Abstract 14692: Evaluation of Subaortic Right Ventricular Function in ccTGA: How Do Echocardiography Parameters Compare to CMR?
Bibliographic record
Abstract
Background: Subaortic right ventricular (RV) functional assessment in patients with congenitally corrected transposition of the great arteries (ccTGA) is important for both long-term outcome and as an indication for tricuspid valve replacement. Cardiac magnetic resonance (CMR) imaging is considered the reference standard for assessment of subaortic RV systolic function. However, two-dimensional echocardiography (2DE) remains the most frequently used imaging modality in clinical practice. Objective: To compare 2DE and CMR parameters of RV function in patients with ccTGA. Methods: We identified adults (≥18) with the diagnosis of ccTGA who underwent consecutive CMR and 2DE imaging within 6 months between 2005 and 2015. Patients with tricuspid valve replacement or pacemaker were excluded. 2DE images were reviewed and the following RV parameters re-measured by a single observer: fractional area shortening (FAC), tricuspid annular plane systolic excursion (TAPSE), tricuspid annular systolic velocity (Ts’), the rate of systolic RV pressure increase (dp/dt) and myocardial acceleration during isovolumic contraction (IVA). RVEF as measured by CMR was recorded. Results: There were 82 matched 2DE and CMR studies in 42 ccTGA patients (50% male). Median age at 2DE was 33.1 years (IQR = 22.7- 48.2 year). Pearson correlation analysis demonstrated a weak correlation between FAC and RVEF (r 2 =0.143, p=0.0005). Other 2DE parameters failed to show any correlation with RVEF (Figure 1). Conclusion: In general, 2DE parameters for the assessment of subaortic RV systolic function correlate poorly with CMR measured RVEF in patients with ccTGA. This is important information for selection and interpretation of various modalities in the long-term follow-up of this patient population.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".