Abstract 2340: Should Real-time Three-dimensional Echocardiography Become The Preoperative Standard For The Evaluation Of The Mechanisms Of Atrioventricular Valve Regurgitation In The Patient With Congenital Heart Disease?
Bibliographic record
Abstract
Objective: The purpose of this study was to determine whether Real-time three-dimensional echocardiography (RT3D) is superior to two-dimensional echocardiography (2D) in determining mechanisms and site(s) of atrioventricular valve (AV valve) regurgitation in congenital heart disease. Background: Data is lacking on the utility of RT3D echo in congenital abnormalities of the AV valves. Methods: Between May 2006 and April 2007, 35 cases were prospectively studied prior to AV valve repair (20 left and 15 right) by 2D transthoracic (2DTTE), 2D transesophageal (2DTEE) and RT3D (Philips matrix array X 3–1 and X 7–2). Thirty one had significant and 4 mild regurgitation. Ages ranged from 24 days to 30 years (mean 13.8 years), weight 2.2 to 42kg (mean 26.1Kg). The 2DTTE and TEE were reviewed by a blinded observer. The 3D data were analyzed by a separate observer. In 28 patients surgical findings and regurgitation from saline testing were recorded by digital video and later analyzed by an experienced cardiac surgeon. The remaining 7 had a detailed description of the valve morphology documented immediately after surgery. Surgical findings were used as the gold standard for the assessment of structural abnormalities, with RT3D for the evaluation of regurgitation. Results: See table for structural abnormalities. For both the left and right AV valve, saline testing provided a poorer correlation with RT3D color Doppler jet location, in particular for regurgitant jets from the commmissures (p < 0.01). Conclusion: Transthoracic RT3D provides new and superior information as to the mechanisms and site(s) of AV valve failure in congenital heart disease. Concordance between 2D TTE, 2D TEE and 3D TTE compared to surgical 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".