Evidence map›Paper›PMID 42597015›Full record

ReviewPregnancy (Hoboken, N.J.)2026

Optimizing diabetes care in pregnancy: A systematic review of glycemic targets, treatment initiation, and glucose-lowering pharmacological management for T1DM, T2DM, and GDM.

Gemma Villanueva, Elise Cogo, Brian Buckley, Jennifer Petkovic, Katrin Probyn, Heather McIntosh, Hanna Bergman, Maria Christou, Ferruccio Pelone, Fatema Kazi and 3 more

Abstract readReview
In one paragraph

Review in Pregnancy (Hoboken, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Gemma VillanuevaCochrane Response The Cochrane Collaboration London UK.
Elise CogoCochrane Response The Cochrane Collaboration London UK.
Brian BuckleyCochrane Response The Cochrane Collaboration London UK.
Jennifer PetkovicCochrane Response The Cochrane Collaboration London UK.
Katrin ProbynCochrane Response The Cochrane Collaboration London UK.
Heather McIntoshCochrane Response The Cochrane Collaboration London UK.
Hanna BergmanCochrane Response The Cochrane Collaboration London UK.
Maria ChristouCochrane Response The Cochrane Collaboration London UK.
Ferruccio PeloneCochrane Response The Cochrane Collaboration London UK.
Fatema KaziCochrane Response The Cochrane Collaboration London UK.
Yanina SguasseroCochrane Response The Cochrane Collaboration London UK.
Meghan SebastianskiCochrane Response The Cochrane Collaboration London UK.
Nicholas HenschkeCochrane Response The Cochrane Collaboration London UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Pregnant women with diabetes are at increased risk of adverse maternal and neonatal outcomes, yet the optimal approach to achieving recommended glucose levels and glucose-lowering pharmacological strategies during pregnancy remains unclear. Methods: We conducted a systematic review with meta-analysis of randomized controlled trials (RCTs) synthesizing the evidence on glycemic targets and pharmacological interventions for pregnant women with pre-existing diabetes or gestational diabetes mellitus (GDM). We extracted data for outcomes prioritized for the development of all WHO guidelines on maternal and perinatal health, as well as intervention-specific outcomes. The selected critical outcomes were maternal death, maternal functioning and women's views and experiences, stillbirth/fetal death, neonatal death, and perinatal death. We followed standard Cochrane methods. Results: The evidence on glycemic targets was very limited. Among women with type 1 diabetes mellitus (T1DM), meeting stricter glycemic targets may increase the risk of hypoglycemia and longer hospitalization, whereas less stringent targets may increase the risk of caesarean birth, large-for-gestational-age babies, and neonatal respiratory distress syndrome. In women with GDM, no clear differences were observed between a tight and moderate target. Evidence on the optimal approach to glucose-lowering pharmacotherapy for the management of type 1 and type 2 diabetes during pregnancy was also limited. In women with GDM, metformin was associated with better maternal and neonatal outcomes than glibenclamide. Compared to insulin, metformin probably reduces the risk of neonatal intensive care admission and neonatal hypoglycemia. We rated most outcomes as low or very low certainty, which means that the true effects of the interventions may differ substantially from current estimates, and new evidence is likely to change our confidence in the estimates of effects. The main reasons for downgrading the certainty of the evidence were risk of bias and imprecision. Conclusions: This review did not yield sufficient evidence to determine which glycemic targets are the most effective in improving health outcomes in women with pre-existing diabetes or GDM. Current evidence on glucose-lowering pharmacotherapy in pregnancy is limited and generally of low certainty. In women with GDM, metformin and insulin appeared to offer benefits compared to glibenclamide, and metformin may be a safe first-line alternative to insulin, although the evidence is limited for most outcomes. High-quality RCTs are needed to clarify the effects of these interventions, including into the longer term for the child. PROSPERO registration: CRD42025630036.

Indexed as

diabetes in pregnancygestational diabetes mellitusglybenclamideglycaemic controlinsulinmetforminoral hypoglycaemic agentspregestational diabetestype 1 diabetestype 2 diabetes

Identifiers

PMID42597015
PMCPMC13344337

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.