Recommended Guideline for Uniform Reporting of Neonatal Resuscitation: The Neonatal Utstein Style
Bibliographic record
Abstract
Clinical research on neonatal resuscitation has accelerated over recent decades. However, an important methodologic limitation is that there are no standardized definitions or reporting guidelines for neonatal resuscitation clinical studies. To address this, the International Liaison Committee on Resuscitation Neonatal Life Support Task Force established a working group to develop the first Utstein-style reporting guideline for neonatal resuscitation. The working group modeled this approach on previous Utstein-style guidelines for other populations. This reporting guideline focuses on resuscitation of newborns immediately after birth for respiratory failure, bradycardia, severe bradycardia, or cardiac arrest. We identified 7 relevant domains: setting, patient, antepartum, birth/preresuscitation, resuscitation process, postresuscitation process, and outcomes. Within each domain, relevant data elements were identified as core versus supplemental. Core data elements should be collected and reported for all neonatal resuscitation studies, while supplemental data elements may be collected and reported using standard definitions when possible. The Neonatal Utstein template includes both core and supplemental elements across the 7 domains, and the associated Data Table provides detailed information and reporting standards for each data element. The Neonatal Utstein reporting guideline is anticipated to assist investigators engaged in neonatal resuscitation research by standardizing data definitions. The guideline will facilitate data pooling in meta-analyses, enhancing the strength of neonatal resuscitation treatment recommendations and subsequent guidelines.
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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 | 0.244 | 0.534 |
| Meta-epidemiology (narrow) | 0.002 | 0.005 |
| Meta-epidemiology (broad) | 0.007 | 0.017 |
| Bibliometrics | 0.018 | 0.021 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.013 | 0.007 |
| Research integrity | 0.015 | 0.020 |
| Insufficient payload (model declined to judge) | 0.022 | 0.019 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".