Imaging of atrial septal defects: echocardiography and CT correlation
Bibliographic record
Abstract
Adult patients with atrial septal defects (ASDs) have variable clinical presentations that can range from dyspnoea on exertion to cerebral vascular accidents from paradoxical embolism. Currently echocardiography is the mainstay in the diagnosis and follow-up of patients with ASDs. As CT technology advances and low radiation techniques improve, cardiac CT is becoming a desirable method to evaluate patients with ASDs when echocardiographic evaluation is limited. Correct diagnosis and appropriate management of patients with patent foramen ovales (PFOs) and ASDs relies on an understanding of the embryologic development patterns that resulted in the malformation and associated anomalies. In this review, we illustrate the development of the interatrial septum and the foramen ovale. We discuss the diagnosis of PFOs and ASDs by echocardiography and highlight the incremental benefit of CT to further elucidate defect morphology, associated anomalies, and anatomy post-repair. The primary atrium starts as a common cavity.1 Starting at 5 weeks of gestation, the primordial single atrium begins dividing into right and left sides by formation and fusion of two septa: the septum primum and septum secundum (figure 1). Early in the fifth week of gestation the septum primum begins to form near the centre of the roof of the common atrium, growing downward to the endocardial cushions, and partially dividing the common atrium into right and left counterparts (figure 1, A-1 and A-2). The gap between the septum primum and endocardial cushions is known as the ostium primum. Before the septum primum and endocardial cushions fuse, perforations develop within the cephalic portion of the septum primum through apoptosis, creating a large window known as the ostium secundum. At the end of the sixth week the caudal free edge of the septum primum reaches the atrioventricular cushions and fuses with them, closing the ostium primum (figure 1, B-1 and …
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".