Screening and subsequent management for gestational diabetes for improving maternal and infant health

  • Review
  • Intervention

Authors

  • Joanna Tieu,

    Corresponding author
    1. The University of Adelaide, ARCH: Australian Research Centre for Health of Women and Babies, Robinson Research Institute, Discipline of Obstetrics and Gynaecology, Adelaide, South Australia, Australia
    • Joanna Tieu, ARCH: Australian Research Centre for Health of Women and Babies, Robinson Research Institute, Discipline of Obstetrics and Gynaecology, The University of Adelaide, Women's and Children's Hospital, 1st floor, Queen Victoria Building, 72 King William Road, Adelaide, South Australia, 5006, Australia. joanna.tieu@gmail.com. joanna.tieu@mh.org.au.

    Search for more papers by this author
  • Andrew J McPhee,

    1. Women's and Children's Hospital, Neonatal Medicine, North Adelaide, South Australia, Australia
    Search for more papers by this author
  • Caroline A Crowther,

    1. The University of Adelaide, ARCH: Australian Research Centre for Health of Women and Babies, Robinson Research Institute, Discipline of Obstetrics and Gynaecology, Adelaide, South Australia, Australia
    2. The University of Auckland, Liggins Institute, Auckland, New Zealand
    Search for more papers by this author
  • Philippa Middleton

    1. The University of Adelaide, Women's and Children's Research Institute, Adelaide, South Australia, Australia
    Search for more papers by this author

Abstract

Background

Gestational diabetes mellitus (GDM) is a form of diabetes that occurs in pregnancy. Although GDM usually resolves following birth, it is associated with significant morbidities for mother and baby both perinatally and in the long term. There is strong evidence to support treatment for GDM. However, there is little consensus on whether or not screening for GDM will improve maternal and infant health and if so, the most appropriate protocol to follow.

Objectives

To assess the effects of different methods of screening for GDM and maternal and infant outcomes.

Search methods

We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (1 December 2013).

Selection criteria

Randomised and quasi-randomised trials evaluating the effects of different methods of screening for GDM.

Data collection and analysis

Two review authors independently conducted data extraction and quality assessment. We resolved disagreements through discussion or through a third author.

Main results

We included four trials involving 3972 women in the review. One quasi-randomised trial compared risk factor screening with universal or routine screening by 50 g oral glucose challenge testing. Women in the universal screening group were more likely to be diagnosed with GDM (one trial, 3152 women, risk ratio (RR) 0.44, 95% confidence interval (CI) 0.26 to 0.75). This trial did not report on the other primary outcomes of the review (positive screen for GDM, mode of birth, large-for-gestational age, or macrosomia). Considering secondary outcomes, infants of mothers in the risk factor screening group were born marginally earlier than infants of mothers in the routine screening group (one trial, 3152 women, mean difference (MD) -0.15 weeks, 95% CI -0.27 to -0.03).

The remaining three trials evaluated different methods of administering a 50 g glucose load. Two small trials compared glucose monomer with glucose polymer testing, with one of these trials including a candy bar group. One trial compared a glucose solution with food. No differences in diagnosis of GDM were found between each comparison. However, in one trial significantly more women in the glucose monomer group screened positive for GDM than women in the candy bar group (80 women, RR 3.49, 95% CI 1.05 to 11.57). The three trials did not report on the primary review outcomes of mode of birth, large-for-gestational age or macrosomia. Overall, women drinking the glucose monomer experienced fewer side effects from testing than women drinking the glucose polymer (two trials, 151 women, RR 2.80, 95% CI 1.10 to 7.13). However, we observed substantial heterogeneity between the trials for this result (I² = 61%).

Authors' conclusions

There was insufficient evidence to determine if screening for gestational diabetes, or what types of screening, can improve maternal and infant health outcomes.

Résumé scientifique

Dépistage et prise en charge du diabète gestationnel pour une meilleure santé de la mère et de l'enfant

Contexte

Le diabète sucré gestationnel (DSG) est une forme de diabète qui survient pendant la grossesse. Bien que le DSG disparaisse généralement après l'accouchement, il est associé à des morbidités importantes pour la mère et l'enfant, tant dans la période périnatale qu'à long terme. Il existe des données probantes en faveur du traitement du DSG. Toutefois, les avis divergent quant à savoir si le dépistage du DSG améliore ou non la santé de la mère et de l'enfant et, le cas échéant, quel est le meilleur protocole à suivre.

Objectifs

Évaluer les effets des différentes méthodes de dépistage du DSG et les résultats cliniques pour la mère et l'enfant.

Stratégie de recherche documentaire

Nous avons effectué des recherches dans le registre des essais du groupe Cochrane sur la grossesse et l'accouchement (1 décembre 2013).

Critères de sélection

Essais randomisés et quasi randomisés évaluant les effets des différentes méthodes de dépistage du DSG.

Recueil et analyse des données

Deux auteurs de la revue ont de façon indépendante extrait les données et évalué leur qualité. Les désaccords ont été résolus par discussion ou par l'intervention d'un troisième auteur.

Résultats principaux

Quatre essais, impliquant 3 972 femmes, ont été inclus dans la revue. Un essai quasi randomisé a comparé le dépistage selon les facteurs de risque au dépistage universel ou de routine par test de charge glycémique après ingestion de 50 g de glucose. Les femmes du groupe de dépistage universel étaient plus susceptibles de recevoir un diagnostic de DSG (un essai, 3 152 femmes, risque relatif (RR) 0,44, intervalle de confiance (IC) à 95 % de 0,26 à 0,75). Cet essai ne rendait pas compte des autres critères de jugement principaux de la revue (dépistage positif du DSG, mode d'accouchement, grande taille pour l'âge gestationnel ou macrosomie). Sur les critères de jugement secondaires, les nourrissons des mères dans le groupe de dépistage selon les facteurs de risque sont nés légèrement plus tôt que ceux dont la mère était dans le groupe de dépistage de routine (un essai, 3 152 femmes, différence moyenne (DM) -0,15 semaine, IC à 95 % -0,27 à -0,03).

Les trois autres essais ont évalué différentes méthodes d'administration d'une charge de 50 g de glucose. Deux petits essais ont comparé les tests avec un monomère de glucose à un polymère de glucose, l'un d'entre eux comportant un groupe ingérant une barre chocolatée. Un essai a comparé une solution glucosée à des aliments. Aucune différence de diagnostic de DSG n'a été observée entre chaque comparaison. Toutefois, dans un essai, significativement plus de femmes dans le groupe de monomère de glucose ont eu un dépistage positif de DSG que les femmes dans le groupe de barre chocolatée (80 femmes, RR 3,49, IC à 95 % 1,05 à 11,57). Les trois essais ne rendaient pas compte des critères de jugement principaux de cette revue, à savoir le mode d'accouchement, la grande taille pour l'âge gestationnel ou la macrosomie. Dans l'ensemble, les femmes ayant bu le monomère de glucose ont présenté moins d'effets secondaires dus au test que celles ayant bu le polymère de glucose (deux essais, 151 femmes, RR 2,80, IC à 95 % 1,10 à 7,13). Toutefois, nous avons observé une hétérogénéité substantielle entre les essais pour ce résultat (I² = 61 %).

Conclusions des auteurs

Les données étaient insuffisantes pour déterminer si le dépistage du diabète gestationnel, et quels types de dépistage le cas échéant, peuvent améliorer les résultats cliniques de la mère et de l'enfant.

Plain language summary

Screening for gestational diabetes and subsequent management for improving maternal and infant health

Gestational diabetes mellitus (GDM) is a form of diabetes that can develop during pregnancy. Having GDM increases the risk of complications during the rest of the pregnancy for the mother and her baby. Women with GDM are more likely to develop pre-eclampsia (high blood pressure and protein in the urine) and require a caesarean section. For the baby, potential problems include the baby growing larger than it normally would, causing difficulties with birth. The baby can also have low blood sugar levels after birth. Although GDM usually resolves following birth, both mother and child are at risk of developing type II diabetes in the future. There is strong evidence that treating GDM is beneficial and improves health outcomes.

It may therefore help if pregnant women are screened to identify as many as possible of those who do have GDM before they have symptoms, such as excessive thirst or urination, or fatigue. The two main approaches to screening are 'universal' where all women undergo a screening test for GDM; and 'selective' where only those women at 'high risk' are screened. The main risk factors are maternal age, high body mass index, family history and cigarette smoking. The different screening strategies used around the world to identify women with GDM include identifying women based on their risk factors, a blood sugar test one hour after a 50 g glucose drink, and random blood sugar measurements. It is however unclear whether screening for GDM leads to better health outcomes and if so, which screening strategy is the most appropriate.

This review included four trials involving 3972 women and their babies, and found that there is little high-quality evidence on the effects of screening for GDM on health outcomes for mothers and their babies. One trial compared risk factor screening with universal screening, and three trials evaluated different methods of administering a 50 g glucose load (the glucose load is used during the screening test). In one trial, women who were in the universal screening group were more likely to be diagnosed with GDM compared with women in the high-risk screening group. However, this trial was not of high quality. Few other differences between groups were shown in any of the trials. Further research is required to see which recommendations for screening practices for GDM are most appropriate.

Résumé simplifié

Le dépistage et la prise en charge du diabète gestationnel pour une meilleure santé de la mère et de l'enfant

Le diabète sucré gestationnel (DSG) est une forme de diabète qui peut survenir pendant la grossesse. Le DSG augmente le risque de complications pendant le reste de la grossesse pour la mère et son bébé. Les femmes atteintes de DSG sont plus susceptibles de développer une pré-éclampsie (hypertension et protéine dans les urines) et de nécessiter une césarienne. Les complications potentielles pour l'enfant sont notamment une croissance anormalement importante, ce qui peut entraîner des difficultés lors de l'accouchement. Le bébé peut également présenter une hypoglycémie après la naissance. Bien que le DSG disparaisse généralement après l'accouchement, la mère comme l'enfant risquent de développer un diabète de type II par la suite. Tout porte à croire que le traitement du DSG apporte des bénéfices et améliore les résultats cliniques.

Par conséquent, il peut être utile de dépister les femmes enceintes afin d'identifier autant que possible celles atteintes de DSG avant qu'elles n'en développent les symptômes, tels qu'une soif ou une miction excessive ou la fatigue. Les deux approches principales de dépistage sont l'approche « universelle », lorsque toutes les femmes subissent un test de dépistage du DSG, et l'approche « sélective », lorsque seules les femmes à « risque élevé » sont dépistées. Les principaux facteurs de risque sont l'âge de la mère, un indice de masse corporelle élevé, les antécédents familiaux et le tabagisme. Les différentes stratégies de dépistage utilisées dans le monde pour identifier les femmes atteintes de DSG incluent l'identification des femmes d'après leurs facteurs de risque, un test de glycémie une heure après l'absorption d'une boisson contenant 50 g de glucose, et des mesures de glycémie aléatoires. Toutefois, on ne sait pas avec certitude si le dépistage du DSG améliore les résultats cliniques et, le cas échéant, quelle stratégie de dépistage est la plus efficace.

Cette revue a inclus quatre essais portant sur 3 972 femmes et leurs bébés, et a révélé qu'il existe peu de données de qualité élevée sur les effets du dépistage du DSG sur les résultats cliniques pour la mère et l'enfant. Un essai comparait le dépistage selon les facteurs de risque au dépistage universel, et trois essais évaluaient différentes méthodes d'administration d'une charge de 50 g de glucose (utilisée pendant le test de dépistage). Dans un essai, les femmes qui étaient dans le groupe de dépistage universel étaient plus susceptibles de recevoir un diagnostic de DSG, en comparaison avec les femmes dans le groupe de dépistage à haut risque. Cependant, cet essai n'était pas de qualité élevée. Peu d'autres différences entre les groupes ont été observées dans l'ensemble des essais. D'autres recherches sont nécessaires pour établir des recommandations quant aux meilleures pratiques de dépistage du diabète sucré gestationnel.

Notes de traduction

Traduit par: French Cochrane Centre 22nd June, 2014
Traduction financée par: Financeurs pour le Canada : Instituts de Recherche en Santé du Canada, Ministère de la Santé et des Services Sociaux du Québec, Fonds de recherche du Québec-Santé et Institut National d'Excellence en Santé et en Services Sociaux; pour la France : Ministère en charge de la Santé

Streszczenie prostym językiem

Badania przesiewowe oraz późniejsze postępowanie u kobiet z cukrzycą ciężarnych w celu poprawy zdrowia matki i dziecka

Cukrzyca ciężarnych (ang. Gestational Diabetes Mellitus, GDM) jest typem cukrzycy, który może rozwinąć się podczas ciąży. Zachorowanie na GDM zwiększa ryzyko powikłań podczas ciąży u matki i jej dziecka. U kobiet z GDM stwierdza się większe prawdopodobieństwo rozwoju stanu przedrzucawkowego (wysokiego ciśnienia krwi i obecności białka w moczu) i częściej istnieje potrzeba przeprowadzenia u nich cesarskiego cięcia. W przypadku dziecka potencjalne problemy obejmują zwiększenie rozmiarów dziecka ponad normę, co powodować może trudności podczas porodu. Dziecko może mieć również niski poziom cukru po urodzeniu. Chociaż GDM zwykle ustępuje po urodzeniu, zarówno matka oraz dziecko obciążone są ryzykiem rozwoju cukrzycy typu 2 w przyszłości. Istnieją silne dowody na to, że leczenie GDM jest korzystne i poprawia wyniki zdrowotne.

Badania przesiewowe kobiet ciężarnych, mogłyby okazać się przydatne w celu zidentyfikowania jak największej liczby kobiet chorujących na GDM jeszcze przed wystąpieniem objawów takich jak: nadmierne pragnienie, częste oddawanie moczu lub zmęczenie. Dwa główne podejścia do badań przesiewowych to podejście "uniwersalne", w którym wszystkie kobiety poddane są badaniu przesiewowemu pod kątem GDM; oraz podejście "wybiórcze", w którym badane są wyłącznie kobiety obciążone "dużym ryzykiem" wystąpienia cukrzycy. Główne czynniki ryzyka stanowią: wiek matki, duży wskaźnik masy ciała (BMI), dodatni wywiad rodzinny oraz palenie papierosów. Różne strategie badań przesiewowych wykorzystuje się na całym świecie do identyfikacji kobiet z GDM, obejmują one metody identyfikacji na podstawie czynników ryzyka, test obciążenia glukozą po jednej godzinie od wypicia płynu z 50 g glukozy oraz pomiary cukru we krwi w dowolnym momencie. Nie jest jednak jasne czy badania przesiewowe w kierunku GDM prowadzą do lepszych wyników zdrowotnych, a jeśli prowadzą, to która strategia badań przesiewowych jest najbardziej odpowiednia.

Do niniejszego przeglądu włączono cztery badania obejmujące 3972 kobiet oraz ich dzieci, stwierdzono, że istnieje niewiele doniesień o wysokiej jakości dotyczących wpływu badań przesiewowych w kierunku GDM na zdrowie matek oraz ich dzieci. W jednym badaniu porównywano badania przesiewowe u kobiet obciążonych czynnikami ryzyka z badaniem przesiewowym prowadzonym u wszystkich kobiet, w trzech innych badaniach porównywano różne metody podawania 50 g glukozy w teście obciążenia glukozą (obciążenie glukozą jest wykorzystywane podczas badania przesiewowego). W innym badaniu, u kobiet objętych uniwersalnym badaniem przesiewowym było większe prawdopodobieństwo rozpoznania GDM w porównaniu z grupą obejmującą badania przesiewowe jedynie u kobiet obciążonych dużym ryzykiem. Badanie to nie było jednak wysokiej jakości. Kilka innych różnic między grupami stwierdzono w opisanych badaniach. Potrzeba dalszych badań w celu sprawdzenia, które zalecenia dotyczące badań przesiewowych w kierunku GDM są najbardziej odpowiednie.

Uwagi do tłumaczenia

Tłumaczenie: Bartłomiej Matulewicz, Redakcja Paulina Rolska

Background

Description of the condition

Gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is defined as "carbohydrate intolerance of varying degrees of severity with onset or first recognition during pregnancy" (Metzger 1998). GDM therefore includes type I or type II diabetes previously undetected or with first presentation during pregnancy. GDM typically resolves following birth. However, these women are at risk for type II diabetes in the future (Kim 2002).

Epidemiology

GDM affects up to 14% of pregnant women every year and accounts for 90% of pregnancies affected by diabetes mellitus (Coustan 1995; Setji 2005). There is growing concern over the increasing prevalence of GDM and its effects for individual mothers and infants and its impact on public health (Ferrara 2007; Hunt 2007; Metzger 2007). GDM is associated with numerous risk factors. Maternal age and body mass index (BMI) are among the most common risk factors (Di Cianni 2003; O'Sullivan 1973). Specific ethnicities are also at higher risk of developing GDM, namely Hispanic, black, Native American, South or East Asian, Pacific Islander and Indigenous Australian (Kjos 2005). These ethnicities are similar to those at high risk of type II diabetes mellitus, with suggestions that parallels may be drawn between these two forms of diabetes (Ben-Haroush 2004; Kuhl 1998). Other risk factors include previous birth of a large baby, a family history of diabetes mellitus, weight gain and cigarette smoking (Davey 2001; Di Cianni 2003; O'Sullivan 1973; Solomon 1997).

Aetiology/pathophysiology

Normally, insulin is released by pancreatic beta cells in response to increasing blood glucose levels to achieve euglycaemia (normal blood glucose levels). This system can be disrupted in two ways. A problem with the release of insulin from beta cells can occur, such as in type I or insulin dependent diabetes mellitus. Alternatively, insulin may not act as effectively in promoting glucose uptake. This is known as insulin resistance, and is seen in the development of type II or non insulin dependent diabetes mellitus and GDM.

Placental hormones such as progesterone, cortisol, prolactin and human placental lactogen released mid-pregnancy contribute to decreased insulin action in pregnancy (Kuhl 1998). Physiologically, this ensures sufficient nutrient transport to the fetus as it develops, and promotes growth (Setji 2005). In a normal pregnancy, the action of these placental hormones is adequately compensated by increasing insulin release, creating an equilibrium between insulin supply and insulin demand.

In pregnant women with abnormal glucose intolerance, the insulin resistance of pregnancy is not adequately compensated for, resulting in carbohydrate or glucose intolerance. It is suggested that women who develop GDM may also have an underlying insulin resistance, such as high maternal adiposity, or beta cell dysfunction that potentiates the insulin resistance of pregnancy (Buchanan 2005; Kuhl 1998; Richardson 2007). Recent theories relating to the pathogenesis of GDM include inflammation (Richardson 2007).

These effects culminate in a disruption of the action of insulin in maintaining glucose levels, resulting in maternal hyperglycaemia (high blood glucose). Glucose is transferred, via the placenta, to the fetus. Maternal hyperglycaemia therefore stimulates a fetal hyperinsulinaemia to counter the excess placental glucose transfer.

There is strong evidence confirming the continuum of risk associated with increasing carbohydrate intolerance (Dodd 2007; HAPO 2008; Sermer 1995). The point at which this increasing carbohydrate intolerance becomes pathological remains uncertain.

Clinical features

Infant

Excess insulin due to maternal hyperglycaemia acts in two ways on the fetus. Firstly, insulin promotes fat deposition due to the state of nutrient excess (Pedersen 1954; Whitelaw 1977). Secondly, insulin acts as a growth factor, stimulating further growth of the infant in utero (Hunt 2007). Thus, fetal hyperinsulinaemia results in excessive growth of the fetus, leading to one of the major perinatal concerns in GDM, macrosomia (birthweight greater than 4000 g). Macrosomia may lead to birth trauma including shoulder dystocia, nerve palsies and fractures (Dodd 2007; Metzger 1998). GDM is associated with respiratory distress syndrome, neonatal hypoglycaemia (low blood glucose), hyperbilirubinaemia (high bilirubin levels), polycythaemia (excess red blood cells), and hypocalcaemia (low calcium) (ADA 2003; Metzger 1998). In utero exposure to hyperglycaemia has long lasting effects on the infant, increasing their risk of future obesity and type II diabetes mellitus (Pettitt 1985; Silverman 1998).

Maternal

With the implementation of screening protocols, GDM is usually diagnosed before it becomes symptomatic during pregnancy. However, where GDM is undetected, the pregnant woman may experience polyuria (increased urinary frequency), polydipsia (excessive thirst) or fatigue. Macrosomia in utero or polyhydramnios (excess amniotic fluid volume) may also indicate GDM.

In the mother, evidence supports an association between GDM and increased rates of caesarean delivery and pre-eclampsia (ACOG 2001). As with their infants, the consequences of GDM for the mother extend beyond the perinatal period. There are strong links between GDM and future development of type II diabetes mellitus. Within 10 years of developing GDM, half the women develop type II diabetes mellitus (Kim 2002).

Diagnosis of GDM

Although diagnostic criteria vary (ACOG 2001; ADA 2003; Berger 2002; IADPSG 2010; NICE 2008; Oats 2004; RANZCOG 2008; WHO 1999), the oral glucose tolerance test (OGTT) is considered the ‘gold standard’ for diagnosis of GDM (Scott 2002). Minor degrees of abnormal carbohydrate tolerance, such as one abnormal value on OGTT or positive oral glucose challenge test (OGCT) with normal OGTT are also associated with similar outcomes to GDM. This is in line with the increasing awareness of the continuum of risk associated with increasing carbohydrate intolerance (Dodd 2007; HAPO 2008; Sermer 1995).

Management of GDM

The importance of management for women with GDM has been widely accepted and is evaluated by several Cochrane reviews (Alwan 2009; Boulvain 2001; Ceysens 2006) and the treatment of GDM is widely supported (ADA 2003; Crowther 2005; Hoffman 1998; Metzger 1998; O'Sullivan 1966). Treatment focuses on reducing the hyperglycaemia driving the complications of GDM (Metzger 1998). In general, management includes any or all of: nutritional therapy, exercise, blood glucose monitoring and insulin therapy. The results from two large, multi-centred randomised controlled trials provide strong support for the treatment of women with mild GDM (Crowther 2005; Landon 2009). Crowther and colleagues reported reduced infant morbidity in those treated for GDM in addition to suggesting that maternal quality of life was improved by treatment. Landon and colleagues showed treatment for GDM reduced the risks of fetal overgrowth, shoulder dystocia and pre-eclampsia.

Medical nutrition therapy

The American Diabetes Association and Australasian Diabetes in Pregnancy Society, in line with other governing bodies, recommend nutrition therapy in the treatment of GDM (ADA 2003; ADA 2007; Hoffman 1998). Both guidelines focus on managing carbohydrate intake for blood glucose maintenance.

Exercise

Exercise is often used in conjunction with dietary therapy to maintain normal glucose levels. The Cochrane review ‘Exercise in diabetic pregnancy’ found that there was insufficient evidence to make a recommendation (Ceysens 2006). However, there is growing consensus on the safety of moderate exercise in pregnancy and its benefits in the treatment of GDM.

Blood glucose monitoring

Blood glucose monitoring is often recommended (ACOG 2001; Hoffman 1998). Postprandial hyperglycaemia monitoring demonstrates a closer association with rates of fetal macrosomia and obviously correlates with peaks of blood glucose (Hoffman 1998). Blood glucose monitoring provides the health professional with a representation of glycaemic control while providing the woman with feedback on her management progress.

Insulin/oral hypoglycaemic agents

Where the maternal hyperglycaemia cannot be managed by dietary or exercise advice and blood glucose levels remain elevated, insulin is added for greater control (Metzger 1998). The methods for administering insulin are discussed in the Cochrane review 'Continuous subcutaneous insulin infusion versus multiple daily injections of insulin for pregnant women with diabetes' (Farrar 2007). Oral hypoglycaemics such as glyburide (Langer 2000) and metformin (Rowan 2008) have been suggested as alternatives to insulin therapy.

Birth

The Cochrane review ‘Elective delivery in diabetic pregnant women’ suggested that induction of labour at 38 to 39 weeks may be suitable for diabetic women treated with insulin (Boulvain 2001).

Following pregnancy

It is recommended that women whose pregnancies were affected by GDM receive an OGTT between six and 12 weeks postpartum to detect diabetes (ACOG 2009; Berger 2002; Hoffman 1998; Metzger 2007; Oats 2004; RANZCOG 2008). Because of the high risk of future diabetes, these women are often advised to be retested on a regular basis (Hoffman 1998; Metzger 2007; Oats 2004; RANZCOG 2008).

Description of the intervention

Screening

A screening tool establishes the risk of disease in an otherwise well person (NSC 2007). Ordinarily, the presentation of symptoms prompts testing for disease. However, screening aims to identify the illness earlier, before symptoms arise. Identification of an illness by screening allows for earlier management, which may result in better health outcomes. While screening can be beneficial, it can also cause unnecessary anxiety due to the testing process itself. This is further complicated by the occurrence of false positives, where screening has suggested an increased risk for the disease but the diagnostic test does not show evidence of the disease.

An accepted screening process must first meet certain criteria (NSC 2003). In addition to the illness being an important health problem, the screening process must benefit the individual. This includes the acceptability of the screening process clinically, socially and ethically and the availability of an effective treatment. These benefits must outweigh any possible harms such as discomfort from any testing and costs of administering the screening process. From an economic perspective, the screening process must also be cost effective.

Screening does not always involve a clinical test, and may include, for example, a series of history questions. Furthermore, it is important to distinguish screening from diagnostic procedures which provide a diagnosis in an already symptomatic or high-risk individual. It is important to distinguish between a screening and diagnostic test. While a screening test will identify those at risk for a disease, diagnostic tests are generally designed to give a definitive yes or no. Diagnostic tests are also often more complex and expensive than screening tests.

While screening tools will identify those at risk of an illness, it is the subsequent management of the result that ultimately affects health outcomes. 'Screening' can be used to refer to an individual screening tool or to a screening program, protocol or guideline, which includes the screening tool and subsequent management such as diagnostic testing and treatment of any illness identified. By identifying individuals at high and low risk of a particular illness, a screening tool therefore identifies those who require diagnostic testing and those who do not. It therefore follows that the implementation of a screening program, which includes a combination of screening tool, subsequent diagnostic testing and management, is able to affect health outcome.

Screening for GDM

Whether to screen for GDM, and which methods to use, remain controversial. This is compounded by the lack of clearly defined, universally accepted screening criteria, and the uncertainty as to the severity of glucose intolerance at which treatment is beneficial. Even with screening protocols in place, GDM is diagnosed at the end of the second trimester or early third trimester based on physiology. This leaves little time for management of GDM. Without screening, the diagnosis of GDM, and therefore treatment, is potentially delayed.

Screening for GDM is often implemented despite the uncertainty of its utility. A wide variety of strategies have been employed in screening for GDM that provide varying degrees of sensitivity and specificity. Universal or routine screening, usually where all women are offered a 50 g OGCT, and risk factor screening (by women's history) are the most commonly used methods and combinations of these and other methods have been used to form various screening protocols (ACOG 2001; Gabbe 2004; Metzger 2007; Mires 1999; Rumbold 2001).

The OGCT was originally proposed by O’Sullivan and colleagues to provide a more sensitive screening process than risk factor screening (O'Sullivan 1973). An OGCT involves a 50 g glucose drink and a blood glucose measurement after one hour. While the predefined risk factors used vary between centres and countries, they commonly include maternal age, BMI, ethnicity, previous GDM and family history of diabetes mellitus (ADA 2003; Berger 2002; Hoffman 1998; Metzger 2007; USPSTF 2008). Other methods used to screen for GDM include urine testing for glucosuria, fructosamine testing, random plasma glucose measurements, fasting plasma glucose measurements and HbA1c (a measure of how well blood glucose has been controlled over the previous two to three months) (Scott 2002).

The variation in screening protocols is reflected in surveys conducted around the world. In a UK survey of obstetric units in 1996, it was found that 89% screened for GDM, with 81% of those units using risk factor based screening (Mires 1999). There was a lack of consensus on the appropriate screening method (Mires 1999). In a similar Australian survey of obstetric practice conducted in 1999, it was found that 87% of the obstetric population was being screened for GDM. Again there was no strong consensus on how to screen (Rumbold 2001). An American survey in 2004 found that 95.2% of obstetricians screening for GDM adopted a universal one-hour 50 g OGCT (Gabbe 2004). This diversity in preferred screening protocols may reflect a number of factors, such as the cost of screening, the expected prevalence of GDM and test accuracy, in addition to the lack of definitive evidence in favour of a particular screening protocol.

A largely accepted time for screening is the end of the second trimester, ranging between 24 to 28 weeks' gestation (ACOG 2001; Hoffman 1998; Metzger 2007; Oats 2004; RANZCOG 2008). This value reflects a balance between having adequate time to manage GDM and the ability to detect the development of carbohydrate intolerance (ACOG 2001; Brody 2003). There is little evidence on the benefits and detriments of screening prior to 24 weeks' gestation (USPSTF 2008).

The negative impact of screening for GDM also needs to be considered. The importance of identification of GDM should be weighed against any discomfort experienced by the woman and anxiety from testing. While the 50 g OGCT is considered to be a quick and simple test, it is unpleasant to drink and is associated with side effects such as dizziness, headaches, nausea and vomiting, and requires a blood test. For many women, the inconvenience of testing can be significant. Screening by any method can create anxiety for the mother, including women identified as having risk factors for GDM, those identified through routine OGCT and those with elevated random blood glucose levels. In particular, a false positive result has been associated with a decline in women's perception of health (Kerbel 1997; Rumbold 2002). It also follows that with the introduction of screening, that more women are offered diagnostic testing, usually an OGTT, which requires them to fast overnight, drink a higher glucose load, requires more blood tests and can take up to three hours to complete.

An evaluation of cost is imperative with any screening procedure. While screening processes may affect detection, management and therefore improve maternal and infant health, this must also be weighed against the cost of screening all pregnant women, any subsequent diagnostic tests and treatment for additional women diagnosed with GDM.

Why it is important to do this review

Many believe that the incidence of GDM, the adverse outcomes arising from GDM and the benefits of treatment suggest a need for some screening process. However, high-quality evidence demonstrating the effectiveness of screening on detection of GDM and subsequent maternal and infant health is required for screening to be implemented (NSC 2003). Whether a screening protocol adequately identifies those at risk of GDM, and whether this knowledge improves the health outcomes for women with GDM and their babies through subsequent management of a screening result, are important factors to consider when recommending a screening process. It is also equally important that a recommended screening protocol does not harm women without GDM. Moreover, given the lack of consensus on a method for screening, an evaluation of the different screening protocols on the detection of GDM and subsequent maternal and infant health is required.

This review updates a previously published Cochrane review on screening and subsequent management for GDM for improving maternal and infant health (Tieu 2010). The previous review included four randomised trials and found that there was insufficient evidence to determine if screening for GDM, or what types of screening, can improve maternal and infant health outcomes; and concluded that high-quality, large trials are required in this area.

This review update therefore aims to evaluate the current evidence regarding the effects of screening for GDM as an intervention on maternal and infant health. The evaluation of test performance of individual screening methods is not included in the scope of this review. The strategies for diagnosis of GDM have been evaluated in a separate Cochrane review 'Alternative strategies for glucose tolerance testing to diagnose gestational diabetes and impaired glucose tolerance during pregnancy' (Farrar 2011). The Cochrane review 'Treatments for gestational diabetes' (Alwan 2009) assesses management after diagnosis of GDM or impaired glucose tolerance and therefore is looking at a later stage in the pathways of care and management than this review which addresses the process from screening onwards

Objectives

To assess the effects of different methods of screening for gestational diabetes mellitus on maternal and infant outcomes.

Methods

Criteria for considering studies for this review

Types of studies

Randomised controlled trials, quasi-randomised controlled trials and cluster-randomised trials. We planned to exclude cross-over trials. We planned to include studies published as abstracts provided there was sufficient information to allow us to assess study eligibility and risk of bias. If sufficient information was not available, the study would await assessment pending the publication of the full trial report, or the provision of further information by trial authors.

Types of participants

Pregnant women, excluding women who have already been diagnosed with GDM in this pregnancy or who have pre-existing diabetes mellitus.

Types of interventions

Any individual screening tool or screening program, protocol or guideline for GDM compared with the absence of screening; or any individual screening tool or screening program, protocol or guideline for GDM with another.

Types of outcome measures

Primary outcomes
Maternal
Perinatal
  1. Diagnosis of GDM*;

  2. positive screen for GDM*;

  3. mode of birth (normal vaginal birth, operative vaginal birth, caesarean section).

Offspring
Neonatal
  1. Large-for-gestational age (birthweight greater than or equal to 90th percentile);

  2. macrosomia (greater than 4000 g or greater than 4500 g).

* as defined by author(s)

Secondary outcomes
Maternal
Perinatal
  1. Pre-eclampsia;

  2. induction of labour;

  3. perineal trauma;

  4. weight gain in pregnancy;

  5. augmentation of labour;

  6. insulin or oral hypoglycaemic agent required to treat GDM;

  7. women who screen positive and are not subsequently diagnosed with GDM;

  8. placental abruption;

  9. postpartum haemorrhage*;

  10. postpartum infection*;

  11. women's sense of well-being and quality of life*.

Long term
  1. Development of type II diabetes mellitus;

  2. GDM in subsequent pregnancy;

  3. development of type I diabetes mellitus;

  4. impaired glucose tolerance*;

  5. insulin sensitivity*;

  6. body mass index (BMI);

  7. BMI greater than 25;

  8. BMI greater than 30;

  9. women's sense of well-being and quality of life*.

Offspring
Neonatal
  1. Stillbirths;

  2. death of liveborn infants prior to hospital discharge;

  3. infant death (up to one year of life);

  4. shoulder dystocia;

  5. bone fractures;

  6. nerve palsy;

  7. birthweight;

  8. birth centile;

  9. ponderal index;

  10. gestational age at birth;

  11. preterm birth (less than 37 weeks' gestation);

  12. respiratory distress syndrome;

  13. hypoglycaemia requiring treatment;

  14. hyperbilirubinaemia requiring treatment;

  15. five minute Apgar score less than seven;

  16. five minute Apgar score less than four.

Childhood
  1. BMI;

  2. BMI greater than 25;

  3. BMI greater than 30;

  4. weight;

  5. height;

  6. fat mass/fat-free mass;

  7. skinfold thickness measurements;

  8. blood pressure;

  9. impaired glucose tolerance*;

  10. type I diabetes;

  11. type II diabetes;

  12. insulin sensitivity*;

  13. dyslipidaemia.

Adulthood
  1. BMI;

  2. BMI greater than 25;

  3. BMI greater than 30;

  4. weight;

  5. height;

  6. fat mass/fat-free mass;

  7. skinfold thickness measurements;

  8. blood pressure;

  9. impaired glucose tolerance*;

  10. type I diabetes;

  11. type II diabetes;

  12. insulin sensitivity*;

  13. dyslipidaemia;

  14. educational achievement.

Acceptability of testing
  1. Adverse effects of testing (e.g. nausea, vomiting);

  2. women's acceptance of screening protocol*.

Costs
  1. Cost of screening each woman;

  2. number of hospital visits/antenatal visits for mother;

  3. dietitian visits;

  4. medical physician visits;

  5. length of postnatal stay (mother);

  6. length of postnatal stay (baby);

  7. cost of maternal care;

  8. cost of offspring care.

* as defined by author(s)

Search methods for identification of studies

Electronic searches

We contacted the Trials Search Co-ordinator to search the Cochrane Pregnancy and Childbirth Group’s Trials Register (1 December 2013).

The Cochrane Pregnancy and Childbirth Group’s Trials Register is maintained by the Trials Search Co-ordinator and contains trials identified from: 

  1. quarterly searches of the Cochrane Central Register of Controlled Trials (CENTRAL);

  2. weekly searches of MEDLINE;

  3. weekly searches of Embase;

  4. handsearches of 30 journals and the proceedings of major conferences;

  5. weekly current awareness alerts for a further 44 journals plus monthly BioMed Central email alerts.

Details of the search strategies for CENTRAL, MEDLINE and Embase, the list of handsearched journals and conference proceedings, and the list of journals reviewed via the current awareness service can be found in the ‘Specialized Register’ section within the editorial information about the Cochrane Pregnancy and Childbirth Group

Trials identified through the searching activities described above are each assigned to a review topic (or topics). The Trials Search Co-ordinator searches the register for each review using the topic list rather than keywords.  

We did not apply any language restrictions.

Data collection and analysis

For methods used in the previous version, please see Tieu 2010.

For this update, the following methods were used.

Selection of studies

Two review authors independently assessed for inclusion all the potential studies we identified as a result of the search strategy. We resolved any disagreement through discussion or, if required, we consulted a third review author.

Data extraction and management

We designed a form to extract data. For eligible studies, two review authors extracted the data using the agreed form. We resolved discrepancies through discussion or, if required, we consulted a third review author. We entered data into Review Manager software (RevMan 2012) and checked for accuracy.

When information regarding any of the above was unclear, we attempted to contact authors of the original reports to provide further details.

Assessment of risk of bias in included studies

Two review authors independently assessed risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We resolved any disagreement by discussion or by involving a third author.

(1) Random sequence generation (checking for possible selection bias)

We described for each included study the methods used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups.

We assessed the methods as:

  • low risk of bias (any truly random process, e.g. random number table; computer random number generator);

  • high risk of bias (any non-random process, e.g. odd or even date of birth; hospital or clinic record number);

  • unclear risk of bias.

(2) Allocation concealment (checking for possible selection bias)

We described for each included study the method used to conceal the allocation sequence and determined whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment.

We assessed the methods as:

  • low risk of bias (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes);

  • high risk of bias (open random allocation; unsealed or non-opaque envelopes, alternation; date of birth);

  • unclear risk of bias.

(3.1) Blinding of participants and personnel (checking for possible performance bias)

We described for each included study, the methods, if any, used to blind study participants and personnel from knowledge of which intervention a participant received. We considered studies to be at a low risk of bias if they were blinded, or if we judged that the lack of blinding would be unlikely to affect results. We assessed blinding separately for different outcomes or classes of outcomes.

We assessed the methods as:

  • low, high or unclear risk of bias for participants;

  • low, high or unclear risk of bias for personnel.

(3.2) Blinding of outcome assessment (checking for possible detection bias)

We described for each included study the methods used, if any, to blind outcome assessors from knowledge of which intervention a participant received. We assessed blinding separately for different outcomes or classes of outcomes.

We assessed methods used to blind outcome assessment as:

  • low, high or unclear risk of bias.

(4) Incomplete outcome data (checking for possible attrition bias due to the amount, nature and handling of incomplete outcome data)

We described for each included study and for each outcome or class of outcomes, the completeness of data including attrition and exclusions from the analysis. We stated whether attrition and exclusions were reported, the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information was reported or was supplied by the trial authors, we included missing data in the analyses which we undertook.

We assessed the methods as:

  • low risk of bias (e.g. where there were no missing data or where reasons for missing data were balanced across groups);

  • high risk of bias (e.g. numbers or reasons for missing data imbalanced across groups; 'as treated' analysis done with substantial departure of intervention received from that assigned at randomisation);

  • unclear risk of bias.

(5) Selective reporting bias (checking for reporting bias)

We described for each included study how the possibility of selective outcome reporting bias was examined by us and what we found.

We assessed the methods as:

  • low risk of bias (where it was clear that all of the study’s pre-specified outcomes and all expected outcomes of interest to the review had been reported);

  • high risk of bias (where not all the study’s pre-specified outcomes had been reported; one or more reported primary outcomes were not pre-specified; outcomes of interest were reported incompletely and so could not be used; study failed to include results of a key outcome that would have been expected to have been reported);

  • unclear risk of bias.

(6) Other sources of bias (checking for bias due to problems not covered by (1) to (5) above)

We described for each included study any important concerns we had about other possible sources of bias. We assessed whether each study was free of other problems that could put it at risk of bias:

  • low risk of other bias;

  • high risk of other bias;

  • unclear whether there is risk of other bias.

(7) Overall risk of bias

We made explicit judgements about whether studies were at a high risk of bias, according to the criteria given in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). With reference to (1) to (6) above, we assessed the likely magnitude and direction of the bias and whether we considered it is likely to impact on the findings. We planned to explore the impact of the level of bias through undertaking sensitivity analyses - see Sensitivity analysis.

Measures of treatment effect

Dichotomous data

For dichotomous data, we presented results as risk ratio with 95% confidence intervals.

Continuous data

For continuous data, we used the mean difference when outcomes were measured in the same way between trials. If necessary, we would have used the standardised mean difference to combine trials that measured the same outcome, but used different methods.

Unit of analysis issues

Cluster-randomised trials

We planned to include cluster-randomised trials in the analyses along with individually-randomised trials. We planned to adjust their sample sizes using the methods described in the Handbook using an estimate of the intracluster correlation co-efficient (ICC) derived from the trial (if possible), from a similar trial or from a study of a similar population. If we had used ICCs from other sources, we planned to report this and conduct sensitivity analyses to investigate the effect of variation in the ICC. If we had identified both cluster-randomised trials and individually-randomised trials, we planned to synthesise the relevant information. We would have considered it reasonable to combine the results from both if there was little heterogeneity between the study designs and the interaction between the effect of intervention and the choice of randomisation unit was considered to be unlikely.

We planned to also acknowledge heterogeneity in the randomisation unit and perform a sensitivity analysis to investigate the effects of the randomisation unit.

Cross-over trials

We considered cross-over trials inappropriate for this research question.

Dealing with missing data

For included studies, we noted levels of attrition. We planned to explore the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis.

For all outcomes, we carried out analyses, as far as possible, on an intention-to-treat basis, i.e. we attempted to include all participants randomised to each group in the analyses, and all participants were analysed in the group to which they were allocated, regardless of whether or not they received the allocated intervention. The denominator for each outcome in each trial was the number randomised minus any participants whose outcomes were known to be missing.

Assessment of heterogeneity

We assessed statistical heterogeneity in each meta-analysis using the Tau², I² and Chi² statistics. We regarded heterogeneity as substantial where the I² was greater than 30% and either the Tau² was greater than zero, or there was a low P value (less than 0.10) in the Chi² test for heterogeneity.

Assessment of reporting biases

In future updates of this review, if there are 10 or more studies in the meta-analysis, we will investigate reporting biases (such as publication bias) using funnel plots. We will assess funnel plot asymmetry visually. If asymmetry is suggested by a visual assessment, we will perform exploratory analyses to investigate it.

Data synthesis

We carried out statistical analysis using the Review Manager software (RevMan 2011). We used fixed-effect meta-analysis for combining data where it was reasonable to assume that studies were estimating the same underlying treatment effect: i.e. where trials were examining the same intervention, and the trials’ populations and methods were judged sufficiently similar. Where there was clinical heterogeneity sufficient to expect that the underlying treatment effects differed between trials, or where substantial statistical heterogeneity was detected, we used random-effects meta-analysis to produce an overall summary, if an average treatment effect across trials was considered clinically meaningful. The random-effects summary was treated as the average range of possible treatment effects and we have discussed the clinical implications of treatment effects differing between trials. If the average treatment effect was not clinically meaningful, we would not have combined trials.

Where we have used random-effects analyses, we have presented the results as the average treatment effect with its 95% confidence interval, and the estimates of Tau² and I²

Subgroup analysis and investigation of heterogeneity

If we had identified substantial heterogeneity, we planned to investigate it using subgroup analyses and sensitivity analyses. We planned to consider whether an overall summary was meaningful, and if it was, use random-effects analysis to produce it.

We planned an assessment of trials comparing any screening protocol with none, with data analysed separately for different methods of screening. We analysed trials comparing one method of screening with another, with data from different comparisons analysed separately.

We planned to carry out the following subgroup analyses for primary outcomes:

  • high risk for GDM (variously defined) (we will explore risk factors individually if sufficient data become available);

  • gestational age at screening (less than 24 weeks, 24 to 30 weeks, 30 weeks or more);

  • number of stages in the screening protocol;

  • type of management protocol.

There were insufficient data to conduct subgroup analyses.

We planned to assess subgroup differences by interaction tests available in within RevMan (RevMan 2012). We planned to report the results of the subgroup analysis quoting the Chi² statistic and P value, and the interaction test I² value.

Sensitivity analysis

We planned to carry out sensitivity analysis to explore the effect of trial quality assessed by concealment of allocation, by excluding studies with clearly inadequate allocation of concealment (rated high risk of bias).

We planned to then carry out sensitivity analysis to explore the effect of trial quality on primary outcomes. This would have involved analysis based on an assessment of selection bias and attrition bias. We planned to exclude studies of poor quality in the analysis (those rating unclear or high risk) in order to assess for any substantive difference in the overall result.

There were insufficient data to conduct sensitivity analyses.

Results

Description of studies

Results of the search

The updated search of the Cochrane Pregnancy and Childbirth Group’s Trials Register identified three studies (one which was awaiting assessment in the previous version of this review). We have excluded the three studies, and have therefore not included any new trials in this update.

In the previous version of this review, the search identified 31 trials to be considered for inclusion. Following application of eligibility criteria, we included four of these trials in this review (Bergus 1992; Griffin 2000; Martinez Collado 2003; Murphy 1994); we excluded 25, and one remains awaiting classification (Bebbington 1999).

Included studies

One quasi-randomised study compared the effect of screening by risk factors and universal (routine) screening by a 50 g oral glucose challenge test (OGCT) on health outcomes (Griffin 2000). Three studies compared screening by different glucose loading methods (Bergus 1992; Martinez Collado 2003; Murphy 1994). Of the four studies, Griffin 2000 was the largest study with 3742 women enrolled in the study. Murphy 1994 recruited 124 women, Bergus 1992 enrolled 76 women into the study and Martinez Collado 2003 included 30 women.

Participants

All studies included pregnant women in Western societies. Bergus 1992 and Murphy 1994 were conducted in the United States, while Griffin 2000 took place in Ireland and Martinez Collado 2003 recruited women in Mexico. In all studies, women were recruited from obstetric clinics. Gestational age at entry was specified in Bergus 1992 and Martinez Collado 2003, where women were between 24 and 28 weeks' gestation. Murphy 1994 screened women routinely at 24 to 28 weeks' gestation and also screened women at their first antenatal visit if they were found to have one of the following risk factors for GDM: past history of glucose intolerance, first-degree relative with diabetes mellitus, age greater than 35 years, previous baby with macrosomia, habitual abortion, unexplained stillbirth, congenital anomalies, current pregnancy with glycosuria, hypertension, suspected large-for-gestational-age fetus, polyhydramnios or obesity. Martinez Collado 2003 included women with a 'high-risk' pregnancy, although a description of 'high risk' was not reported. This trial excluded women with diabetes, previously diagnosed GDM and those treated with steroids or tocolytics. No other exclusion criteria were listed for the studies.

Baseline characteristics of the participants by treatment group were compared in two studies (Griffin 2000; Murphy 1994). In Murphy 1994, there was an imbalance in age and parity at screening with participants in the candy bar group being younger and having a lower parity than those in the d-glucose group. No baseline imbalances were reported between women in the candy bar group and the polymer group. Participants in the risk factor group and universal group in Griffin 2000 were similar with respect to age, weight at 36 weeks, BMI, gestational age at delivery, parity and prevalence of risk factors for GDM.

Interventions
Risk factor versus universal (routine) screening

Griffin 2000 compared risk factor screening with universal (routine) screening. Participants in the risk factor group of Griffin 2000 were screened on the basis of historical and current risk factors, including having a first-degree relative with diabetes mellitus, weighing more than 100 kg in the current pregnancy, having a previous baby greater than 4.5 kg, previous unexplained stillbirth or intrauterine death, previous major malformation, previous GDM, glycosuria in second fasting urine sample, macrosomia in the current pregnancy and polyhydramnios in the current pregnancy. Women received glucose testing by a 100 g oral glucose tolerance test (OGTT) at 32 weeks' gestation where they were found to have any of the risk factors listed.

The universal screening group used a 50 g OGCT at 26 to 28 weeks' gestation. A one-hour plasma glucose of greater than or equal to 7.8 mmol/L was considered positive. A positive screening test was an indication for a full 100 g OGTT using the National Diabetes Data Group criteria for diagnosis. The 50 g OGCT was repeated in those with a negative OGCT and with risk factors for GDM four to six weeks after the initial OGCT.

Women who were diagnosed with GDM were treated by standard diabetes management, maintaining otherwise similar antenatal care for both groups. Griffin 2000 referred women for obstetric and endocrinology review fortnightly and weekly after 36 weeks' gestation, with treatment including diabetic diet and insulin as required.

Glucose method

Bergus 1992, Martinez Collado 2003 and Murphy 1994 compared different methods of glucose loading as screening tests for GDM. Both Bergus 1992 and Murphy 1994 assessed solutions of glucose monomer (d-glucose) and glucose polymer. Murphy 1994 included an additional group where participants ate 50 g chocolate bars in place of a glucose drink. In both studies, all women underwent a glucose tolerance test within three to seven days of their 50 g challenge test. Both used a 100 g OGTT by O'Sullivan criteria to diagnose GDM. Martinez Collado 2003 compared a 50 g glucose solution with a food mix, which included 50 g of glucose, and did not report on further testing to diagnose GDM. It is not reported whether the glucose solution was a glucose monomer or polymer.

Outcomes

Griffin 2000 reported clinical measures of maternal health outcome and infant health outcome and size. Bergus 1992, Martinez Collado 2003 and Murphy 1994 focused primarily on the efficiency of the methods by which glucose was administered, reporting on diagnosis of GDM, glucose levels following testing and the adverse effects of the different methods. Murphy 1994 reported side effects only where they were rated moderate to severe by women on a five-point scale.

Excluded studies

Eighteen studies identified by the literature search assessed strategies for diagnosis of GDM rather than screening (Berkus 1995; Brustman 1995; Buhling 2004; Cheng 1992; Court 1984; Court 1985; Duenas-Garcia 2011; Fung 1993; Harlass 1991; Jones 1993; Meltzer 2010; Olarinoye 2004; Saijan 2011; Sammarco 1993; Soonthornpun 2003; Stavrianos 2004; Weiss 1998; Zhang 1995). One study was not randomised (Dornhorst 2000). Seven of the trials identified were cross-over studies (Eslamian 2007; Eslamian 2008; Helton 1989; Hidar 2001; Lamar 1999a; Lamar 1999b; Soonthornpun 2008) and two studies included women who had already undergone diagnostic testing for GDM (Kjos 2001; Lewis 1993).

Risk of bias in included studies

Please see Figure 1 and Figure 2 for summaries of all 'Risk of bias' assessments.

Figure 1.

Methodological quality graph: review authors' judgements about each methodological quality item presented as percentages across all included studies.

Figure 2.

Methodological quality summary: review authors' judgements about each methodological quality item for each included study.

Allocation

The generation of randomisation sequence was specified only by Bergus 1992. Bergus 1992 used consecutive numbers from a random number table to allocate participants to study group while Griffin 2000 was quasi-randomised, allocating women to study group by the day of their clinic visit. While reported as randomised controlled trials, Martinez Collado 2003 and Murphy 1994 did not specify the method of allocation of participants.

None of the studies reported allocation concealment.

Blinding

Bergus 1992 describes a 'double-blind design', but did not specifically state who was blinded. Griffin 2000, Martinez Collado 2003 and Murphy 1994 did not report on blinding of participants, clinicians or outcome assessors.

Incomplete outcome data

Ten out of 76 women (13%) did not complete the symptom questionnaire in Bergus 1992 and it is reported that their baseline characteristics were comparable to those who were followed up. Griffin 2000 reported that 590, or 31%, of the women in the universal screening group did not consent to glucose challenge testing and were excluded from analysis. No participants in the risk factor screening group were lost to follow-up. Routine care in this centre was risk factor screening, which contributes to the differential loss to follow-up rate. There were no significant differences between those who consented to glucose challenge testing and those who did not in Griffin 2000. Sixteen women in Murphy 1994 were lost to follow-up. However, no comparison of baseline characteristics of those lost to follow-up and those who remained in the study was made and it is unclear which groups these women were from. It is also uncertain as to how many women in Murphy 1994 were being screened in their first trimester or at 24 to 28 weeks' gestation.

Selective reporting

Outcome data in Griffin 2000 was analysed primarily by GDM diagnosis rather than by original group allocation by day of visit, which affects the ability to interpret results of pre-specified outcomes. Although a comparison of baseline characteristics between women who were able or unable to complete the symptom questionnaire was made, Bergus 1992 did not report the baseline characteristics of participants by intervention group. Murphy 1994 only reported side effects of testing where women had rated their symptoms as moderate or severe, equivalent to a three to five out of a possible five. Mild symptoms were unreported.

Other potential sources of bias

Analysis of Griffin 2000 was based on diagnosis of GDM rather than original group allocation by day of visit. Because no baseline comparison of the intervention groups was made in Bergus 1992 and Martinez Collado 2003, it is uncertain whether or not baseline imbalances are present.

Overall risk of bias

In general, assessment of the included studies for methodological quality revealed a moderate to high risk of bias, which is likely to have affected the results of the review (Figure 1; Figure 2) by making the results of trials less certain. Most studies were unclear or did not adequately report on sequence generation, allocation concealment and blinding. Missing data affected the assessment of incomplete outcome data, and selective reporting and other biases were also likely.

Effects of interventions

We included four studies (Bergus 1992; Griffin 2000; Martinez Collado 2003; Murphy 1994), with data available from 3382 of the 3972 women randomised. One study compared risk factor screening with routine screening (Griffin 2000) and three trials compared the method of glucose administration at screening (Bergus 1992; Martinez Collado 2003; Murphy 1994).

Risk factor versus routine screening

Primary outcomes

Significantly more women were diagnosed with GDM in the universal screening group than in the risk factor screening group (Griffin 2000). Thirty-five women were diagnosed with GDM in the routine screening group compared with 22 in the risk factor group (one trial, 3152 women, risk ratio (RR) 0.44, 95% confidence interval (CI) 0.26 to 0.75) (Analysis 1.1).

The Griffin 2000 trial did not report on the other primary outcomes including: positive screen for GDM, mode of birth, large-for-gestational age and macrosomia.

Secondary outcomes

Infants of mothers in the risk factor screening group were born significantly earlier than infants of mothers in the routine screening group (one trial, 3152 women, mean difference (MD) -0.15 weeks, 95% CI -0.27 to -0.03) (Analysis 1.2).

The remaining data from this trial were reported according to diagnosis of GDM and we have been in correspondence with the authors of this paper for additional data. Therefore, we have not been able to report data on any of the review's other secondary outcomes from this trial.

Glucose monomer versus glucose polymer

Primary outcomes

Two studies, Bergus 1992 and Murphy 1994, compared a glucose monomer (d-glucose) with a glucose polymer drink for screening for GDM.

No women were diagnosed with GDM in either group in Bergus 1992. Three women in the glucose monomer group and two women in the glucose polymer group were diagnosed with GDM in Murphy 1994. There was no significant difference in GDM diagnosis between groups overall (two trials, 161 women, RR 1.61, 95% CI 0.28 to 9.15) (Analysis 2.1). Numbers of women screening positive also showed no significant differences between groups in one trial (85 women, RR 2.36, 95% CI 0.90 to 6.21) (Analysis 2.2).

These trials did not report on the other primary outcomes including: mode of birth, large-for-gestational age and macrosomia.

Secondary outcomes

Both trials reported a number of side effects from the method of glucose administration. Although not pre-specified, any symptom, sick, tired, taste and bloating were included as measures of acceptability of testing. Women in the glucose monomer group were significantly more likely to experience 'any symptom' than those in the glucose polymer group (two trials, 151 women, RR 2.80, 95% CI 1.10 to 7.13). There was significant heterogeneity in this result, with an I² value of 61%, and thus a random-effects meta-analysis was used (Analysis 2.3). Nausea was experienced significantly more often by women in the glucose monomer group than glucose polymer (two trials, 151 women, RR 2.62, 95% CI 1.01 to 6.79). No statistically significant differences were found for all other measures of acceptability of testing, including: dizziness and abdominal discomfort (both trials); bloating (Murphy 1994); headache, vomiting, sickness and tiredness (Bergus 1992); or taste (Murphy 1994) (Analysis 2.4).

Neither study reported on additional maternal or infant secondary review outcomes.

Glucose monomer versus candy bar

Primary outcomes

Murphy 1994 included a third group of women, who consumed a chocolate bar as an alternative to the two types of glucose drinks. There was no significant difference in diagnosis of GDM between the candy bar and glucose monomer groups, with three women diagnosed with GDM in the glucose monomer group, compared with none in the candy bar group (one trial, 80 women, RR 6.67, 95% CI 0.36 to 125.02) (Analysis 3.1). However, significantly more women in the monomer group screened positive for GDM (RR 3.49, 95% CI 1.05 to 11.57) (Analysis 3.2).

This trial did not report on the other primary outcomes including: mode of birth, large-for-gestational age and macrosomia.

Secondary outcomes

The candy bar was given the highest rating for taste significantly more often than glucose monomer (one trial, 80 women, RR 0.35, 95% CI 0.17 to 0.74) (Analysis 3.3). No significant differences were seen overall (RR 1.90, 95% CI 0.97 to 3.72) or for each individual symptom of dizziness, nausea, abdominal discomfort and bloating (Analysis 3.4).

No other maternal or infant secondary review outcomes were reported by this trial.

Glucose polymer versus candy bar

Primary outcomes

No significant difference was found in diagnosis of GDM between the two groups (glucose polymer versus candy bar) (one trial, 83 women, RR 4.44, 95% CI 0.22 to 89.84) (Analysis 4.1) or for screening positive (RR 1.48, 95% CI 0.38 to 5.78) (Analysis 4.2).

This trial did not report on the other primary outcomes including: mode of birth, large-for-gestational age and macrosomia.

Secondary outcomes

Again, the candy bar was preferred for taste significantly more often than the glucose polymer drink (one trial, 83 women, RR 0.42, 95% CI 0.22 to 0.82) (Analysis 4.3). Other measures of acceptability of testing were not significantly different between the two groups (RR 0.39, 95% CI 0.13 to 1.18) (Analysis 4.4).

No other maternal or infant secondary review outcomes were reported by this trial.

Glucose solution versus food

Primary outcomes

In one trial (Martinez Collado 2003), there was no significant difference in having a positive screening test for GDM between the two glucose solution and food mix groups (30 women, RR 7.00, 95% CI 0.39 to 124.83) (Analysis 5.1).

This trial did not report on the other primary outcomes including: diagnosis of GDM, mode of birth, large-for-gestational age and macrosomia.

Secondary outcomes

Women receiving the glucose solution were more likely to experience a side effect of the screening, including nausea, vomiting, migraine, diarrhoea and feeling sick, than those receiving the food mix (80% versus 7% for 'any symptom', one trial, 30 women, RR 12.00, 95% CI 1.78 to 81.06) (Analysis 5.2).

No other maternal or infant secondary review outcomes were reported by this trial.

There were insufficient data to perform subgroup analyses or sensitivity analyses for all comparisons of the review.

Discussion

Gestational diabetes mellitus (GDM) is widely accepted as a serious health issue, associated with serious maternal and infant morbidity. Recent, high-quality evidence exists to suggest that treatment of GDM is beneficial (Crowther 2005; Landon 2009). The variation in screening practices and guidelines, both in national surveys and worldwide, further demonstrates the need for large, high-quality trials evaluating the effect of screening for GDM (ACOG 2001; ADA 2003; CDA 2008; Gabbe 2004; Hanna 2008; Mires 1999; NICE 2008; Oats 2004; RANZCOG 2008; Rumbold 2001). Despite its use, this review found little evidence on the effect of screening on maternal and infant health outcomes. This is consistent with other reviews on screening for GDM (Hillier 2008; Hollander 2007; NICE 2008; Scott 2002).

We included four trials evaluating various methods of screening for GDM, which can be considered in two categories. Griffin 2000 evaluated different screening protocols. Bergus 1992, Martinez Collado 2003 and Murphy 1994 compared different types of glucose for a 50 g OGCT.

Griffin 2000 was a large quasi-randomised trial comparing universal screening by 50 g OGCT with risk factor screening and reported on diagnosis of GDM, positive screening for GDM and gestational age at birth. Of the 1299 women in the universal screening group who completed an OGCT, 366 were referred for an oral glucose tolerance test (OGTT). By comparison, fewer women (249 of the 1853 women in the risk factor group) were referred for an OGTT. Unsurprisingly, with more women offered diagnostic testing for GDM in the universal screening group, more women were diagnosed with GDM. It is, however, difficult to interpret how these increases in diagnoses and subsequent management translate to clinical maternal and infant health outcomes in the review. The marginal reduction seen in gestational age at birth is likely a result of the large sample size rather than a clinically relevant difference. The trial reported on the remaining health outcome data with women reorganised into three groups, those who were not diagnosed with GDM, women who were diagnosed with GDM from the universal screening group and those diagnosed with GDM in the risk factor screening group.

While more women received glucose testing in the universal screening group, compared to those in the risk factor group, Griffin 2000 did not report on women's views on the two forms of screening. In addition to side effects of receiving a glucose load, practical issues for testing and the anxiety from screening and false positive results, the anxiety created by receiving an abnormal result on screening compared with receiving information on background risk of GDM is also important in selecting an appropriate screening protocol. Women's views on their health status and the screening protocol would be further affected by whether or not they are subsequently diagnosed and managed for GDM. Given that some screening protocols will result in more women being diagnosed with GDM than others, this may influence women's views on their health status.

Furthermore, although management of diagnosed GDM improves maternal and infant health outcomes, the diagnosis of GDM may also be associated with increased intervention or monitoring such as induction of labour and neonatal intensive care unit admission (Alwan 2009). Therefore, with various protocols for screening, the subsequent management of women with a positive or negative screening result as part of these protocols may impact on maternal and infant health. Large studies are required to address these issues and given that only a proportion of women are subsequently diagnosed with GDM, these trials require sufficient power for subgroup analyses by diagnosis of GDM are meaningful.

Interestingly, women in the risk factor group with risk factors for GDM received an oral glucose tolerance test at 32 weeks. Women in the universal screening group underwent a glucose challenge test at 26 to 28 weeks' gestation and were referred for subsequent OGTT if this was positive. Further to this, if glucose testing was negative, repeat screening was performed where the woman had risk factors for GDM. The risk factor group is therefore more likely to be diagnosed at a later stage in pregnancy than those in the universal screening group. It is unclear, however, if the timing of glucose testing has affected health outcomes.

The trials (Bergus 1992; Martinez Collado 2003; Murphy 1994) evaluating different types of glucose for the challenge test were primarily interested in the side effects and number of women diagnosed by different forms of glucose. Therefore, unlike Griffin 2000, the women in these trials were all offered the same diagnostic testing pathway regardless of the screening result. Although no health outcome data were included in the review, data on health outcome would be unlikely to be affected by the screening test because the women received the same subsequent management.

Bergus 1992 and Murphy 1994 included a comparison of glucose monomer (d-glucose) and glucose polymer. Overall, fewer side effects were reported by women receiving a glucose polymer drink than glucose monomer. There was, however, significant heterogeneity in this result, with a stronger effect seen in Murphy 1994 than Bergus 1992. This may be explained by the different approaches taken by the trials, with Murphy 1994 only reporting side effects where they were rated moderate to severe. Bergus 1992 however used a binary approach. The differences in data presentation therefore limit interpretation of these outcomes. Maternal and infant health outcomes were not recorded by the trials. Although not statistically significant, the glucose polymer group generally reported fewer side effects in the moderate to severe range than the candy bar group.

Interpretation of the results of this arm of the review are, however, limited by the number of participants in each trial. Although women were screened at 24 to 28 weeks' gestation in the trials, Murphy 1994 also included women in their first trimester with risk factors for GDM and Martinez Collado 2003 included women with a 'high-risk' pregnancy. Both trials used a 100 g OGTT for diagnosis of GDM.

The results of this review were limited by the number of participants and methodological quality of the trials, which, overall, was assessed to be moderate to low. Therefore, the results of this review are to be interpreted with caution. Bergus 1992, Martinez Collado 2003 and Murphy 1994 included a total of 230 women and were both primarily interested in the side effects and numbers of women diagnosed by different forms of glucose. As a consequence, most of the maternal and infant health outcomes included in this review were not reported by these trials. While Griffin 2000 was a large quasi-randomised trial enrolling 3792 women, the format of outcome reporting precluded the outcome data of interest for this review from being included.

The trials included in this review were conducted in the United States, Ireland and Mexico. Geographical location, socio-economic circumstances and ethnicity are important factors that can alter the most appropriate method of screening with regard to feasibility and practicality. Compliance is probably not only related to side effects, as investigated by Bergus 1992, Martinez Collado 2003 and Murphy 1994, but also the requirements for the screening protocol. For example, the inconvenience posed by a one-hour 50 g OGCT should be considered against random capillary blood glucose testing or risk factor screening. This emphasises the need for future research to report not only on subsequent management and maternal and infant health outcomes, but also on the acceptability of and adherence to particular screening protocols.

One trial (Bebbington 1999) published as an abstract, and awaiting assessment, also compared universal and selected screening in 2401 women with no reported risk factors for GDM. In abstract form, there were insufficient data to include results in the review. The abstract reports no significant difference in birthweight and the incidence of macrosomia between the two groups.

Authors' conclusions

Implications for practice

There was insufficient evidence from this review to determine the effects of screening for GDM and its subsequent management, or the comparative effects of different protocols for screening. Although women who were routinely screened by 50 g glucose challenge testing were more likely to be diagnosed with GDM than those screened by their risk factors, effects of subsequent management on health outcome are unclear.

Implications for research

Large, high-quality trials are required to evaluate the effects of screening and subsequent management of GDM. As only a proportion of women will be subsequently diagnosed with GDM in these trials, a large number of participants is required for sufficient power to detect statistically significant differences and subgroup analyses by diagnosis. Future studies should assess the value of screening compared with no screening in addition to comparing different types of screening tools. The 50 g oral glucose challenge test and screening tools that are more easily implemented such as risk factor screening, glucosuria and the use of capillary blood glucose testing need to be evaluated as part of screening protocols. Furthermore, assessment of the optimal gestational age for screening is required. Trials should include data on health outcomes for mother and baby, acceptability of the screening protocol and cost effectiveness.

Acknowledgements

We thank Emily Bain, Australian Research Centre for Health of Women and Babies, The University of Adelaide, for her support for updating this review.

We thank Dr George Bergus for contributing extra information and clarification on Bergus 1992. We also acknowledge the efforts of Dr Richard Firth and Dr Michael Bebbington in locating extra data.

The National Institute for Health Research (NIHR) is the largest single funder of the Cochrane Pregnancy and Childbirth Group. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the NIHR, NHS or the Department of Health.

Data and analyses

Download statistical data

Comparison 1. Risk factor versus universal screening
Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size
1 Diagnosis of gestational diabetes13152Risk Ratio (M-H, Fixed, 95% CI)0.44 [0.26, 0.75]
2 Gestational age at birth13152Mean Difference (IV, Fixed, 95% CI)-0.15 [-0.27, -0.03]
Analysis 1.1.

Comparison 1 Risk factor versus universal screening, Outcome 1 Diagnosis of gestational diabetes.

Analysis 1.2.

Comparison 1 Risk factor versus universal screening, Outcome 2 Gestational age at birth.

Comparison 2. Glucose monomer versus glucose polymer
Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size
1 Diagnosis of gestational diabetes2161Risk Ratio (M-H, Fixed, 95% CI)1.61 [0.28, 9.15]
2 Positive screen for gestational diabetes185Risk Ratio (M-H, Fixed, 95% CI)2.36 [0.90, 6.21]
3 Symptoms2 Risk Ratio (M-H, Random, 95% CI)Subtotals only
3.1 Any symptom2151Risk Ratio (M-H, Random, 95% CI)2.80 [1.10, 7.13]
3.2 Headache166Risk Ratio (M-H, Random, 95% CI)5.0 [0.62, 40.51]
3.3 Dizziness2151Risk Ratio (M-H, Random, 95% CI)2.50 [0.93, 6.76]
3.4 Nausea2151Risk Ratio (M-H, Random, 95% CI)2.62 [1.01, 6.79]
3.5 Abdominal discomfort2151Risk Ratio (M-H, Random, 95% CI)6.15 [0.76, 50.08]
3.6 Vomiting166Risk Ratio (M-H, Random, 95% CI)0.0 [0.0, 0.0]
3.7 Sick166Risk Ratio (M-H, Random, 95% CI)9.00 [0.50, 160.78]
3.8 Tired166Risk Ratio (M-H, Random, 95% CI)0.75 [0.18, 3.09]
3.9 Bloating185Risk Ratio (M-H, Random, 95% CI)11.79 [0.67, 206.69]
4 Taste185Risk Ratio (M-H, Fixed, 95% CI)0.83 [0.34, 2.04]
Analysis 2.1.

Comparison 2 Glucose monomer versus glucose polymer, Outcome 1 Diagnosis of gestational diabetes.

Analysis 2.2.

Comparison 2 Glucose monomer versus glucose polymer, Outcome 2 Positive screen for gestational diabetes.

Analysis 2.3.

Comparison 2 Glucose monomer versus glucose polymer, Outcome 3 Symptoms.

Analysis 2.4.

Comparison 2 Glucose monomer versus glucose polymer, Outcome 4 Taste.

Comparison 3. Glucose monomer versus candy bar
Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size
1 Diagnosis of gestational diabetes180Risk Ratio (M-H, Fixed, 95% CI)6.67 [0.36, 125.02]
2 Positive screen for gestational diabetes180Risk Ratio (M-H, Fixed, 95% CI)3.49 [1.05, 11.57]
3 Taste180Risk Ratio (M-H, Fixed, 95% CI)0.35 [0.17, 0.74]
4 Symptoms1 Risk Ratio (M-H, Fixed, 95% CI)Subtotals only
4.1 Any symptom180Risk Ratio (M-H, Fixed, 95% CI)1.90 [0.97, 3.72]
4.2 Dizziness180Risk Ratio (M-H, Fixed, 95% CI)1.66 [0.53, 5.24]
4.3 Nausea180Risk Ratio (M-H, Fixed, 95% CI)0.71 [0.17, 2.99]
4.4 Abdominal discomfort180Risk Ratio (M-H, Fixed, 95% CI)6.67 [0.36, 125.02]
4.5 Bloating180Risk Ratio (M-H, Fixed, 95% CI)1.19 [0.34, 4.11]
Analysis 3.1.

Comparison 3 Glucose monomer versus candy bar, Outcome 1 Diagnosis of gestational diabetes.

Analysis 3.2.

Comparison 3 Glucose monomer versus candy bar, Outcome 2 Positive screen for gestational diabetes.

Analysis 3.3.

Comparison 3 Glucose monomer versus candy bar, Outcome 3 Taste.

Analysis 3.4.

Comparison 3 Glucose monomer versus candy bar, Outcome 4 Symptoms.

Comparison 4. Glucose polymer versus candy bar
Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size
1 Diagnosis of gestational diabetes183Risk Ratio (M-H, Fixed, 95% CI)4.44 [0.22, 89.84]
2 Positive screen for gestational diabetes183Risk Ratio (M-H, Fixed, 95% CI)1.48 [0.38, 5.78]
3 Taste183Risk Ratio (M-H, Fixed, 95% CI)0.42 [0.22, 0.82]
4 Symptoms1 Risk Ratio (M-H, Fixed, 95% CI)Subtotals only
4.1 Any symptom183Risk Ratio (M-H, Fixed, 95% CI)0.39 [0.13, 1.18]
4.2 Dizziness183Risk Ratio (M-H, Fixed, 95% CI)0.66 [0.16, 2.79]
4.3 Nausea183Risk Ratio (M-H, Fixed, 95% CI)0.89 [0.06, 13.70]
4.4 Abdominal discomfort183Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
4.5 Bloating183Risk Ratio (M-H, Fixed, 95% CI)0.10 [0.01, 1.78]
Analysis 4.1.

Comparison 4 Glucose polymer versus candy bar, Outcome 1 Diagnosis of gestational diabetes.

Analysis 4.2.

Comparison 4 Glucose polymer versus candy bar, Outcome 2 Positive screen for gestational diabetes.

Analysis 4.3.

Comparison 4 Glucose polymer versus candy bar, Outcome 3 Taste.

Analysis 4.4.

Comparison 4 Glucose polymer versus candy bar, Outcome 4 Symptoms.

Comparison 5. Glucose versus food
Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size
1 Positive screen for gestational diabetes130Risk Ratio (M-H, Fixed, 95% CI)7.0 [0.39, 124.83]
2 Any symptom130Risk Ratio (M-H, Fixed, 95% CI)12.0 [1.78, 81.06]
Analysis 5.1.

Comparison 5 Glucose versus food, Outcome 1 Positive screen for gestational diabetes.

Analysis 5.2.

Comparison 5 Glucose versus food, Outcome 2 Any symptom.

Feedback

Oliveira, 9 March 2015

Summary

I'm a consumer and an activist for better health care practices. It seems that the famous HAPO1 study was not included in this review. I would like to have your help to understand why.

Comment submitted by Sandra Oliveira, March 2015

References

1. Hyperglycemia and Adverse Pregnancy Outcomes. New England Journal of Medicine 2008;358:1991-2002.

What's new

DateEventDescription
9 March 2015Feedback has been incorporated Feedback 1 submitted by Sandra Oliveira.

History

Protocol first published: Issue 3, 2008
Review first published: Issue 7, 2010

DateEventDescription
1 December 2013New search has been performedReview updated.
1 December 2013New citation required but conclusions have not changedNew search. Three studies have been excluded (Duenas-Garcia 2011; Meltzer 2010; Saijan 2011); no new trials have been included.
10 January 2011AmendedContact details updated.

Contributions of authors

For this update, Joanna Tieu and Philippa Middleton assessed the new studies for inclusion/exclusion. Joanna Tieu and Philippa Middleton drafted changes to the text, and Caroline Crowther and Andy McPhee commented on drafts and contributed to the final version.

Declarations of interest

None known.

Sources of support

Internal sources

  • ARCH, Robinson Institute, The University of Adelaide, Australia.

External sources

  • National Health and Medical Research Council, Australia.

Differences between protocol and review

None known.

Characteristics of studies

Characteristics of included studies [ordered by study ID]

Bergus 1992

Methods

Randomised controlled trial.

Funding: unspecified.

Participants

Location: Ketchikan Native Health Clinic, Ketchikan, Alaska and Mt. Edgecumbe Hospital, Sitka, Alaska.

Inclusion criteria: pregnant native Alaskan women at 24-28 weeks' gestation, with no history of diabetes mellitus, between January 1988 and May 1990.

Exclusion criteria: none specified.

76 women were enrolled into the study.

Interventions

Participants received either a 50 g glucose monomer or 50 g glucose polymer according to their randomly allocated group, regardless of time of last meal.

Both groups: venous and capillary samples were collected after 1 hour. A result of greater than or equal to 7.8 mmol/L was considered positive. All participants underwent a 100 g 3-hour OGTT within 3 days of their glucose challenge test.

Outcomes

Maternal: venous plasma glucose following glucose challenge test, capillary blood glucose following glucose challenge test, OGTT and symptom questionnaire ('felt sick', 'felt nauseated', 'headache', 'felt dizzy', 'felt bloated', 'felt tired', 'vomited' and 'felt abdominal discomfort').

Infant: none.

Notes 
Risk of bias
BiasAuthors' judgementSupport for judgement
Random sequence generation (selection bias)Low risk'Randomisation was achieved by using consecutive numbers from a random number table.'
Allocation concealment (selection bias)Unclear riskNot specified.
Blinding of participants and personnel (performance bias)
All outcomes
Unclear risk'Double-blind' implies that participants and personnel were blinded to randomised group, although this is not stated.
Blinding of outcome assessment (detection bias)
All outcomes
Unclear riskBlinding of outcome assessors was not reported.
Incomplete outcome data (attrition bias)
All outcomes
Unclear risk'10 women did not complete the symptom questionnaire, but their baseline characteristics did not differ significantly from those with complete data collection.' These women (13%) were excluded from the analysis of symptoms.
Selective reporting (reporting bias)Low riskAll pre-specified outcomes were reported.
Other biasUnclear riskBaseline characteristics were not reported. It is therefore, unclear whether baseline imbalances exist.

Griffin 2000

Methods

Quasi-randomised controlled trial.

Funding: grant from Bayer Diagnostics and research grant from National Maternity Hospital, Dublin.

Participants

Location: outpatient obstetric clinics at the National Maternity Hospital, Dublin.

Inclusion criteria: first visit to outpatient clinic of National Maternity Hospital, over a 24-month period.

Exclusion criteria: none specified.

3742 women were enrolled into the study, with 1853 randomised to the risk factor screening group and 1889 randomised to the universal screening group.

Interventions

Risk factor group: 100 g 3-hour OGTT performed at 32 weeks' gestation if any risk factors are present (historical - first-degree relative with diabetes mellitus, > 100 kg in current pregnancy, previous baby > 4.5 kg, previous unexplained stillbirth/intrauterine death, previous major malformation, previous GDM, current - glycosuria in 2nd fasting urine sample, macrosomia in current pregnancy or polyhydramnios in current pregnancy).

Universal group: 50 g 1-hour OGCT at 26-28 weeks' gestation without regard to time of last meal. This was considered positive if 1-hour plasma glucose was greater than or equal to 7.8 mmol/L. In those with a positive glucose challenge test, a 100 g OGTT was performed (using National Diabetes Data Group criteria). Women with risk factors for GDM (i.e. those listed for the risk factor group), had a repeat OGCT if the first OGCT was negative or if the OGTT was negative (following a positive OGCT).

Both groups: there was uniform diabetic and obstetric management for all participants, regardless of randomly allocated screening group. Women diagnosed with GDM were referred to both an obstetrician and endocrinologist, reviewed every 2 weeks until 36 weeks and awaited until 42 weeks unless medically contraindicated. All participants diagnosed with GDM were instructed in appropriate diabetic diet and intensive insulin treatment was instituted if fasting and postprandial (1.5 hour) blood glucose following a standard breakfast were not maintained (< 5.9 mmol/L or < 7.9 mmol/L respectively).

Outcomes

Maternal: diagnosis of GDM, spontaneous vaginal birth at term, emergency caesarean section, pre-eclampsia and insulin treatment required.

Infant: LGA, macrosomia (> 4500 g), hypoglycaemia, hyperbilirubinaemia, gestational age at birth, ponderal index, admission to neonatal intensive care unit and preterm birth.

NotesWe are in correspondence with authors for additional data.
Risk of bias
BiasAuthors' judgementSupport for judgement
Random sequence generation (selection bias)High riskThis trial was quasi-randomised. 'Randomisation to group was performed on the basis of which day the clinic was held as patients were randomly assigned clinics at booking.'
Allocation concealment (selection bias)High riskNot feasible since randomisation was based on the day women came to the clinic.
Blinding of participants and personnel (performance bias)
All outcomes
Unclear riskNot specified. It was probably unfeasible for the study to blind participants and personnel.
Blinding of outcome assessment (detection bias)
All outcomes
Unclear riskBlinding of outcome assessors was not reported.
Incomplete outcome data (attrition bias)
All outcomes
Unclear risk'There were no significant differences between those women who consented to glucose challenge test and those who refused with respect to weight, BMI, age, socio-economic group or presence of risk factors for GDM.' 590 (31%) women in the universal group were lost with no losses in the routine care group seen since routine care in this centre is the care received in the risk factor group.
Selective reporting (reporting bias)High riskOutcome data for participants were not available by original group allocation by day of visit, and were analysed by GDM diagnosis rather than randomly allocated group, affecting interpretation of outcome data.
Other biasHigh riskAs mentioned above, outcome data were analysed by GDM diagnosis rather than by original group allocation by day of visit.

Martinez Collado 2003

Methods

Randomised controlled trial.

Funding: not specified.

Participants

Location: Hospital Regional 1o de Octubre.

Inclusion criteria: pregnant women at 24 to 28 weeks' gestation with a high-risk pregnancy.

Exclusion criteria: women with diabetes mellitus, previously diagnosed with GDM or on steroid or tocolytic therapy.

30 women were enrolled into the study, with 15 allocated to a 50 g glucose challenge test and 15 women allocated to receive a food mix.

Interventions

Glucose challenge test group: received a 50 g glucose solution orally.

Food group: received food mix containing carbohydrate, protein, fats and 50 g of glucose.

A venous blood sample was taken 1 hour after consuming the glucose solution or food mix. A glucose level greater than 140 mg/dL was considered abnormal.

Outcomes

Maternal: positive screen for GDM and tolerance to food or solution.

Infant: none specified.

NotesStudy was reported in Spanish.
Risk of bias
BiasAuthors' judgementSupport for judgement
Random sequence generation (selection bias)Unclear riskThe allocation of participants is described as being 'randomly assigned', no further information is provided on the sequence generation.
Allocation concealment (selection bias)Unclear riskNot specified.
Blinding of participants and personnel (performance bias)
All outcomes
Unclear riskNot specified. It is likely that blinding of participants was unfeasible, and blinding of study personnel was not reported.
Blinding of outcome assessment (detection bias)
All outcomes
Unclear riskBlinding of outcome assessors was not reported.
Incomplete outcome data (attrition bias)
All outcomes
Unclear riskLosses to follow-up were not reported.
Selective reporting (reporting bias)Low riskThe pre-specified outcomes of outcome of venous blood sample and tolerance to food or solution were reported.
Other biasUnclear riskThere was no baseline comparison of participants in the 2 groups.

Murphy 1994

  1. a

    BMI: body mass index
    LGA: large-for-gestational age
    GDM: gestational diabetes mellitus
    OGCT: oral glucose challenge test
    OGTT: oral glucose tolerance test

Methods

Randomised controlled trial.

Funding: not specified.

Participants

Location: Saint Luke's Hospital, Kansas City, Missouri.

Inclusion criteria: pregnant women at the Medical Education Clinics, Saint Luke's Hospital, Kansas City, Missouri.

Exclusion criteria: none specified.

Of the 124 women who were enrolled into the study, 44 were allocated to group 1 (glucose polymer), 41 were allocated to group 2 (d-glucose) and 39 were allocated to group 3 (candy bar). 16 of the 124 women were unable to complete the glucose tolerance test within 1 week of screening, as required by all participants. Of these 16 women, 5 vomited or were too symptomatic and 11 did not complete the glucose tolerance test for logistical reasons or incomplete data.

Interventions

Those recruited, following hospital protocol, were screened at 24-28 weeks. Where the woman possessed 1 of the following risk factors, they also receive GDM screening at their initial visit (past history of glucose intolerance, first-degree relative with diabetes mellitus, age > 35 years, past macrosomia, habitual abortion, unexplained stillbirth, congenital anomalies or current pregnancy with glycosuria, hypertension, suspected LGA fetus, polyhydramnios or obesity). For each of the screening methods, the carbohydrate source was ingested without regard to time of last meal. Within 1 week of the screening test, all women were required to undergo a 100 g 3-hour glucose tolerance test (in 300 mL of carbonated water). GDM was diagnosed using O'Sullivan criteria.

Group 1 (n = 44): participants received 50 g of glucose polymer. This was made from 100 mL of 43% polymer solution with 1.5 g unsweetened flavouring and 50 mL of unsweetened club soda.

Group 2 (n = 41): participants received the standard 50 g d-glucose solution in 300 mL of carbonated water.

Group 3 (n = 39): participants received a total of 50 g of candy bar (containing milk chocolate, sucrose, corn syrup, partially hydrogenated soya bean oil, cocoa, salt, egg whites, malt extract, soybean protein and artificial flavour).

Outcomes

Maternal: diagnosis of GDM, serum glucose values following screening and symptom questionnaire (taste, abdominal pain, bloating, dizziness and nausea).

Infant: none reported.

Notes 
Risk of bias
BiasAuthors' judgementSupport for judgement
Random sequence generation (selection bias)Unclear riskNot specified. Women were 'prospectively enrolled and randomly assigned to receive 1 of 3 different carbohydrate sources for their GDM screening'.
Allocation concealment (selection bias)Unclear riskNot specified.
Blinding of participants and personnel (performance bias)
All outcomes
Unclear riskNot specified for participants, clinicians and outcome assessors.
Blinding of outcome assessment (detection bias)
All outcomes
Unclear riskNot specified for participants, clinicians and outcome assessors.
Incomplete outcome data (attrition bias)
All outcomes
High risk

Data from 16 of the 124 women (13%) were not included in the final analysis as they were unable to complete the glucose tolerance test within 1 week. Of these women, 5 were unable to complete because they became symptomatic during the test and the remaining 11 were unable to complete the test for logistical reasons or because there was incomplete laboratory data. The number of women lost to follow-up from each treatment group is not reported. A comparison of baseline characteristics was not made on those lost to follow-up and those not.

Furthermore, it is not reported how many of the women included in the study were screened in their first trimester or at the standard 24 to 28 weeks' gestation.

Selective reporting (reporting bias)High riskSide effects were only reported where the women rated it in the moderate to severe range (3 to 5 out of a possible 5). Therefore, mild symptoms were not reported.
Other biasLow riskNo obvious source of other bias.

Characteristics of excluded studies [ordered by study ID]

StudyReason for exclusion
  1. a

    GDM: gestational diabetes mellitus

Berkus 1995Study assessed strategies for diagnosis of GDM, not screening.
Brustman 1995Study assessed strategies for diagnosis of GDM, not screening.
Buhling 2004Study assessed strategies for diagnosis of GDM, not screening.
Cheng 1992Study assessed strategies for diagnosis of GDM, not screening.
Court 1984Study assessed strategies for diagnosis of GDM, not screening.
Court 1985Study assessed strategies for diagnosis of GDM, not screening.
Dornhorst 2000Not a randomised controlled trial.
Duenas-Garcia 2011Study assessed strategies for diagnosis of GDM, not screening.
Eslamian 2007Cross-over study.
Eslamian 2008Cross-over study.
Fung 1993Study assessed strategies for diagnosis of GDM, not screening.
Harlass 1991Study assessed strategies for diagnosis of GDM, not screening.
Helton 1989Cross-over study.
Hidar 2001Cross-over study.
Jones 1993Study assessed strategies for diagnosis of GDM, not screening.
Kjos 2001Women in this study had already been diagnosed with GDM.
Lamar 1999aCross-over study.
Lamar 1999bCross-over study.
Lewis 1993Women in this study had already been diagnosed with GDM or had undergone a process for diagnosis of GDM.
Meltzer 2010Study assessed strategies for diagnosis of GDM, not screening.
Olarinoye 2004Study assessed strategies for diagnosis of GDM, not screening.
Saijan 2011Study assessed strategies for diagnosis of GDM, not screening. Unclear if this study was randomised.
Sammarco 1993Study assessed strategies for diagnosis of GDM, not screening.
Soonthornpun 2003Study assessed strategies for diagnosis of GDM, not screening.
Soonthornpun 2008Cross-over study.
Stavrianos 2004Study assessed strategies for diagnosis of GDM, not screening.
Weiss 1998Study assessed strategies for diagnosis of GDM, not screening.
Zhang 1995Study assessed strategies for diagnosis of GDM, not screening.

Characteristics of studies awaiting assessment [ordered by study ID]

Bebbington 1999

  1. a

    GDM: gestational diabetes mellitus

Methods

Type of study: randomised controlled trial.

Method of randomisation: unspecified.

Loss of participants to follow-up: 18 of 2401 women were lost to follow-up.

Intention-to-treat analysis: unspecified.

Blinding: unfeasible to blind participants or healthcare providers. 'Blinded assessors collected outcomes postpartum.'

Funding: unspecified.

Participants

Location: British Columbia Women's Hospital, British Columbia, Canada.

Inclusion criteria: low-risk pregnancy at British Columbia Women's Hospital.

Exclusion criteria: risk factors for GDM (specific risk factors not specified).

2401 women were enrolled into the study. 1197 women were allocated to the routine screening arm and 1204 women were allocated to the selected screening arm.

Interventions

Routine testing group: received a 50 g glucose screen and a full 100 g glucose tolerance test was performed in women whose 1 hour glucose was > 7.8 mmol/L on 50 g screening.

Selected screening group: received glucose testing only for selected indications that arose during pregnancy.

Outcomes

Maternal: none.

Infant: birthweight and macrosomia.

NotesThe only publication of this trial is a conference abstract. We are in correspondence with the authors for additional data. No contact as at July 2013.

Ancillary