Oral anti-diabetic pharmacological therapies for the treatment of women with gestational diabetes(review)

Transcription

1 Cochrane Database of Systematic Reviews Oral anti-diabetic pharmacological therapies for the treatment of women with gestational diabetes(review) BrownJ,MartisR,HughesB,RowanJ,CrowtherCA BrownJ,MartisR,HughesB,RowanJ,CrowtherCA.. Cochrane Database of Systematic Reviews 2017, Issue 1. Art. No.: CD DOI: / CD pub2. (Review) Copyright 2017 The Cochrane Collaboration. Published by John Wiley& Sons, Ltd.

2 T A B L E O F C O N T E N T S HEADER ABSTRACT PLAIN LANGUAGE SUMMARY SUMMARY OF FINDINGS FOR THE MAIN COMPARISON BACKGROUND OBJECTIVES METHODS Figure RESULTS Figure Figure ADDITIONAL SUMMARY OF FINDINGS DISCUSSION AUTHORS CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES CHARACTERISTICS OF STUDIES DATA AND ANALYSES Analysis 1.1. Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 1 Hypertensive disorders of pregnancy. 68 Analysis 1.2. Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 2 Caesarean section Analysis 1.3. Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 3 Large-for-gestational age Analysis 1.4. Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 4 Use of additional pharmacotherapy. 70 Analysis 1.5. Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 5 Glycaemic control (end of treatment) (mg/dl) Analysis 1.6. Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 6 Weight gain in pregnancy (Kg).. 72 Analysis 1.7. Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 7 Induction of labour Analysis 1.8. Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 8 Perineal trauma Analysis 1.9. Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 9 Stillbirth Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 10 Neonatal death Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 11 Small-for-gestational age Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 12 Macrosomia Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 13 Birthweight (g) Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 14 Shoulder dystocia Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 15 Bone fracture Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 16 Nerve palsy Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 17 Gestational age at birth (weeks). 77 Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 18 Neonatal hypoglycaemia Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 19 Hyperbilirubinaemia Analysis Comparison 1 Oral anti-diabetic agents versus placebo, Outcome 20 Admission to NICU Analysis 2.1. Comparison 2 Metformin versus glibenclamide, Outcome 1 Hypertensive disorders of pregnancy Analysis 2.2. Comparison 2 Metformin versus glibenclamide, Outcome 2 Caesarean section Analysis 2.3. Comparison 2 Metformin versus glibenclamide, Outcome 3 Perinatal mortality Analysis 2.4. Comparison 2 Metformin versus glibenclamide, Outcome 4 Large-for-gestational age Analysis 2.5. Comparison 2 Metformin versus glibenclamide, Outcome 5 Death or serious morbidity composite Analysis 2.6. Comparison 2 Metformin versus glibenclamide, Outcome 6 Use of additional pharmacotherapy Analysis 2.7. Comparison 2 Metformin versus glibenclamide, Outcome 7 Maternal hypoglycaemia Analysis 2.8. Comparison 2 Metformin versus glibenclamide, Outcome 8 Glycaemic control (mg/l; mmol/l) Analysis 2.9. Comparison 2 Metformin versus glibenclamide, Outcome 9 Weight gain in pregnancy (Kg) Analysis Comparison 2 Metformin versus glibenclamide, Outcome 10 Induction of labour Analysis Comparison 2 Metformin versus glibenclamide, Outcome 11 Perineal trauma Analysis Comparison 2 Metformin versus glibenclamide, Outcome 12 Stillbirth i

3 Analysis Comparison 2 Metformin versus glibenclamide, Outcome 13 Macrosomia Analysis Comparison 2 Metformin versus glibenclamide, Outcome 14 Birth trauma Analysis Comparison 2 Metformin versus glibenclamide, Outcome 15 Shoulder dystocia Analysis Comparison 2 Metformin versus glibenclamide, Outcome 16 Gestational age at birth (weeks) Analysis Comparison 2 Metformin versus glibenclamide, Outcome 17 Preterm birth Analysis Comparison 2 Metformin versus glibenclamide, Outcome 18 5-minute Apgar < Analysis Comparison 2 Metformin versus glibenclamide, Outcome 19 Birthweight (g) Analysis Comparison 2 Metformin versus glibenclamide, Outcome 20 Ponderal index Analysis Comparison 2 Metformin versus glibenclamide, Outcome 21 Neonatal hypoglycaemia Analysis Comparison 2 Metformin versus glibenclamide, Outcome 22 Respiratory distress syndrome Analysis Comparison 2 Metformin versus glibenclamide, Outcome 23 Hyperbilirubinaemia Analysis Comparison 2 Metformin versus glibenclamide, Outcome 24 Admission to NICU Analysis 3.1. Comparison 3 Glibenclamide versus acarbose, Outcome 1 Caesarean section Analysis 3.2. Comparison 3 Glibenclamide versus acarbose, Outcome 2 Perinatal mortality Analysis 3.3. Comparison 3 Glibenclamide versus acarbose, Outcome 3 Large-for-gestational age Analysis 3.4. Comparison 3 Glibenclamide versus acarbose, Outcome 4 Need for additional pharmacotherapy Analysis 3.5. Comparison 3 Glibenclamide versus acarbose, Outcome 5 Maternal hypoglycaemia Analysis 3.6. Comparison 3 Glibenclamide versus acarbose, Outcome 6 Weight gain in pregnancy (Kg) Analysis 3.7. Comparison 3 Glibenclamide versus acarbose, Outcome 7 Macrosomia Analysis 3.8. Comparison 3 Glibenclamide versus acarbose, Outcome 8 Small-for-gestational age Analysis 3.9. Comparison 3 Glibenclamide versus acarbose, Outcome 9 Birth trauma (not specified) Analysis Comparison 3 Glibenclamide versus acarbose, Outcome 10 Gestational age at birth (weeks) Analysis Comparison 3 Glibenclamide versus acarbose, Outcome 11 Preterm birth Analysis Comparison 3 Glibenclamide versus acarbose, Outcome 12 Birthweight (Kg) Analysis Comparison 3 Glibenclamide versus acarbose, Outcome 13 Neonatal hypoglycaemia Analysis Comparison 3 Glibenclamide versus acarbose, Outcome 14 Respiratory distress syndrome ADDITIONAL TABLES APPENDICES CONTRIBUTIONS OF AUTHORS DECLARATIONS OF INTEREST SOURCES OF SUPPORT DIFFERENCES BETWEEN PROTOCOL AND REVIEW NOTES INDEX TERMS ii

4 [Intervention Review] Oral anti-diabetic pharmacological therapies for the treatment of women with gestational diabetes Julie Brown 1, Ruth Martis 1, Brenda Hughes 2, Janet Rowan 3, Caroline A Crowther 1,4 1 Liggins Institute, The University of Auckland, Auckland, New Zealand. 2 Pharmacy, Auckland City Hospital, Auckland, New Zealand. 3 National Women s Health, Auckland, New Zealand. 4 ARCH: Australian Research Centre for Health of Women and Babies, Robinson Research Institute, Discipline of Obstetrics and Gynaecology, The University of Adelaide, Adelaide, Australia Contact address: Julie Brown, Liggins Institute, The University of Auckland, Park Rd, Grafton, Auckland, 1142, New Zealand. j.brown@auckland.ac.nz. Editorial group: Cochrane Pregnancy and Childbirth Group. Publication status and date: New, published in Issue 1, Citation: Brown J, Martis R, Hughes B, Rowan J, Crowther CA. Oral anti-diabetic pharmacological therapies for the treatment of women with gestational diabetes. Cochrane Database of Systematic Reviews 2017, Issue 1. Art. No.: CD DOI: / CD pub2. Background A B S T R A C T Gestational diabetes mellitus (GDM) is a major public health issue with rates increasing globally. Gestational diabetes, glucose intolerance first recognised during pregnancy, usually resolves after birth and is associated with short- and long-term complications for the mother and her infant. Treatment options can include oral anti-diabetic pharmacological therapies. Objectives To evaluate the effects of oral anti-diabetic pharmacological therapies for treating women with GDM. Search methods We searched Cochrane Pregnancy and Childbirth s Trials Register (14 May 2016), ClinicalTrials.gov, WHO ICTRP (14 May 2016) and reference lists of retrieved studies. Selection criteria We included published and unpublished randomised controlled trials assessing the effects of oral anti-diabetic pharmacological therapies for treating pregnant women with GDM. We included studies comparing oral anti-diabetic pharmacological therapies with 1) placebo/ standard care, 2) another oral anti-diabetic pharmacological therapy, 3) combined oral anti-diabetic pharmacological therapies. Trials using insulin as the comparator were excluded as they are the subject of a separate Cochrane systematic review. Women with pre-existing type 1 or type 2 diabetes were excluded. Data collection and analysis Two review authors independently assessed trials for inclusion and trial quality. Two review authors independently extracted data and data were checked for accuracy. 1

5 Main results We included 11 studies (19 publications) (1487 women and their babies). Eight studies had data that could be included in meta-analyses. Studies were conducted in Brazil, India, Israel, UK, South Africa and USA. The studies varied in diagnostic criteria and treatment targets for glycaemic control for GDM. The overall risk of bias was unclear due to inadequate reporting of methodology. Using GRADE the quality of the evidence ranged from moderate to very low quality. Evidence was downgraded for risk of bias (reporting bias, lack of blinding), inconsistency, indirectness, imprecision and for oral anti-diabetic therapy versus placebo for generalisability. Oral anti-diabetic pharmacological therapies versus placebo/standard care There was no evidence of a difference between glibenclamide and placebo groups for hypertensive disorders of pregnancy (risk ratio (RR) 1.24, 95% confidence interval (CI) 0.81 to 1.90; one study, 375 women, very low-quality evidence), birth by caesarean section (RR 1.03, 95% CI 0.79 to 1.34; one study, 375 women, very low-quality evidence), perineal trauma (RR 0.98, 95% CI 0.06 to 15.62; one study, 375 women, very low-quality evidence) or induction of labour (RR 1.18, 95% CI 0.79 to 1.76; one study, 375 women; very low-quality evidence). No data were reported for development of type 2 diabetes or other pre-specified GRADE maternal outcomes (return to pre-pregnancy weight, postnatal depression). For the infant, there was no evidence of a difference in the risk of being born large-for-gestational age (LGA) between infants whose mothers had been treated with glibenclamide and those in the placebo group (RR 0.89, 95% CI 0.51 to 1.58; one study, 375, low-quality evidence). No data were reported for other infant primary or GRADE outcomes (perinatal mortality, death or serious morbidity composite, neurosensory disability in later childhood, neonatal hypoglycaemia, adiposity, diabetes). Metformin versus glibenclamide There was no evidence of a difference between metformin- and glibenclamide-treated groups for the risk of hypertensive disorders of pregnancy (RR 0.70, 95% CI 0.38 to 1.30; three studies, 508 women, moderate-quality evidence), birth by caesarean section (average RR 1.20, 95% CI 1.20; 95% CI 0.83 to 1.72, four studies, 554 women, I 2 = 61%, Tau 2 = 0.07 low-quality evidence), induction of labour (0.81, 95% CI 0.61 to 1.07; one study, 159 women; low-quality evidence) or perineal trauma (RR 1.67, 95% CI 0.22 to 12.52; two studies, 158 women; low-quality evidence). No data were reported for development of type 2 diabetes or other prespecified GRADE maternal outcomes (return to pre-pregnancy weight, postnatal depression). For the infant there was no evidence of a difference between the metformin- and glibenclamide-exposed groups for the risk of being born LGA (average RR 0.67, 95% CI 0.24 to 1.83; two studies, 246 infants, I 2 = 54%, Tau 2 = 0.30 low-quality evidence). Metformin was associated with a decrease in a death or serious morbidity composite (RR 0.54, 95% CI 0.31 to 0.94; one study, 159 infants, low-quality evidence). There was no clear difference between groups for neonatal hypoglycaemia (RR 0.86, 95% CI 0.42 to 1.77; four studies, 554 infants, low-quality evidence) or perinatal mortality (RR 0.92, 95% CI 0.06 to 14.55, two studies, 359 infants). No data were reported for neurosensory disability in later childhood or for adiposity or diabetes. Glibenclamide versus acarbose There was no evidence of a difference between glibenclamide and acarbose from one study (43 women) for any of their maternal or infant primary outcomes (caesarean section, RR 0.95, 95% CI 0.53 to 1.70; low-quality evidence; perinatal mortality - no events; low-quality evidence; LGA, RR 2.38, 95% CI 0.54 to 10.46; low-quality evidence). There was no evidence of a difference between glibenclamide and acarbose for neonatal hypoglycaemia (RR 6.33, 95% CI 0.87 to 46.32; low-quality evidence). There were no data reported for other pre-specified GRADE or primary maternal outcomes (hypertensive disorders of pregnancy, development of type 2 diabetes, perineal trauma, return to pre-pregnancy weight, postnatal depression, induction of labour) or neonatal outcomes (death or serious morbidity composite, adiposity or diabetes). Authors conclusions There were insufficient data comparing oral anti-diabetic pharmacological therapies with placebo/standard care (lifestyle advice) to inform clinical practice. There was insufficient high-quality evidence to be able to draw any meaningful conclusions as to the benefits of one oral anti-diabetic pharmacological therapy over another due to limited reporting of data for the primary and secondary outcomes in this review. Short- and long-term clinical outcomes for this review were inadequately reported or not reported. Current choice of oral anti-diabetic pharmacological therapy appears to be based on clinical preference, availability and national clinical practice guidelines. The benefits and potential harms of one oral anti-diabetic pharmacological therapy compared with another, or compared with placebo/ standard care remains unclear and requires further research. Future trials should attempt to report on the core outcomes suggested in this review, in particular long-term outcomes for the woman and the infant that have been poorly reported to date, women s experiences and cost benefit. 2

6 P L A I N L A N G U A G E S U M M A R Y Oral medication for the treatment of women with gestational diabetes What is the issue? Globally the number of women being diagnosed with gestational diabetes mellitus (GDM) is increasing. GDM is an intolerance to glucose leading to high blood sugars, first recognised during pregnancy and usually resolving after birth. Standard care involves lifestyle advice on diet and exercise. Treatment for some women includes oral anti-diabetic medications, such as metformin and glibenclamide, which are an alternative to, or can be used alongside, insulin to control the blood sugar. This review aimed to investigate benefits of taking oral medication to treat GDM in pregnant women. Another Cochrane Review compares the effects of insulin with oral antidiabetic pharmacological therapies (Brown 2016). Why is this important? Women diagnosed with GDM are at a greater risk of experiencing complications such as high blood pressure during pregnancy and at birth. They have an increased risk of developing diabetes later in life. The babies of women who have been diagnosed with GDM can be larger than normal and this can cause injuries to the mother and the baby at birth. The birth is more likely to be induced or the baby born by caesarean section. These babies are at risk of developing diabetes as children or young adults. Finding the best medications to treat the women and prevent the complications that are linked to GDM is therefore important. What evidence did we find? We searched for studies on 14 May We included 11 randomised controlled trials involving 1487 mothers and their babies (but only eight trials contributed data to our analyses). The evidence was limited by the quality and number of studies and we advise caution when looking at the results. The criteria for diagnosis of GDM and treatment targets varied between studies, and each outcome is based on few studies with low numbers of women. Three studies compared oral medication with placebo/standard care but the following findings are from a single study (375 women). The quality of the evidence was very low or low. We found no differences between the oral medication and placebo group for the risk of high blood pressure, birth by caesarean section, induction of labour or perineal trauma. The number of babies born large-for-gestational age, with low blood sugars or dying at birth was not clearly different between the groups. Two studies (434 women) reported no difference in the need for insulin between the oral medication and placebo group. Six studies compared metformin with glibenclamide. The quality of the evidence was very low to moderate. We found no difference between metformin and glibenclamide for the risk of high blood pressure (three studies, 508 women, moderate-quality evidence), birth by caesarean section (four studies, 554 women, low-quality evidence), perineal trauma (two studies, 308 women, low-quality evidence) or induction of labour (one study, 159 women, low-quality evidence). We found no difference between metformin and glibenclamide for the baby having low blood sugars (four studies, 554 infants, low-quality evidence), being born large-for-gestational age (two studies, 246 infants) or dying at birth (all low- or very low-quality evidence). In one study, the babies of the mothers taking metformin were at reduced risk of having any serious outcome (low blood sugar, jaundice, being born large, breathing problems, injury at birth or death combined) (low-quality evidence). One small study (43 women) comparing glibenclamide with acarbose reported no differences in outcomes for mothers or their babies. None of the included studies provided any data on many of the outcomes pre-specified in this review, including long-term outcomes for the mother or for the baby as a child or an adult. What does this mean? There is not enough high-quality evidence available to guide us on if oral medication has better outcomes for women with gestational diabetes, and their babies, compared with a placebo or if one oral medication has better health outcomes than another oral medication. Because we are still unclear, further research is needed. Future studies should be encouraged to report on the outcomes suggested in this review and in particular the long-term outcomes for the woman and the infant that have been poorly reported to date. 3

7 S U M M A R Y O F F I N D I N G S F O R T H E M A I N C O M P A R I S O N [Explanation] Oral anti-diabetic pharmacological therapies versus placebo - maternal outcomes Patient or population: women diagnosed with gestational diabetes; weeks gestation; singleton pregnancy Setting: Medical Centre, USA. Intervention: oral anti-diabetic pharmacological therapy (glibenclamide) placebo Outcomes Anticipatedabsoluteeffects (95%CI) Relativeeffect (95% CI) Hypertensive disorders of pregnancy - (any type) Risk with placebo Risk with oral anti- diabetic pharmacological therapies 167 per per 1000 (135 to 317) Caearean section 360 per per 1000 (285 to 483) Development of type 2 diabetes - not measured RR 1.24 (0.81 to 1.90) RR 1.03 (0.79 to 1.34) of participants (studies) 375 (1 RCT) 375 (1 RCT) Quality of the evidence (GRADE) Very low abc Very low abc Comments see comment see comment not estimable - - This was not a prespecified outcome for the included studies reporting on this comparison Perineal trauma 5 per per 1000 (0 to 84) RR 0.98 (0.06 to 15.62) 375 (1 RCT) Very low abcd Event rates were low 1/ 189 for anti-diabetic pharmacological therapy and 1/186 in the control (placebo) group 4

8 Return to pre-pregnancyweight -not measured Postnatal depression - not measured see comment see comment not estimable - - This was not a prespecified outcome for the included studies reporting on this comparison see comment see comment not estimable - - This was not a prespecified outcome for the included studies reporting on this comparison Induction of labour 188 per per 1000 (149 to 331) RR 1.18 (0.79 to 1.76) 375 (1 RCT) Very low abc *Theriskintheinterventiongroup(and its 95%confidence interval) is based on the assumed risk in the comparison group and therelativeeffect of the intervention (and its 95%CI). CI: confidence interval; RCT: randomised controlled trial; RR: risk ratio; OR: odds ratio GRADE Working Group grades of evidence Highquality:We are very confident that the true effect lies close to that of the estimate of the effect Moderatequality: We are moderately confident in the effect estimate: The true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different Low quality: Our confidence in the effect estimate is limited: The true effect may be substantially different from the estimate of the effect Very low quality: We have very little confidence in the effect estimate: The true effect is likely to be substantially different from the estimate of effect a Risk of bias -we did not find a published protocol and there were more outcomes reported in the published paper than were listed in the trial registration document - downgraded 1 level. b Generalisability - in this single study 93%of participants were Hispanic women. Results may not be generalisable to other populations - downgraded 1 level. c Imprecision -evidence based on a single study -downgraded 1 level. d Imprecision - wide confidence intervals crossing the line of no effect and low event rates suggestive of imprecision - downgraded 1 level. 5

9 B A C K G R O U N D The original review by Alwan and colleagues, Treatments for gestational diabetes (Alwan 2009) has been split into three new review titles reflecting the complexity of treating women with gestational diabetes. Lifestyle interventions for the treatment of women with gestational diabetes mellitus (Brown 2015) Oral anti-diabetic pharmacological therapies for the treatment of women with gestational diabetes mellitus (this review) Insulin for the treatment of women with gestational diabetes mellitus (Brown 2016) There will be similarities in the background, methods and outcomes between these three systematic reviews. Portions of the methods section of this review are based on a standard template used by Cochrane Pregnancy and Childbirth. Description of the condition Gestational diabetes mellitus (GDM) often referred to as gestational diabetes can be defined as glucose intolerance or hyperglycaemia (high blood glucose concentration) with onset or first recognition during pregnancy (WHO 1999). GDM occurs when the body is unable to make enough insulin to meet the extra needs in pregnancy. The high blood sugars associated with GDM will return to normal after the birth of the baby. However, there are currently no universally accepted diagnostic criteria (ACOG 2013; Coustan 2010; HAPO 2008; Hoffman 1998; IADPSG 2010; Metzger 1998; NICE 2015). GDM may include previously undetected type 1 diabetes, type 2 diabetes or diabetes presenting only during pregnancy (HAPO 2008; IADPSG 2010; Metzger 1998; Nankervis 2014; WHO 2014). GDM is one of the most common pregnancy complications and the prevalence is rising worldwide with 1% to 36% of pregnancies being affected (Bottalico 2007; Cundy 2014; Duran 2014; Ferrara 2007; NICE 2015; Ragnarsdottir 2010; Tran 2013). The prevalence of GDM is likely to continue to increase along with the increasing prevalence of maternal obesity and associated type 2 diabetes (Bottalico 2007; Mulla 2010; Petry 2010). A variety of factors have been associated with an increased risk of developing GDM. Non-modifiable risk factors include advanced maternal age (Chamberlain 2013; Morisset 2010), high parity, non-white race or ethnicity (in particular South Asian, Middle Eastern), family history of diabetes, maternal high or low birthweight, polycystic ovarian syndrome (Cypryk 2008; Petry 2010; Solomon 1997), a history of having a previous macrosomic infant (birthweight 4000 g or more) and previous history of GDM (Petry 2010). Modifiable risk factors include physical inactivity (Chasan-Taber 2008), having a low-fibre and high-glycaemic load diet (Zhang 2006), maternal overweight (body mass index (BMI) equal to or greater than 25 kg/m²) or obesity (equal to or greater than 30 kg/ m²) (Kim 2010) and excessive weight gain during pregnancy, especially for those who are already overweight or obese (Hedderson 2010). Pathophysiology of gestational diabetes Normal pregnancy is associated with significant changes in maternal metabolism (Lain 2007). In early pregnancy, oestrogen and progesterone stimulate maternal beta-cell hyperplasia and insulin secretion, which promotes maternal nutrient storage (adipose and hepatic glycogen) to support later fetal growth. At this stage, insulin sensitivity is maintained or may even increase. However, as pregnancy progresses whole-body insulin sensitivity steadily decreases, such that by the third trimester it is reduced by almost half (Barbour 2007). Several factors contribute to this, including placental hormones (human placental lactogen and placental growth hormone), cytokines released from adipocytes (IL-6, TNF-alpha), increased free fatty acids and lower adiponectin concentrations (Clapp 2006; Devlieger 2008). This results in decreased post-prandial peripheral glucose disposal by up to 40% to 60% (Barbour 2007). Because glucose is transported to the fetus by facilitated diffusion, this state of physiological insulin resistance promotes fetal glucose uptake, a principal oxidative fuel and carbon source for the growing fetus. In normal pregnancy, maternal glycaemia is maintained by a significant increase in insulin secretion of up to 200% to 250% (Barbour 2007; Lain 2007; Suman Rao 2013). Regulation of fetal glucose metabolism requires (1) the maintenance of maternal glucose concentration through increasing maternal glucose production, and at the same time, developing maternal glucose intolerance and insulin resistance, (2) transfer of glucose to the fetus across the placenta and (3) production of fetal insulin and uptake of glucose into adipose tissue and skeletal muscle (Suman Rao 2013). Women with GDM have further reductions in insulin signalling, and glucose uptake is decreased beyond that of normal pregnancy (Barbour 2007). This results in glucose intolerance, though glycaemia in pregnancy represents a continuum. In GDM, the steeper maternal-fetal glucose gradient, especially post-prandial, leads to increased fetal glucose uptake which stimulates fetal insulin secretion. Insulin is a key fetal anabolic hormone and hyperinsulinaemia promotes fetal overgrowth leading to large-for-gestational age (LGA) infants, macrosomia, and possible organ damage (Catalano 2003; Ju 2008; Metzger 2008; Reece 2009). Women with GDM also have increased circulating inflammatory cytokines and lower adiponectin concentrations leading to increased lipolysis and fatty acid concentrations. Placental transfer of free fatty acids contributes to increased fetal adiposity, independent of glucose uptake (Knopp 1985). Thus, even women with well-controlled GDM still have increased risk of fetal macrosomia (Langer 2005). 6

10 Screening and diagnosis of GDM Regardless of whether universal or selective (risk-factor), screening with a 50 g oral glucose challenge test is used, diagnosis of GDM is usually based on either a 75 g two-hour oral glucose tolerance test (OGTT) or a 100 g three-hour OGTT (ADA 2013; IADPSG 2010; Nankervis 2014; NICE 2015; WHO 1999). Recommendations regarding diagnostic criteria vary nationally and internationally (Table 1), and these diagnostic criteria have changed over time, sometimes due to changing understanding about the effects of hyperglycaemia on pregnancy and infant outcomes (Coustan 2010), but also because of a lack of evidence clearly demonstrating the clinical and cost-effectiveness of one criterion over another. The Hyperglycaemia and Adverse Pregnancy Outcomes (HAPO) study (HAPO 2008), a large, international observational study reported graded linear associations in the odds of several GDMassociated adverse outcomes and glucose levels at OGTT, with no clear threshold identified at which risk increased substantially. The International Association of the Diabetes and Pregnancy Study Groups (IADPSG) recommended diagnostic criteria using data from the HAPO study (IADPSG 2010). Applying the IADPSG criteria in most health environments will increase the number of women with GDM. A study conducted in Vietnam showed that depending on the criteria used, the diagnosis of GDM varied between 5.9% (American Diabetes Association - ADA), 20.4% (International Association of Diabetes in Pregnancy Study Groups - IADPSG), 20.8% (Australasian Diabetes in Pregnancy Society - ADIPS), and up to 24.3% (World Health Organization - WHO) (Tran 2013). A Bulgarian study also reported differences in prevalence based on the diagnostic criteria ranging from 10.8% (European Association for the Study of Diabetes - EASD), 13.5% (ADA), 16.2% (New Zealand Society for the Study of Diabetes - NZSSD), 17.1% (WHO), 21.2% (ADIPS), 31.6% (IADPSG) (Boyadzhieva 2012). Clinical outcomes for women with gestational diabetes Adverse outcomes have been consistently reported at higher rates in women diagnosed with GDM and their infants compared to women without GDM (Crowther 2005; Landon 2009; Metzger 2008; Reece 2009). Women with GDM have an increased risk of developing preeclampsia, are more likely to have their labour induced (Anderberg 2010; Crowther 2005; Ju 2008; Landon 2009; Metzger 2008), and give birth by caesarean section (Landon 2009; Metzger 2008). The incidence of uterine rupture, shoulder dystocia and perineal lacerations are increased in women with GDM due to the increased likelihood of having a LGA or macrosomic baby (Jastrow 2010). Women who have experienced GDM are at a greater risk of metabolic dysfunction in later life (Shah 2008; Vohr 2008), with a crude cumulative incidence of type 2 diabetes of 10% to 20% within 10 years (Bellamy 2009; Kim 2002), but up to 50% when adjusted for retention and length of follow-up (Kim 2002). Neonatal, infant and later outcomes related to gestational diabetes A significant adverse health outcome for babies born to mothers with GDM is being born LGA or macrosomic (Catalano 2003; Crowther 2005; Landon 2009; Metzger 2008; Reece 2009). Largefor-gestational age or macrosomic infants are at increased risk of birth injury, such as shoulder dystocia, perinatal asphyxia, bone fractures and nerve palsies (Esakoff 2009; Henriksen 2008; Langer 2005; Metzger 2008). Babies born to women with GDM, compared with babies born to women without GDM, have significantly greater skinfold measures and fat mass compared with infants of women with normal glucose tolerance (Catalano 2003). The offspring of women with GDM are heavier (adjusted for height) and have greater adiposity than the offspring of women with normal glycaemia during pregnancy (Pettitt 1985; Pettitt 1993), and are more likely to develop early overweight or obesity, type 2 diabetes (Hillier 2007; Pettitt 1993; Whincup 2008), or metabolic syndrome (a cluster of risk factors defined by the occurrence of three of the following: obesity, hypertension, hypertriglyceridaemia and low concentration of high-density lipoprotein (HDL) cholesterol) in childhood, adolescence or adulthood (Guerrero-Romero 2010; Harder 2009). The development of the metabolic syndrome during childhood is a risk factor for the development of adult type 2 diabetes at 25 to 30 years of age (Morrison 2008). These health problems repeat across generations (Dabelea 2005; Mulla 2010) and are important from a public health perspective, because with each generation the prevalence of diabetes increases. Other adverse outcomes which are increased for babies born to women with GDM include respiratory distress syndrome, hypoglycaemia (which if prolonged can cause brain injury), hyperbilirubinaemia, hypertrophic cardiomyopathy, hypocalcaemia, hypomagnesaemia, polycythaemia and admission to the neonatal nursery (Metzger 2008; Reece 2009). Description of the intervention First-line treatment for women with GDM is usually a lifestyle intervention combining dietary and exercise components. Where glycaemic treatment targets are not attained by lifestyle interventions alone, or where initial glucose levels are considered to be very high, the option for treatment is to introduce a pharmacological intervention. Current options include subcutaneous insulin or oral anti-diabetic pharmacological therapies. There has been an increase in the use of oral anti-diabetic pharmacological therapies as an alternative to subcutaneous insulin (Ogunyemi 2011) for the treatment of women with GDM, due to lower costs, ease of administration and acceptability (Ryu 2014). The most commonly used therapies are glyburide (glibenclamide) and metformin, although there are other less frequently used anti- 7

11 diabetic pharmacological therapies such as acarbose (Kalra 2015). Despite their wide use, oral antidiabetic pharmacological therapies are not licensed for use during pregnancy in many countries (including Australia, New Zealand, UK, USA). First generation sulphonylureas First generation sulphonylureas, such as chlorpropamide and tolbutamide have been used to treat diabetes in pregnancy in the past. Both drugs cross the placenta and have been associated with prolonged neonatal hypoglycaemia (Christesen 1998; Kemball 1970). Second generation sulphonylureas Second generation sulphonylureas, such as glibenclamide (glyburide) or glipizide work by enhancing insulin secretion. In pregnancy, studies have focused on the use of glibenclamide as it was shown to have the least placental passage in vitro (Elliott 1991). However, with improved assays it is now estimated that cord plasma concentrations of glibenclamide can be 70% to 77% of maternal levels (Schwarz 2013). Glibenclamide is completely metabolised by the liver and the metabolites are excreted equally in bile and urine. Oral tablets are administered at a typical dose of 2.5 to 5 mg taken once a day. Dosage can be increased if glycaemic control is not achieved in increments of 2.5 mg daily at intervals of every seven days (Brayfield 2014). The maximum daily dose is usually 15 mg taken in divided doses. Glibenclamide is associated with weight gain during pregnancy and postpartum and maternal hypoglycaemia (Simmons 2015). Other commonly reported side effects include nausea, vomiting, sensations of fullness, abdominal pain, anorexia, heartburn and diarrhoea. Less common side effects include abnormal liver function, haematological reactions and dermatological reactions ( Glibenclamide is contraindicated in cases of renal and hepatic insufficiency ( Langer 2000 reported equivalence between glyburide and subcutaneous insulin for the primary outcome of glycaemic control and reported that glibenclamide was not detected in the cord blood of any of the babies whose mother had been treated with glibenclamide in their trial. Metformin Metformin is a biguanide that can be administered in immediate-release or sustained-release oral preparations. The drug is absorbed along the entire gastrointestinal mucosa, but absorption is incomplete. Typical doses and dose scheduling of metformin provide steady-state plasma concentrations within 24 to 48 hours of administration and are generally less than 1 microgram/ml. Metformin is excreted unchanged in the urine and is not metabolised by the liver. Tablets should be taken in divided doses with meals. The initial dose is typically 500 mg taken once or twice daily and may be increased over subsequent weeks, dependent on glycaemic control, up to a maximum of 1000 mg three times per day ( In clinical trials using metformin during pregnancy the maximum dose is 2500 mg daily (Rowan 2008). Renal insufficiency is reported as a contra-indication to the prescription of metformin ( Metformin is known to cross the placenta although there is no evidence to suggest that this leads to fetal abnormalities (Ekpebegh 2007; Gilbert 2006). Maternal lactic acidosis is a rare (0.03 cases per 1000 patient years) but is a serious metabolic condition that is associated with accumulation of metformin during treatment ( Metformin is commonly associated with gastrointestinal disturbances (diarrhoea, nausea, vomiting) (Simmons 2015). Mild erythema, reduced vitamin B12 absorption and a metallic taste are also reported as side effects of metformin ( As very little metformin is transferred to human breast milk it is thought to be safe during breastfeeding (Simmons 2015). A sentinel trial conducted by Rowan 2008 reported equivalence between metformin and subcutaneous insulin for maternal and infant outcomes. Combined metformin and glibenclamide Metformin and glibenclamide are available in some regions in a combined formulation (Europe, USA). Acarbose Acarbose is an alpha-glucosidase inhibitor that delays the digestion of carbohydrates, thus resulting in a reduced increase in postprandial blood glucose concentrations ( scripts/cder/daf/). The typical initial dose is 75 to 150 mg taken in three divided doses. This can be further increased to a maximum of 600 mg per day (in divided doses) after four to eight weeks. Acarbose is metabolised within the gastrointestinal tract and the small amount that is excreted is via the urine ( Animal studies have not found an association between acarbose and fetal teratogenicity, but data are lacking in human studies (Kalra 2015). Acarbose is not associated with maternal hypoglycaemia but is frequently associated with gastrointestinal side effects (Simmons 2015). Acarbose is contraindicated in people with inflammatory bowel disease or similar conditions, malabsorption syndromes, severe hepatic or renal impairment ( Oral insulin Oral insulin is currently under research development for the treatment of diabetes mellitus, which may include GDM (Fonte 2013; Iyer 2010). This systematic review will not include trials of oral insulin as they will be included in the review of Insulin for the treatment of women with gestational diabetes (Brown 2016). 8

12 How the intervention might work Glibenclamide Glibenclamide stimulates increased insulin secretion by binding to pancreatic beta-cell receptors. There is reduced basal hepatic glucose production and enhancement of peripheral insulin action at post-receptor (probably intracellular) sites. The mechanism of action of glibenclamide requires functional beta-cells (Patanè 2000). Glibenclamide also inhibits glucagon-producing alpha cells in the pancreas and increases the release of somatostatin. There is a mild diuretic action which increases free water clearance (Radó 1974). O B J E C T I V E S To evaluate the effects of oral anti-diabetic pharmacological therapies for treating women with GDM. M E T H O D S Criteria for considering studies for this review Metformin Metformin actions are not completely understood but it inhibits glucogenesis in the liver, delays glucose absorption from the gastrointestinal tract and stimulates glucose uptake into the peripheral tissues. It has been suggested that as metformin increases insulin sensitivity, it does not stimulate insulin release, but does require the presence of insulin to potentiate its antihyperglycaemic effect. Both fasting and post-prandial blood glucose are lowered in individuals with diabetes. As metformin does not stimulate insulin secretion it is not associated with an increase in hypoglycaemia in diabetic or non-diabetic populations ( Metformin may protect β-cell function in the baby/child/adult and as a consequence reduce the cross generational effects of obesity and type 2 diabetes (Simmons 2015). During pregnancy the pharmacological action of metformin is altered slightly due to enhanced renal elimination, varying food absorption and gastrointestinal transit times (Simmons 2015). Acarbose Acarbose does not enhance insulin secretion. It reduces intestinal carbohydrate absorption by inhibiting the cleavage of disaccharides and oligosaccharides to monosaccharides in the small intestine resulting in reduced glucose absorption and lower post-prandial glucose concentrations (Kalra 2015). Why it is important to do this review Although oral anti-diabetic pharmacological therapies are more acceptable to women with GDM (Rowan 2008), cost less and are easier to administer than subcutaneous insulin, the safety of these therapies is still unclear. The comparison of subcutaneous or oral insulin with oral anti-diabetic pharmacological therapies is the subject of a new Cochrane Review and will not therefore be covered in this review. The superiority of one anti-diabetic pharmacological therapy over another has not previously been addressed by a Cochrane systematic review. Types of studies We included published or unpublished randomised, quasi-randomised or cluster-randomised trials in full text or abstract format. We excluded cross-over trials. Conference abstracts were handled in the same way as full publications. Types of participants Participants were pregnant women diagnosed with gestational diabetes mellitus (GDM) (diagnosis as defined by the individual trial). Women with type 1 or type 2 diabetes diagnosed prior to pregnancy were excluded. Types of interventions We included those anti-diabetic pharmacological therapies that were used during pregnancy including metformin, glibenclamide, acarbose, tolbutamide, chlorpropamide or any combination of these therapies. Only oral anti-diabetic pharmacological therapies were included in this review. We will include any new therapies prescribed for the treatment of women with GDM in updates of the review. Oral anti-diabetic pharmacological therapy versus placebo or no pharmacological treatment. A single oral anti-diabetic pharmacological therapy versus an alternative oral anti-diabetic pharmacological therapy (drug A versus drug B). Any combination of oral anti-diabetic pharmacological therapies versus any combination of oral anti-diabetic pharmacological therapies (drug A followed by drug B versus drug B followed by drug A for example). Oral anti-diabetic pharmacological therapy versus another intervention (excluding insulin) not specified above. We have not included the comparison of oral anti-diabetic pharmacological therapies versus insulin in this review as it will be covered in the review entitled Insulin for the treatment of women with gestational diabetes (Brown 2016). 9

13 Types of outcome measures Primary outcomes Maternal Hypertensive disorders of pregnancy (including preeclampsia, pregnancy-induced hypertension, eclampsia as defined by trialists) Caesarean section Development of type 2 diabetes Neonatal Perinatal (fetal and neonatal death) and later infant mortality Large-for-gestational age (LGA) (as defined by trialists) Death or serious morbidity composite (variously defined by trials, e.g. perinatal or infant death, shoulder dystocia, bone fracture or nerve palsy) Neurosensory disability in later childhood (as defined by trialists) Secondary outcomes Maternal Use of additional pharmacotherapy Maternal hypoglycaemia (as defined by trialists) Glycaemic control during/end of treatment (as defined by trialists) Weight gain in pregnancy Adherence to the intervention Induction of labour Placental abruption Postpartum haemorrhage (as defined by trialists) Postpartum infection Perineal trauma/tearing Breastfeeding at discharge, six weeks postpartum, six months or longer Maternal mortality Sense of well-being and quality of life Behavioural changes associated with the intervention Views of the intervention Relevant biomarker changes associated with the intervention (including adiponectin, free fatty acids, triglycerides, high-density lipoproteins, low-density lipoproteins, insulin) Long-term outcomes for mother Postnatal depression Body mass index (BMI) Postnatal weight retention or return to pre-pregnancy weight Type 1 diabetes Type 2 diabetes Impaired glucose tolerance Subsequent gestational diabetes Cardiovascular health (as defined by trialists including blood pressure, hypertension, cardiovascular disease, metabolic syndrome) Fetal/neonatal outcomes Stillbirth Neonatal death Macrosomia (greater than 4000 g; or as defined by individual study) Small-for-gestational age (as defined by trialists) Birth trauma (shoulder dystocia, bone fracture, nerve palsy) Gestational age at birth Preterm birth (less than 37 weeks gestation; and less than 32 weeks gestation) Five-minute Apgar less than seven Birthweight and z score Head circumference and z score Length and z score Ponderal index Adiposity (including skinfold thickness measurements (mm), fat mass) Neonatal hypoglycaemia (as defined by trialists) Respiratory distress syndrome Neonatal jaundice (hyperbilirubinaemia) (as defined by trialists) Hypocalcaemia (as defined by trialists) Polycythaemia (as defined by trialists) Relevant biomarker changes associated with the intervention (including insulin, cord c-peptide) Later Infant/childhood outcomes Weight and z scores Height and z scores Head circumference and z scores Adiposity (including BMI, skinfold thickness, fat mass) Educational attainment Blood pressure Type 1 diabetes Type 2 diabetes Impaired glucose tolerance Dyslipidaemia or metabolic syndrome 10

14 Child as an adult outcomes Weight Height Adiposity (including BMI, skinfold thickness, fat mass) Cardiovascular health (as defined by trialists including blood pressure, hypertension, cardiovascular disease, metabolic syndrome) Employment, education and social status/achievement Dyslipidaemia or metabolic syndrome Type 1 diabetes Type 2 diabetes Impaired glucose tolerance Health service use Number of antenatal visits or admissions Number of hospital or health professional visits (including midwife, obstetrician, physician, dietician, diabetic nurse) Admission to neonatal intensive care unit/nursery Length of antenatal stay Length of postnatal stay (maternal) Length of postnatal stay (baby) Cost of maternal care Cost of offspring care Costs associated with the intervention Costs to families associated with the management provided Cost of dietary monitoring (e.g. diet journals, dietician, nurse visits, etc) Costs to families - change of diet, extra antenatal visits Extra use of healthcare services (consultations, blood glucose monitoring, length and number of antenatal visits) Women s view of treatment advice Duration of stay in neonatal intensive care unit or special care baby unit Duration of maternal and neonatal hospital stay (antenatal, neonatal, postnatal) and conference proceedings, and the list of journals reviewed via the current awareness service, please follow this link to the editorial information about the Cochrane Pregnancy and Childbirth in the Cochrane Library and select the Specialized Register section from the options on the left side of the screen. Briefly, Cochrane Pregnancy and Childbirth s Trials Register is maintained by their Information Specialist and contains trials identified from: 1. monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL); 2. weekly searches of MEDLINE (Ovid); 3. weekly searches of Embase (Ovid); 4. monthly searches of CINAHL (EBSCO); 5. handsearches of 30 journals and the proceedings of major conferences; 6. weekly current awareness alerts for a further 44 journals plus monthly BioMed Central alerts. Search results are screened by two people and the full text of all relevant trial reports identified through the searching activities described above is reviewed. Based on the intervention described, each trial report is assigned a number that corresponds to a specific Pregnancy and Childbirth review topic (or topics), and is then added to the Register. The Information Specialist searches the Register for each review using this topic number rather than keywords. This results in a more specific search set that has been fully accounted for in the relevant review sections (Included studies; Excluded studies; Studies awaiting classification; Ongoing studies). In addition, we searched ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) for unpublished, planned and ongoing trial reports (14 May 2016). The search terms we used are given in Appendix 1. Searching other resources We searched the reference lists of retrieved studies. We did not apply any language or date restrictions. Search methods for identification of studies The following methods section of this review is based on a standard template used by Cochrane Pregnancy and Childbirth. Electronic searches We searched Cochrane Pregnancy and Childbirth s Trials Register by contacting their Information Specialist (16 May 2016). The Register is a database containing over 22,000 reports of controlled trials in the field of pregnancy and childbirth. For full search methods used to populate Pregnancy and Childbirth s Trials Register including the detailed search strategies for CENTRAL, MED- LINE, Embase and CINAHL; the list of handsearched journals Data collection and analysis The following methods section of this review is based on a standard template used by Cochrane Pregnancy and Childbirth. 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 disagreements through discussion. A third person was not required. We created a study flow diagram to map out the number of records identified, included and excluded (Figure 1). 11

15 Figure 1. Study flow diagram 12

16 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. Consultation with a third person was not required. We entered data into Review Manager (RevMan) software (RevMan 2014) 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 2011a). We resolved any disagreement by discussion. Consultation with a third person was not required. intervention a participant received. We considered that studies were at low risk of bias if they were blinded, or if we judge 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. (1) Random sequence generation (checking for possible selection bias) We described for each included study the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups. We assessed the method 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 allocation to interventions prior to assignment and will assess 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 nonopaque 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 used, if any, to blind study participants and personnel from knowledge of which (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 and 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. No additional data that could be included in a meta-analysis were supplied by study authors. In future updates, where sufficient information is reported, or can be supplied by the study authors, we will re-include missing data in the analyses which we undertake. We assessed methods as: low risk of bias (e.g. no missing outcome data; missing outcome data 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 (checking for reporting bias) We described for each included study how we investigated the possibility of selective outcome reporting bias and what we found. We assessed the methods as: low risk of bias (where it was clear that all of the study s prespecified outcomes and all expected outcomes of interest to the review were reported); 13

17 high risk of bias (where not all the study s pre-specified outcomes were 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 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 high risk of bias, according to the criteria given in the Cochrane Handbook for Systematic Reviews of Interventions(Higgins 2011a). With reference to (1) to (6) above, we assessed the likely magnitude and direction of the bias and whether we considered it was likely to impact on the findings. We planned to explore the impact of the level of bias through undertaking sensitivity analyses - see Sensitivity analysis. Assessment of the quality of the evidence using the GRADE approach We assessed the quality of the evidence using the GRADE approach as outlined in the GRADE Handbook in order to assess the quality of the body of evidence relating to the following outcomes. We selected up to a maximum of seven outcomes for the mother and seven for the infant covering both short- and longterm outcomes for the main comparisons. Neonatal outcomes LGA Perinatal mortality Death or serious morbidity composite (variously defined by studies, e.g. infant death, shoulder dystocia, bone fracture or nerve palsy) Neonatal hypoglycaemia Adiposity Diabetes Neurosensory disability in later childhood We used the GRADEpro Guideline Development Tool ( GRADEpro GDT) to import data from RevMan (RevMan 2014) in order to create Summary of findings tables. We produced a summary of the intervention effect and a measure of quality for each of the above outcomes using the GRADE approach. The GRADE approach uses five considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of the body of evidence for each outcome. The evidence can be downgraded from high quality by one level for serious (or by two levels for very serious) limitations, depending on assessments for risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates or potential publication bias. Measures of treatment effect Dichotomous data For dichotomous data, we presented results as summary risk ratio (RR) with 95% confidence intervals (CI). Continuous data For continuous data, we used the mean difference (MD) if outcomes were measured in the same way between trials. We used the standardised mean difference (SMD) to combine data from trials that measured the same outcome, but used different methods. Unit of analysis issues Maternal outcomes Hypertensive disorders of pregnancy (including preeclampsia, pregnancy-induced hypertension, eclampsia) Caesarean section Development of type 2 diabetes Perineal trauma Return to pre-pregnancy weight Postnatal depression Induction of labour Cluster-randomised trials We did not identify any cluster-randomised controlled trials in this version of the systematic review. In future updates, if cluster-randomised trials are identified, we will include cluster-randomised trials in the analyses along with individually-randomised trials. We will make adjustments using the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Section or ) using an estimate of the intra-cluster correlation co-efficient (ICC) derived from the trial (if possible), 14

18 from a similar trial or from a study of a similar population (Higgins 2011b). If we use ICCs from other sources, we will report this and conduct sensitivity analyses to investigate the effect of variation in the ICC. We will consider it reasonable to combine the results from both cluster-randomised trials and individually-randomised trials if there is little heterogeneity between the study designs and the interaction between the effect of intervention and the choice of randomisation unit is considered to be unlikely. If cluster-randomised trials are included, we will seek statistical advice on appropriate analysis to enable inclusion of data in the meta-analyses. Other unit of analysis issues Multiple pregnancy There may be unit of analysis issues that arise when the women randomised have a multiple pregnancy. We did not include any studies including multiple pregnancies in this version of the systematic review. In future updates, if multiple pregnancies are identified, we will present maternal data as per woman randomised and neonatal data per infant. Multiple-arm studies Where a trial has multiple intervention arms we planned to avoid double counting of participants by combining groups to create a single pair-wise comparison if possible. Where this was not possible, we planned to split the shared group into two or more groups with smaller sample size and include two or more (reasonably independent) comparisons. We did not identify any studies of multiple comparisons in this version of the systematic review. 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 (more than 20%) in the overall assessment of treatment effect by using sensitivity analysis. However, one of the included studies reported attrition greater than 20% (De Bacco 2015) and therefore we did not conduct sensitivity analyses based on attrition in this version of the review. In future updates we plan to explore attrition for sensitivity analysis if sufficient evidence is available. For all outcomes, we carried out analyses, as far as possible, on an intention-to-treat basis, that is, 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 (Higgins 2003) and Chi² statistics. We regarded heterogeneity as substantial if an I² was greater than 40% and either a 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 If there were 10 or more studies in the meta-analysis, we planned to investigate reporting biases (such as publication bias) using funnel plots. This was not possible in this version of the review. In future updates, where possible, 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 2014). We used fixed-effect meta-analysis for combining data where it was reasonable to assume that studies were estimating the same underlying treatment effect: that is, where trials were examining the same intervention, and the trials populations and methods were judged sufficiently similar. If there was clinical heterogeneity sufficient to expect that the underlying treatment effects differed between trials, or if 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 of the range of possible treatment effects and we tried to discuss the clinical implications of treatment effects differing between trials. If the average treatment effect was not clinically meaningful, we did not combine trials. If we used random-effects analyses, the results were presented as the average treatment effect with 95% CIs, and the estimates of Tau² and I². Subgroup analysis and investigation of heterogeneity If we identified substantial heterogeneity, we investigated it using subgroup analyses. We considered whether an overall summary was meaningful, and if it was, used random-effects analysis to produce it. Diagnostic tests used ADA 2013, IADPSG 2010, Nankervis 2014 versus ACOG 2013 versus NICE 2015 versus NICE 2008; WHO 1999; WHO 2014; Hoffman 1998 versus New Zealand Ministry of Health 2014 versus other not previously specified. 15

19 Timing of diagnosis of GDM Early (< 28 weeks gestation) versus late ( 28 weeks gestation) There was insufficient data for us to be able to explore subgroup analyses for this review. In future updates, if there is sufficient evidence, we plan to use the following outcomes in subgroup analysis. Maternal outcomes Pre-eclampsia Caesarean section Development of type 2 diabetes Neonatal outcomes LGA Perinatal death or later infant mortality Death or serious morbidity composite (variously defined by trials, e.g. infant death, shoulder dystocia, bone fracture or nerve palsy) Neurosensory disability in later childhood (as defined by trialists). We assessed subgroup differences by interaction tests available within RevMan (RevMan 2014). We reported the results of subgroup analyses quoting the Chi 2 statistic and P value, and the interaction test I² value. Sensitivity analysis Where there was evidence of substantial heterogeneity, we explored this by using the quality of the included trials for the primary outcomes. We planned to compare trials that had low risk of bias for allocation concealment with those judged to be of unclear or high risk of bias. We planned to exclude conference abstracts from the meta-analysis. In future updates, where data are available we plan to investigate the effect of the randomisation unit (i.e. where included clusterrandomised trials along with individually-randomised trials). R E S U L T S Description of studies Results of the search We identified 28 potential reports for inclusion in the review (Figure 1). Eleven studies (20 reports) were included and five studies were excluded. Two studies (Coiner 2015; Sheizaf 2006) are awaiting classification and one study (Moore 2016) is ongoing (see Characteristics of studies awaiting classification; Characteristics of ongoing studies). Included studies Eleven studies (20 reports) were identified that met the inclusion criteria for this review (Bertini 2005; Casey 2015; Cortez 2006; De Bacco 2015; Fenn 2015; George 2015; Moore 2010; Myers 2014; Nachum 2015; Notelovitz 1971; Silva 2012). Three of these were published in conference abstract format only (Cortez 2006; De Bacco 2015; Nachum 2015). Design All 11 studies were randomised parallel design. Sample sizes The 11 studies recruited a total of 1487 women and their babies. Sample size ranged from 40 women reported by Myers 2014 to 207 women reported by Notelovitz Setting Three studies were conducted in Brazil (Bertini 2005; De Bacco 2015; Silva 2012) and USA (Casey 2015; Cortez 2006; Moore 2010). Two studies were conducted in India (Fenn 2015; George 2015). One study each was conducted in South Africa (Notelovitz 1971), UK (Myers 2014) and Israel (Nachum 2015). Participants Maternal age was reported in six of the 11 studies (Table 2), maternal body mass index (BMI) (kg/m 2 ) was reported in five of 11 studies (Table 3) and gestational age at study entry was reported in four of 11 studies (Table 4). Interventions and comparisons Four different comparisons were reported. Oral anti-diabetic pharmacological therapy versus placebo or usual care One study compared glibenclamide with placebo (Casey 2015); one study compared acarbose with placebo (Cortez 2006), one study compared metformin with standard care (Myers 2014) and one study compared tolbutamide and chlorpropamide with diet (Notelovitz 1971). 16

20 Metformin versus glibenclamide Five studies compared metformin with glibenclamide (De Bacco 2015; Fenn 2015; George 2015; Moore 2010; Silva 2012). Glibenclamide versus acarbose One study compared glibenclamide with acarbose (Bertini 2005). Glibenclamide with or without metformin versus metformin with or without glibenclamide One study compared glibenclamide plus metformin if glycaemic targets were not met, with metformin plus glibenclamide if glycaemic targets were not met (Nachum 2015). Diagnostic criteria Four different diagnostic criteria were used by the eight studies that reported this. George 2015 and Casey 2015 used the National Diabetes Data Group (NDGG 1979) Bertini 2005 and Silva 2012 used WHO (1999) criteria Three studies (Fenn 2015; Moore 2010; Nachum 2015) used Carpenter and Coustan criteria De Bacco 2015 used WHO criteria but the abstract did not state if this was 1999 or 2015 criteria Cortez 2006, Myers 2014 and Notelovitz 1971 did not state which diagnostic criteria they used Refer to Table 1 and Table 5. Treatment targets Eight studies reported three different treatment targets for fasting blood glucose (Refer to Table 6): less than 5.0 mmol/l (90 mg/dl) (Bertini 2005; Silva 2012); less than 5.3 mmol/l (95 mg/dl) (Casey 2015; Cortez 2006; Fenn 2015; George 2015; Nachum 2015); less than 5.8 mmol/l (105 mg/dl) (Moore 2010). Four studies reported four different treatment targets for one-hour postprandial blood glucose: less than 6.7 mmol/l (120 mg/dl) (Silva 2012); less than 7.2 mmol/l (130 mg/dl) (George 2015) 90 minutes; less than 7.5 mmol/l (135 mg/dl) (Cortez 2006); less than 7.8 mmol/l (140 mg/dl) (Fenn 2015). Four studies reported two different treatment targets for two-hour postprandial blood glucose: less than 5.5 mmol/l (100 mg/dl) (Bertini 2005); less than 6.7 mmol/l (120 mg/dl) (Casey 2015; George 2015; Moore 2010). Notelovitz 1971 reported good control was obtained with a postprandial (timing not specified) blood glucose reading of less than 8.3 mmol/l (150 mg/dl). De Bacco 2015 and Myers 2014 did not provide details of glycaemic targets for treatment. The Notelovitz 1971 study included women with both GDM and pre-gestational diabetes. The proportions of women included with each type of diabetes were unclear and therefore the data have not been included in any meta-analyses. See Characteristics of included studies. Excluded studies We excluded five studies. One study comparing metformin and placebo was registered with the clinical studies registry ClinicalTrials.gov in Subsequent updates indicate that the study never started recruitment due to insufficient funding for enrolment of participants (Branch 2010). Hebert 2011, was a pharmacokinetic study and not an interventional study. We excluded Ainuddin 2013 as the comparison was ineligible for inclusion in this review, the trial compared metformin and insulin. We excluded two studies as the intervention was postpartum (Berens 2015; Smith 2015). See Characteristics of excluded studies. Risk of bias in included studies Refer to Figure 2; Figure 3 and Characteristics of included studies for risk of bias summaries of the included studies. 17

21 Figure 2. Risk of bias graph: review authors judgements about each risk of bias item presented as percentages across all included studies 18

22 Figure 3. Risk of bias summary: review authors judgements about each risk of bias item for each included study 19