Assessment of ductal blood flow in newborns with obstructive left heart lesions by cardiovascular magnetic resonance
Bibliographic record
Abstract
BACKGROUND: Newborns with obstructive left heart lesions often depend on a patent ductus arteriosus to sustain the systemic circulation. Our aims were to validate the direct measurement of ductal flow, and to characterize the magnitude, determinants and hemodynamic effects of patent ductus arteriosus in newborns with obstructive left heart lesions by cardiovascular magnetic resonance (CMR). METHODS: In this retrospective study, the CMR and clinical information of newborns with obstructive left heart lesions were reviewed. The feasibility and validity of measuring ductal flow and the correlations between ductal flow and ventricular volumes, ascending aortic flow, post-ductal oxygen saturation and Qp:Qs were assessed. RESULTS: The CMR examinations of 32 newborns were included. It was possible to measure the ductal flow in all of them, with moderate-to-good agreement between measured and calculated ductal flow volume. The flow was bidirectional in all patients, with a net right-to-left shunt in 72%. Net ductal flow correlated inversely with ascending aortic flow (Rho -0.63; p 0.0002), post-ductal oxygen saturation (Rho -0.58; p 0.0004), Qp:Qs (Rho -0.43; p 0.02), and with left ventricular end-diastolic volume index (Rho -0.38; p 0.04). There was no correlation with the diameter of the ductus. The contribution of ductus flow to the systemic circulation correlated with the left ventricular end-diastolic volume index (Rho -0.47; p 0.02). CONCLUSIONS: Direct measurement of ductal flow in newborns with obstructive left heart lesions is feasible. From these measurements, we were able to demonstrate that patients with smaller left ventricles and lower ascending aortic flow have a greater contribution of ductal flow to the systemic circulation. The size of the ductus arteriosus does not predict net ductal flow. Phase-contrast CMR can be an adjunct method for the assessment of the physiology for very ill neonate patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".