The Effects of Tocolysis on Neonatal Septic Death in Women With PPROM: A Retrospective Cohort Study [21Q]
Bibliographic record
Abstract
INTRODUCTION: The use of tocolysis in women with preterm premature rupture of membranes (PPROM) remains uncertain, particularly in suspected chorioamnionitis. The purpose of our study was to evaluate the effect of tocolysis on neonatal septic death in women with PPROM +/- chorioamnionitis. METHODS: Using the Linked Birth and Infant Death data files (2009-2013) from the National Center for Health Statistics, we conducted a retrospective cohort study on all registered live births between 24-32 weeks' of pregnancy in order to evaluate the effect of tocolysis on neonatal septic death at 7 and at 28 days among women with PPROM between 24 and 32 weeks' gestation. Logistic regression models were used to evaluate the effect of tocolysis on neonatal septic death at 7 and at 28 days in births with and without chorioamnionitis. RESULTS: There were 46,968 births that met study criteria, and of which 6,264 (13.3%) received tocolysis. Tocolysis was more commonly administered to women who were Caucasians, smokers, and with multiple birth pregnancies and previous preterm births. There was no significant association between tocolysis and neonatal septic death at 7 days (OR 0.66, 95% CI 0.39-1.13) and at 28 days (OR 0.85, 95% CI 0.60-1.19). This was consistent in pregnancies complicated by chorioamnionitis and those without chorioamnionitis. CONCLUSION: In the setting of PPROM, tocolysis does not appear to increase the risk of neonatal septic death. Therefore, consideration can be given to its administration if clinically indicated.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".