculated as 0.02 per patient-year (95% CI: 0.01-0.05). The long-term reintervention rate was 0.08 per patient-year (95% CI: 0.05-0.13). CONCLUSIONS: There is limited experience on aortic valve intervention during aortic root surgery in children. Single-arm studies on valve-sparing surgeries show excellent survival up to one year. Mortality and reintervention rates increase in the longer term. The small sample size and lack of controlled studies do not allow for direct comparisons between procedure types.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".