Impact of meconium consistency on infant resuscitation and respiratory outcomes: a retrospective-cohort study and systematic review
Bibliographic record
Abstract
Objective To compare short-term outcomes of infants born with thick versus thin meconium stained amniotic fluid (MSAF) and to perform a systematic review of the topic.Methods A retrospective, single center, cohort study of infants’ ≥34 weeks’ gestation born with MSAF between 1 June 2013 and 30 September 2016. Birth resuscitation and respiratory outcomes were compared between the groups. A systematic review was conducted of similar studies published between 1 January 2000 and 30 June 2019.Results 1507 infants were eligible; 464 (30.8%) thick, 1,043 (69.2%) thin MSAF. The thick group required more respiratory support at birth and was 5.5-fold (95% CI: 2.51–11.95) more likely to and have meconium aspiration syndrome (MAS) and 2.1-fold more likely (95% CI: 0.89–4.83) to require either noninvasive respiratory support or intubation than the thin group. The thick group also had significantly higher oxygen supplementation >24 h (p < .001) and pneumothorax (p = .002). Across 12 studies included in the systematic review, infants with thick MSAF required more intensive birth resuscitation, ventilation support, with higher incidences of MAS. Study differences prohibited data comparisons and quantitative outcome evaluations.Conclusion Infants with thick MSAF required more intensive birth resuscitation and ventilation support. Our findings need confirmation in robust, prospective cohort studies.
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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 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".