Guidelines on Deferred Cord Clamping and Cord Milking: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Deferred cord clamping (DCC) saves lives. It reduces extremely preterm infants' mortality by 30%, yet a minority of eligible infants receive it. This may in part be due to lack of awareness or confidence in evidence, or conflicting or vague guidelines. OBJECTIVE: To systematically review clinical practice guidelines and other statements on DCC and cord milking. DATA SOURCES: Ten academic and guideline databases were searched. STUDY SELECTION: Clinical practice guidelines and other statements (position statements and consensus statements) providing at least 1 recommendation on DCC or umbilical cord milking among preterm or term infants were included. DATA EXTRACTION: Data from included statements were extracted by 2 independent reviewers, and discrepancies were resolved through consensus. Guideline quality was appraised with modified Appraisal of Guidelines for Research and Evaluation II and Appraisal of Guidelines for Research and Evaluation Recommendation Excellence tools. RESULTS: Forty-four statements from 35 organizations were included. All endorsed DCC for uncompromised preterm infants, and 11 cautiously stated that cord milking may be considered when DCC is infeasible. Only half (49%) of the recommendations on the optimal duration of DCC were supported by high-quality evidence. Only 8% of statements cited a mortality benefit of DCC for preterm infants. LIMITATIONS: Because systematic reviews of guidelines are relatively novel, there are few tools to inform study execution; however, we used the Appraisal of Guidelines for Research and Evaluation II and the Appraisal of Guidelines for Research and Evaluation Recommendation Excellence to assess quality and were methodologically informed by previous systematic reviews of guidelines. CONCLUSIONS: Statements worldwide clearly encouraged DCC. Their implementability would benefit from noting the preterm mortality benefit of DCC and more granularity.
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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 | 0.036 | 0.191 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.021 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".