Falling Third-Trimester Insulin Requirements in Diabetic Pregnancies and Adverse Pregnancy Outcomes: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: There is conflicting evidence on whether falling insulin requirements (FIRs) in the third trimester are associated with adverse pregnancy outcomes. We synthesized published evidence to address this knowledge gap. Methods: We conducted a systematic review and meta-analysis, wherein we searched four bibliographic databases until September 04 2025 for articles describing third-trimester FIR and pregnancy outcomes. We assessed the risk of bias using the Quality In Prognosis Studies (QUIPS) tool, performed meta-analysis with pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) for maternal and perinatal outcomes and assessed certainty of evidence (CoE) using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. Results: We identified 2044 articles, of which nine fulfilled the eligibility criteria. Third-trimester FIR has an important association with preeclampsia [OR 3.0 (95% CI 1.41–6.38, absolute event rate (AER) 15.9%, high CoE], probably has an important association with neonatal respiratory distress [OR 2.03 (95% CI 1.27–3.26), AER 15.8%, moderate CoE]; may have an important association with a composite of outcomes reflecting placental dysfunction [OR 2.32 (95% CI 1.07–5.03), AER 13.5%, low CoE] and preterm birth [OR 2.0 (95% CI 0.51–7.85), AER 9.3%, very low CoE]; and may not have an important association with stillbirth [OR 1.5 (95% CI 0.27–8.40), AER 0.05%, low CoE], small-for-gestational-age [OR 1.29 (95% CI 0.77–2.15), AER 1.8%, low CoE], or low Apgar score at 5 minutes [OR 1.68 (95% CI 0.68–4.14), AER 2.3%, low CoE]. Conclusions: The CoE regarding associations between third-trimester FIR and adverse pregnancy outcomes varies considerably, and it remains uncertain whether these associations reflect cause or effect. Therefore, a solitary finding of third-trimester FIR does not warrant early delivery and maternal–foetal surveillance should be based on the primary clinical diagnosis.
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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 | 0.014 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.037 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".