Right Ventricular Morphology in PA/IVS: Integrating Developmental Pathology with Echocardiographic Prognostication
Bibliographic record
Abstract
The management of pulmonary atresia with intact ventricular septum (PA/IVS) or critical pulmonary stenosis (CPS) in neonates continues to evolve, with a growing emphasis on individualized care based on right ventricular (RV) morphology. This commentary discusses and expands upon the recent study by Moras et al., which proposes echocardiographic classification of RV morphology—tripartite versus bipartite—as a predictive tool for post-intervention complications and a guide for intensive care management following transcatheter RV decompression. Integrating developmental cardiac anatomy, the commentary highlights how structural differences in RV segmentation influence physiological responses. Tripartite RVs are often susceptible to left ventricular (LV) dysfunction due to a sudden preload shift following decompression, requiring early inotropic support and delayed feeding strategies. In contrast, bipartite RVs are predisposed to dynamic outflow tract obstruction, often managed with beta-blockers and possible surgical shunting. The discussion also addresses the surgical versus catheter-based treatment decision in light of anatomical constraints such as RV-dependent coronary circulation and monopartite RVs. Additionally, the commentary reviews echocardiographic modalities used to assess RV function both prenatally and postnatally, including TAPSE, tissue Doppler imaging, myocardial performance index, and speckle-tracking echocardiography. It concludes by suggesting that early RV morphotype identification and function monitoring, even in fetal life, may enhance prognostication and therapeutic planning. This commentary advocates for a developmentally informed, phenotype-driven approach to neonatal cardiac care that bridges structural diagnosis with functional management.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| 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".