<b>NET</b>work <b>M</b>eta-analysis Of <b>T</b>rials of <b>I</b>nitial <b>O</b>xygen in preterm <b>N</b>ewborns (NETMOTION): A Protocol for Systematic Review and Individual Participant Data Network Meta-Analysis of Preterm Infants &#x3c;32 Weeks’ Gestation Randomized to Initial Oxygen Concentration for Resuscitation
Bibliographic record
Abstract
BACKGROUND: Internationally recognized guidelines recommend the judicious use of low oxygen (21-30%), titrated to peripheral oxygen saturation targets, for the initiation of resuscitation of very and extremely preterm infants (<32 weeks' gestation). However, despite more than 10 randomized controlled trials on this question, the ideal initial oxygen concentration for this group of vulnerable infants remains uncertain. AIMS: This study aims to assess the effect of various initial oxygen concentrations on (1) all-cause mortality, chronic lung disease, intraventricular hemorrhage, and retinopathy of prematurity; and (2) reaching the prescribed oxygen saturation targets by 5 min after birth, in preterm infants requiring resuscitation. METHODS: We will conduct a systematic review and network meta-analysis using individual participant data. Studies of preterm infants <32 weeks' gestation, randomized to initial oxygen concentration, will be included. We will systematically search medical databases and trial registries for eligible studies (published or unpublished). Records will be screened by two independent reviewers, with conflicts resolved by the inclusion of a third reviewer. Identified initial oxygen concentrations will be grouped into the following nodes: low (≤30%), intermediate (60%), and high (≥90%) oxygen. A two-step random-effects contrast-based network meta-regression will be calculated to compare and rank different oxygen concentrations. Analyses will be intention-to-treat, with the primary outcome of all-cause mortality. DISCUSSION: This is the first individual participant data network meta-analysis of initial oxygen concentrations for the resuscitation of preterm infants. This novel approach may address long-standing uncertainty regarding optimal oxygen supplementation practice for the resuscitation of preterm infants <32 weeks' gestation.
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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 | 0.023 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.019 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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".