Dynamic morphology of the secundum atrial septal defect evaluated by three dimensional transoesophageal echocardiography
Bibliographic record
Abstract
OBJECTIVE: To define by three dimensional echocardiography the pattern and potential determinants of contraction of a secundum atrial septal defect through the cardiac cycle, and to evaluate the possibility of using cross sectional transthoracic and transoesophageal imaging to assess the dynamic nature of the defect. DESIGN: Three dimensional echocardiography was performed using a multiplane transoesophageal probe on 50 patients with a secundum atrial septal defect (median age 9.8 years). Nine patients were excluded because of poor images or morphological features that precluded defect measurement. In 41 cases, defect area, long and short axis length, and distance of the attenuated anterior rim were measured in their largest and smallest dimensions. RESULTS: Defect area changed significantly through the cardiac cycle (mean change 61%, p < 0.0001; range 17% to 86%). The defect contracted symmetrically and was not related to patient age, defect size, heart rate, Qp/Qs ratio, the presence of an aneurysmal atrial septum, or attenuated anterior rim. In all cases with an attenuated anterior rim (n = 13), the length of the rim significantly decreased (p = 0. 001) during atrial systole. Dynamic changes measured by either transthoracic or transoesophageal cross sectional images did not correlate with those obtained by three dimensional imaging. CONCLUSIONS: Three dimensional echocardiography shows dynamic features of defects in the atrial septum. This information may lead to an improved understanding of the pathophysiology of atrial shunting.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".