Going “the Last Mile” With Guidelines for Deferred Umbilical Cord Clamping
Bibliographic record
Abstract
* Abbreviation: DCC — : deferred cord clamping Why are clinicians reluctant to adopt deferred umbilical cord clamping? Deferred cord clamping (DCC) facilitates a smooth transition to extrauterine life, and recent meta-analyses reveal reduced neonatal morbidity and mortality among preterm infants.1–3 In this issue of Pediatrics , Korale Liyanage et al4 present a systematic review of clinical practice guidelines on DCC and umbilical cord milking. All 44 statements from 35 organizations included in the review endorsed deferred umbilical cord clamping for uncompromised preterm infants. Despite the proliferation of guidelines, the authors note that >40% of preterm infants admitted to NICUs across California and Canada do not receive DCC. What is preventing the translation of evidence to practice? Low uptake of clinical practice guidelines is not unique to cord management; however, the case of DCC highlights that publication of guidelines only begins the crucial phase of dissemination, local implementation, and evaluation.5,6 Less than half of guidelines adequately articulated the values and preferences informing their treatment recommendations or provided advice on implementation.4 Regional and national councils and professional organizations often create context-specific guidelines from a common evidence-evaluation base, such as the International Liaison Committee on Resuscitation Consensus on Science. When different regions, … Address correspondence to Susan Niermeyer, MD, MPH, University of Colorado School of Medicine, Section of Neonatology, 13121 E 17th Ave, Mail Stop 8402, Aurora, CO 80045. E-mail: susan.niermeyer{at}cuanschutz.edu
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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 | 0.032 | 0.235 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".