<i>Retracted:</i> Experience of cases with inhaled nitric oxide and therapeutic hypothermia
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
BACKGROUND: Neonates with hypoxic-ischemic encephalopathy (HIE) on therapeutic hypothermia (TH) therapy may show persistent pulmonary hypertension of the newborn (PPHN). In Japan, the reported mortality rate is lower than in the US, possibly due to treatment differences of newborns with moderate to severe HIE and PPHN. This study aimed to determine the feasibility and long-term outcomes of inhaled nitric oxide (iNO) and TH therapy in newborns with moderate to severe HIE and PPHN. METHODS: This was a retrospective review of neonates with moderate to severe HIE that were treated with TH from 2008 to 2017 at a large medical center in Japan. We documented their long-term neurological prognosis, measuring their developmental and Gross Motor Function Classification System level at 18 months old. RESULTS: A total of 37 neonates with moderate to severe HIE underwent TH therapy and six of them were started with iNO therapy for PPHN. iNO with TH was safely administered to all six newborns with moderate to severe HIE with PPHN. In two neonates TH was discontinued because of intraventricular hemorrhage (IVH) and severe hypotension. Neurological outcomes were similar in newborns who were treated with iNO and TH and those who were treated with TH alone. CONCLUSION: These initial findings suggest that monitoring hematological and cardiovascular status is important with iNO for severe asphyxia in infants with PPHN. Safer and more feasible protocols are needed for when iNO and TH therapy are administered together.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".