Shape of Pulmonary Artery Doppler Flow Profile and Right Ventricular Hemodynamics in Neonates
Bibliographic record
Abstract
OBJECTIVES: To characterize pulmonary artery Doppler flow profile (PAFP) patterns among infants receiving care in neonatal intensive care units and to examine the association of PAFP patterns with pulmonary and right ventricular (RV) hemodynamics. STUDY DESIGN: This is a retrospective study at 2 tertiary intensive care units over 4 years that included neonates who demonstrated a complete tricuspid regurgitation envelope on targeted neonatal echocardiography. Separate personnel reviewed TNEs to characterize PAFP patterns, divide cohort into PAFP groups, and measure quantitative indices of RV hemodynamics (RV systolic pressure, pulmonary artery acceleration time and its ratio with RV ejection time, tricuspid annular plane systolic excursion, and RV output), for intergroup comparisons. RESULTS: We evaluated TNEs from 186 neonates with median gestational age of 28.5 weeks (IQR, 25.9-35.9 weeks). Four distinct PAFP patterns were identified (A) near-isosceles triangle (22%), (B) right-angled triangle (29%), (C) notching (40%), and (D) low peak velocity (<0.4 m/s; 9%). Groups A-C demonstrated a stepwise worsening in all indices of PH, whereas pattern D was associated with lower tricuspid annular plane systolic excursion and RV output. Using common definitions of pulmonary hypertension (PH), pattern A performed best to rule out PH (sensitivity range, 81%-90%) and pattern C for diagnosing PH (specificity range, 63%-78%). CONCLUSIONS: Inspection of PAFP is a simple bedside echocardiography measure that provides clinically meaningful information on underlying RV hemodynamics and may aid in screening and monitoring of patients for PH in intensive care units.
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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 | 0.008 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".