The left ventricle in atrial septal defect: Looking through 3D glasses
Bibliographic record
Abstract
Objectives To identify left ventricular (LV) dyssynchrony and associated factors in atrial septal defect (ASD) patients, using real time three‐dimensional echocardiogram (RT3DE). Background Left ventricular dysfunction has been observed in ASD. Few studies have utilized RT3DE to assess LV wall‐motion abnormality in ASD. Methods Patients aged ≥1 year with ASD, with or without partial anomalous pulmonary venous drainage (PAPVD), were included over 1 year. Additional cardiac defects or abnormalities independently affecting LV function were excluded. 2DE and RT3DE‐derived LV function data were recorded. Student's t test and Pearson's correlation were used for analysis. Results Of 104 patients (69 females) aged 1–57 years, ostium secundum ASD was present in 97 and sinus venosus ASD in 7. Maximum excursion increased significantly with age, weight, and body surface area (P < 0.001). Majority of children (58%) aged 3–5 years showed no delay in segmental excursion. Lateral wall excursional delay was greater beyond 5 years or with weight > 15 kg (42% as compared to 20% in <15 kg). In patients weighing < 15 kg, time to minimum systolic volume (Tmsv 16‐SD) was higher with PAPVD and with indexed defect size > 40 mm/m2, though not statistically significant. As compared to EF estimation by 2DE, EF derived using RT3DE was significantly lower (P < 0.001). Conclusion Left ventricular dyssynchrony is least between 3 and 5 years. Beyond 5 years, delayed lateral wall excursion is seen. With an indexed defect size exceeding 40 mm/m2, and in the presence of PAPVD, time to minimum systolic volume is higher.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".