Abstract 15467: Bi-Leaflet Tricuspid Valve in Children With Hypoplastic Left Heart Syndrome is Rarely Incompetent, While Bi-Leaflet With a Cleft Results in Tricuspid Valve Regurgitation
Bibliographic record
Abstract
Introduction: Tricuspid valve (TV) regurgitation in Hypoplastic Left Heart Syndrome (HLHS) increases the risk of death/transplantation by 2 to 3 times. Abnormalities in TV annular shape, leaflets expansion and subvalve apparatus position, have been associated in HLHS with subsequent tricuspid regurgitation (TR). As TV morphological variation is increasingly recognized, its role on tricuspid valve function remains unknown. This study aims to describe and examine the relationship between the TV leaflet morphologies in HLHS and its association with TV repair. Methods: Cross sectional study of selected 38 “classic” HLHS patients from a prospective longitudinal 3DE study of HLHS TV. TV leaflet morphology from 3DE datasets were reviewed (S.Z and N.S.K) blinded to TR grade. We adapted a previously proposed nomenclature to describe the TV leaflets (Figure 1). Using the Chi-squared test, we compared the frequencies of TV morphological types of HLHS with mild or less TR (n = 23) vs. HLHS who had TV repair (n = 15) at latest follow up. Results: Incidence of TV morphological type is summarized in Figure 2. Bi-leaflet TV was the second most common, followed by bi-leaflet with a cleft. When comparing HLHS with mild or less TR vs. HLHS with TVR, only 1 of 9 bi-leaflet TV had subsequent TVR, while all bi-leaflet TV with a cleft, underwent TVR (p<0.05). Conclusion: HLHS has considerable TV leaflet variations with bi-leaflet TV being the second most common variation. While bi-leaflet TV is more likely to be found in a competent TV, those with a bi-leaflet TV with a cleft, all required TVR. Bi-leaflet TV with a cleft, warrants further study to assess its relationship and relative role with TVR.
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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 | 0.000 | 0.001 |
| 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) | 0.005 | 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".