Falling Third-Trimester Insulin Requirements and Adverse Pregnancy Outcomes: A Systematic Review [32E]
Bibliographic record
Abstract
INTRODUCTION: There is conflicting evidence on whether falling insulin requirements in the third-trimester are associated with adverse pregnancy outcomes. Our objective was to systematically review the literature to determine the association between a ≥15 percent fall in insulin dose (PFID) and adverse pregnancy outcomes. METHODS: We searched Medline, Embase and PubMed from inception until October 2016 for English language articles describing falling insulin requirements and pregnancy outcomes. Article screening and data extraction was performed in duplicate. As significant clinical and methodological heterogeneity was anticipated, no formal meta-analysis was planned. Outcomes were described as proportions. RESULTS: We identified 1011 publications, of which three observational studies met eligibility criteria. Two studies that used ≥15 PFID were included in the quantitative analysis. Pregnancies with ≥15 PFID were associated with small-for-gestational-age (SGA) fetuses (6/40 vs. 7/153, p=0.04; risk ratio (RR) 2.95 [1.08, 8.07]). There were no differences in large-for- gestational-age fetuses (14/40 vs. 58/153; RR 1.07 [0.68, 1.70]), low 5-minute Apgar scores (6/40 vs. 16/153; RR 1.93 [0.52, 7.14]), caesarean deliveries (25/40 vs. 105/153; RR 0.90 [0.70, 1.17]), extreme preterm (3/35 vs. 2/104) birth, stillbirths (1/35 vs. 1/104) or hypertensive disorders (9/35 vs. 19/104, p=0.34). CONCLUSION: This systematic review of observational studies found no association between ≥15 PFID and adverse pregnancy outcomes, except for a higher number of SGA fetuses. This was not causal. Early delivery based on ≥15 PFID cannot be recommended. Instead, clinical management should involve continued maternal-fetal surveillance, exploring possible obstetric and metabolic reasons for this PFID, and treatment of the primary cause.
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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 | 0.015 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".