Respiratory stabilization before umbilical cord clamping in preterm neonates: a systematic review and network meta-analysis
Bibliographic record
Abstract
AIM: To evaluate the comparative effectiveness of deferred cord clamping (DCC), umbilical cord milking (UCM); time-based cord clamping with respiratory support prior to umbilical cord clamping (TBCC) and physiological-based cord clamping (PBCC) in preterm neonates. METHODS: Medline, Embase and CENTRAL were searched until April 2025. Bayesian random effects network meta-analysis (NMA) was utilized. DCC for 30-60 s (DCC_60), TBCC with respiratory support for at least 60 s (DCC_ICR_60) or more (DCC_ICR_more_60), PBCC, UCM and immediate cord clamping (ICC) were evaluated. RESULTS: 11 RCTs and 8 non-RCTs were included. Clinical benefit or harm could not be ruled out for mortality, severe IVH and MBI. DCC_60 possibly decreased the risk of periventricular leukomalacia (PVL) and necrotising enterocolitis (NEC) ≥ stage 2 compared to DCC_ICR_60 (very low-certainty). PBCC possibly decreased the risk of delivery room adrenaline compared to DCC_ICR_60 and DCC_60 (very low-certainty). DCC_ICR_more_60 and UCM were probably similar in efficacy with respect to mean admission temperature (moderate-certainty). DCC_60, most TBCC interventions and PBCC probably had similar effect on patent ductus arteriosus requiring intervention, blood transfusion requirement and bronchopulmonary dysplasia (moderate-certainty). DCC_ICR_more_60 compared to ICC possibly decreased the risk of mortality or neurodevelopmental impairment at 2 years' corrected age (low-certainty). CONCLUSIONS: This NMA indicates that DCC, TBCC and PBCC probably have comparable effects on the important clinical outcomes in preterm neonates. Since the evidence certainty was very low for the critical outcomes, adequately powered multi-centric RCTs are warranted.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.028 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".