Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 203

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Screening for gestational diabetes: a systematic review and economic evaluation

Open access
Scott, D.A., Loveman, E., McIntyre, L., Waugh, N.·2002·Health Technology Assessment

Abstract

Background Screening for gestational diabetes mellitus (GDM) has been controversial, with some expert bodies advising universal screening, others selective screening, and yet others advising against screening at all. This has partly been a result of debate about the definition of GDM, and partly because of the profusion of different tests available, both for screening and definite diagnosis. In the UK, there is no national policy on screening, and a variety of practices exist in different parts of the country. There have also been doubts about the treatment of GDM, and particularly about management of minor degrees of glucose elevation, which are better described as glucose intolerance rather than true diabetes. Objectives To provide an updated review of current knowledge, to clarify research needs, and to assist with policy making in the interim, pending future research. Methods A literature review was carried out, with a particular focus on screening methods and costs, and an appraisal of screening for GDM against the criteria for assessing screening programmes used by the UK National Screening Committee (NSC). Results There is still debate about what is meant by GDM – the threshold for diagnosis is not soundly based; the terms GDM and impaired glucose tolerance are not used in a standard fashion in pregnancy; there is almost certainly a continuum of risk to the baby, rather than there being separate normal and abnormal groups; and the key risk factor in most women may be maternal overweight, with glucose intolerance being an associate of that. In addition there are some rare genetic conditions, which affect a few women, such as glucokinase and hepatic nuclear factor disorders. GDM is usually defined according to divergence from normal glucose levels, but glucose levels are usually raised in pregnancy, and so diagnosis by normal levels in non-pregnant women may misclassify many normal pregnant women as abnormal. This may lead to anxiety and the inconvenience of extra investigations and ‘disease’ care. The Caesarean section rate appears to be increased by the diagnosis alone. Ideally, the condition should be defined by the incidence of adverse effects. However, the most common reported complication of GDM is ‘macrosomia’ in the baby. This is usually defined by arbitrary weight cut-offs (usually a birth weight of 4000 g, but sometimes 4500 g), but such neat thresholds fail to distinguish between larger than average healthy babies and those that have the abnormal growth patterns associated with high insulin levels in the womb. Screening for GDM fails to meet some of the NSC criteria. A number of screening tests have been used but some, such as glycosylated haemoglobin and fructosamine, have proved unsatisfactory and can be discarded. Others, such as urine testing or random blood glucose, are far from satisfactory, although they may be cheap to do. There is marked international variation. Risk factors such as weight, age and family history are useful for selective screening but some patients with GDM would be missed. Fasting plasma glucose (FPG) is convenient and reliable, but some pregnant women have normal fasting levels but raised levels of glucose after meals, and would be missed by screening based on FPG alone. Glucose challenge tests (GCTs) are based on glucose levels after a glucose drink, but also have shortcomings. The definitive diagnosis is usually by oral glucose tolerance test (OGTT), but the glucose load and timing vary in different countries; taking a 75 g glucose load is unnatural, makes some women sick, and the reproducibility of the test is poor. More natural methods such as test meals have been used, but not widely. Conclusions Interim conclusions There are clearly some women whose glucose levels rise sufficiently in pregnancy to cause harm to their babies. However, there are also many women with lower levels of glucose intolerance whose babies are not at risk, but who may suffer anxiety and inconvenience as a result of being classed as abnormal. On balance, the present evidence suggests that we should not have universal screening, but a highly selective policy, based on age and overweight. The best test at present, for those deemed to need testing, is probably the GCT, preferably combined with an FPG. The benefits of a follow-up OGTT are doubtful.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3310/hta6110

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 6 references

Cited by

See all 203

Metadata

Authors
Scott, D. A., Loveman, E., McIntyre, L., & Waugh, N.
Venue
Health Technology Assessment
Published
2002
Volume
6
Issue
11
Pages
1-161
ISSN
  • 1366-5278 (ISSN-L)
  • 2046-4924
OpenAlex
W2066951981
Cited by
203
References
6
FWCI
0.91
Type
journal article
Language
en
Open access
diamond

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Screening for gestational diabetes: a systematic review and economic evaluation. https://app.cochat.ai/papers/10.3310/hta6110
The paper
Scott, D. A., Loveman, E., McIntyre, L., & Waugh, N. (2002). Screening for gestational diabetes: a systematic review and economic evaluation. Health Technology Assessment. https://doi.org/10.3310/hta6110

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.