Abstract 20283: Two-Dimensional Echocardiography Incorrectly Identifies Tricuspid Regurgitation Jet Location Compared to Three-Dimensional Echocardiography in Pre-Operative Assessment of Tricuspid Valve Repair in Hypoplastic Left Heart Syndrome
Bibliographic record
Abstract
Background: A recent study using two-dimensional echocardiogram (2DE) reported a predominance of antero-septal commissural regurgitation in patients (70%) undergoing tricuspid valve repair (TVR) in hypoplastic left heart syndrome (HLHS). Three-dimensional echocardiography (3DE) studies on assessment of TV morphology reports a high incidence of error in the identification of TV leaflets in conventional 2DE planes. This study aims to assess the pre-operative 2DE assessment of TR jet location compared to the reference standard of 3DE color datasets in HLHS. Methods: Twenty-five HLHS patients requiring TVR for TR between 2005 and 2015 were assessed using 2DE and 3DE to assess TR grade, 3DE vena contracta (VC) area, TV annulus diameter (indexed to body surface area, iTV) and primary TR jet location. The 2DE observer was blinded to the findings on 3DE. We compared the 2DE findings with 3DE using t-test and Pearson correlation. Surgical notes were reviewed for details of procedures performed. Results: Indexed 2DE iTV was no different to 3DE (61mm/m 2 ± 4 vs. 56mm/m 2 ± 4, p=0.34). 2DE qualitative TR grade correlated with 3DE VC area (r=0.69, p Conclusions: 2DE was accurate in the assessment of the degree of TR and TV annular size, but in most patients incorrectly identified the primary regurgitation location in the antero-septal region instead of other location. This may have implications for planning of the primary surgical procedure in HLHS TV repair based on 2DE findings.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".