Challenges in clinical identification of right ventricular dysfunction in preterm infants with persistent pulmonary hypertension of the newborn
Bibliographic record
Abstract
BACKGROUND: Right ventricular dysfunction, typically qualitatively diagnosed (Q-RVd) in preterm infants, requires echocardiography which is not always acutely available. We aimed to identify clinical indices of Q-RVd in very preterm infants (gestational age, GA <32 weeks) with persistent pulmonary hypertension of newborn (PPHN) and examine the reliability and validity of Q-RVd. METHODS: Forty-seven infants with mean ± SD GA of 26.8 ± 2.7 weeks who had targeted neonatal echocardiography (TNE) ≤72 h old, during PPHN, were retrospectively studied. Three standard TNE clips were reviewed by two blinded assessors, and infants categorized as Q-RVd if moderate-severe RVd was diagnosed on ≥2 clips. Cardiopulmonary clinical indices at TNE and quantitative RV functional markers were compared between Q-RVd vs. no-RVd groups. Potential quantitative RVd definitions examined by classifying each measurement as "low" or "normal" using published data. Inter-rater agreement for Q-RVd assessed using Kappa statistics. RESULTS: Mean age at TNE was 25.3 ± 20.4 h with Q-RVd diagnosed in 19(40 %) infants. Q-RVd group demonstrated higher peak oxygen requirements (96 ± 9 % vs. 84 ± 16 %, p < 0.01); however, no clinical parameters at TNE differentiated the groups. Quantitative measures were lower in Q-RVd patients, confirming classification validity. Among tested quantitative definitions, low RV stroke volume was associated with lower systolic blood pressure (41±7 vs. 47±9 mmHg, p = 0.02) and higher shock index (4.02±0.80 vs. 3.44±0.72, p = 0.02). Kappa for Q-RVd was 0.55 (95%CI 0.32-0.77). CONCLUSIONS: The non-specific nature of clinical markers of RVd in preterm infants with PPHN necessitates echocardiographic diagnosis of RVd. Studies should examine prognostic relevance of RVd and establish outcome-based quantitative definitions in preterm infants.
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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 | 0.036 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".