An Analysis of Time to Improvement in Oxygenation in Japanese Preterm and Late Preterm or Term Neonates With Hypoxic Respiratory Failure and Pulmonary Hypertension
Bibliographic record
Abstract
PURPOSE: We analyzed data from an ongoing registry to determine time to improvement in oxygenation in preterm and late preterm or term neonates with hypoxic respiratory failure and pulmonary hypertension receiving inhaled nitric oxide (iNO) in Japan. METHODS: Registry neonates received iNO ≤7 days after birth (February 26, 2010, to October 9, 2012). Efficacy and safety profile data were collected up to 96 h after iNO initiation and, if necessary, every 24 h thereafter and before iNO discontinuation. Patients were stratified by gestational age (GA), oxygenation index (OI), and shunt direction at baseline. FINDINGS: Data were evaluated for 1106 neonates (431 with a GA <34 weeks and 675 with a GA of ≥34 weeks). Sixty percent of patients had improved OI; rates were similar for those with GAs of <34 versus ≥34 weeks (61% vs 59%). Overall, mean time to improvement was 11.4 h and tended to be shorter in the groups with a GA <34 weeks versus ≥34 weeks (9.2 vs 12.9 h). Thirty percent of responding neonates required >1 h to achieve improvement in oxygenation. Neonates with higher baseline OI had the greatest decrease in OI during the first hour of treatment. The mortality rate was higher among iNO-treated patients with a baseline OI ≥25 versus those with OI ≥15 to <25 (25% vs 12%; P = 0.0073). IMPLICATIONS: iNO treatment provided acute, sustained improvement in oxygenation in neonates with GAs <34 and ≥34 weeks; 70% of patients had improvement within 1 h, but the remaining 30% took >1 h to respond. Initiation of iNO at lower OIs was associated with reduced mortality compared with higher OI.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".