Pulmonary vascular disease and optical coherence tomography imaging in patients with Fontan palliation
Bibliographic record
Abstract
Introduction The Fontan procedure is the palliative procedure of choice for patients with single ventricle physiology. Pulmonary vascular disease (PVD) is an important contributor to Fontan circulatory failure.Areas covered We review the pathophysiology of PVD in patients with Fontan palliation and share our initial experience with optical coherence tomography (OCT) in supplementing standard hemodynamics in characterizing Fontan-associated PVD. In the absence of a sub-pulmonary ventricle, low pulmonary vascular resistance (PVR; ≤2 WU/m2) is required to sustain optimal pulmonary blood flow. PVD is associated with adverse pulmonary artery (PA) remodeling resulting from the non-pulsatile low-shear low-flow circulation. Predisposing factors to PVD include impaired PA growth, endothelial dysfunction, hypercoagulable state, and increased ventricular end-diastolic pressure. OCT parameters that show promise in characterizing Fontan-associated PVD include the PA intima-to-media ratio and wall area ratio (i.e. difference between the whole-vessel area and the luminal area divided by the whole-vessel area).Expert opinion OCT carries potential in characterizing PVD in patients with Fontan palliation. PA remodeling is marked by intimal hyperplasia, with medial regression. Further studies are required to determine the role of OCT in informing management decisions and assessing therapeutic responses.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".