Skip to main content

Assisted reproductive technology and the risk of gestational diabetes mellitus: a systematic review and meta-analysis

Abstract

Background

The use of assisted reproductive technology (ART) is increasing worldwide, and observational studies have indicated that women who conceived by ART have an increased risk of pregnancy complications including gestational diabetes mellitus (GDM). We aimed to determine the risk of GDM among women who conceived with ART by systematic review and meta-analysis.

Main text

A systematic literature search was conducted in ISI Web of Knowledge, MEDLINE, Scopus, and Embase through May 2017 for English-language articles using a list of keywords. All studies comparing GDM in women conceived by ART and those who conceived spontaneously were included. Data extraction was performed by two authors independently and discrepancies were resolved by discussion. In total, 48 studies with 91,487 pregnancies conceived through ART and 2,525,234 spontaneously conceived met the inclusion criteria. There was evidence of substantial heterogeneity among these studies (P < 0.001, I2 = 98.6%). Random effects meta-analysis showed a significant increase in GDM among those who conceived by ART compared with those who conceived spontaneously (pooled relative risk = 1.51, 95% confidence interval = 1.18–1.93). Visual inspection of the funnel plot did not reveal any publication bias, which was supported by Egger’s test and Begg’s test.

Conclusion

The findings of this systematic review indicate that the use of ART treatment is associated with a 1.51-fold increase in GDM. Women need to be counselled carefully before undergoing ART treatment about the possibility and risk of GDM.

Background

Assisted reproductive technology (ART) is a group of medical methods for treating the infertile human in which both male and female gametes are used outside the body to achieve pregnancy [1]. To date, approximately 5 million babies are born worldwide via ART [2]. Although ART may help infertile couples, its use has increased concerns associated with pregnancy-related complications and adverse consequences [3]. It has been suggested that obstetric outcomes in gestation after ART are poor when compared with those pregnancies spontaneously conceived [4]. Moreover, evidence from meta-analyses [4,5,6,7,8] has revealed that singleton pregnancies after ART are at higher risk of adverse consequences than those conceived naturally. One of the outcomes followed by ART is gestational diabetes mellitus (GDM) and is known as one of the most common complications in pregnancy [9, 10]. GDM is defined as “carbohydrate intolerance of variable severity with onset or first recognition during pregnancy” [11]. GDM is a worldwide public health problem and complicates about 7% of all pregnancies [12, 13]. The cause and pathogenesis of GDM is both multifunctional and complex [14]. GDM is prone to causing a woman and her baby a wide range of complications during pregnancy and in later life [15, 16]. women with GDM are more likely to develop metabolic syndrome in the future, including type 2 diabetes [17]. Therefore, it is important to realize the risk factors of GDM such as family history of diabetes, obesity, high parity, advanced maternal age, previous adverse pregnancy, non-white race, history of a baby with birth weight > 3800 g, and hypothyroidism [12, 18].

In addition, studies have indicated that ART pregnancies are related to an increased risk of GDM [19,20,21,22]. Another study in Australia reported those who underwent ART are more prone to experience GDM compared to those who conceived spontaneously [23]. However, it was shown in another study that the rate of GDM was lower in women who conceived under intracytoplasmic sperm injection (ICSI) compared to those of spontaneously, in vitro fertilization (IVF) or simple ART [24]. Finally, we conducted a meta-analysis to provide an up-to-date survey of pregnancies resulting from ART and the increased risk of GDM between 1997 and 2017. We aimed to investigate the higher risk of GDM in pregnancies following ART and compare them to those of spontaneous conceptions.

Material and methods

Search strategy

This systematic review adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist [25]. We searched the electronic databases ISI Web of Knowledge, MEDLINE/PubMed, Scopus, and Embase through May 2017, for studies investigating the relationship between ART and GDM. The search terms used were presented in Table 1. Reference lists from all identified studies were also searched for any relevant articles. Two authors (MM and AA) evaluated the studies, and discrepancies were resolved by discussion.

Table 1 Search strategy for MEDLINE (MeSH, Medical Subject Headings)

Inclusion and exclusion criteria

We included published studies that examined the relationship between the use of ART and the risk of GDM. No restriction criteria were imposed with regard to the size or type of the studied population, nor to the type of ART treatment. The following study types were excluded from the analyses: (a) non-English articles; (b) animal studies; (c) repeated or overlapping studies; (d) reviews, meta-analyses, case reports, editorials, and letters-to-the-editor articles; and (e) unpublished studies.

Outcome and exposure

The exposure variable was all types of ART treatment. Our outcome was GDM, defined as “carbohydrate intolerance of variable severity with onset or first recognition during pregnancy” [11].

Data extraction and quality assessment

Two reviewers (MM and AA) independently abstracted the following data from all eligible articles: first author’s name; year of publication; location; study period; design; sample size; type of ART; and study findings. Discrepancies were resolved by discussion between two reviewers.

Quality assessment of included studies was performed independently by two reviewers using the Newcastle–Ottawa Scale (NOS) [26]. The NOS assesses the methodological quality of the observational studies according to three domains: (a) selection of study groups; (b) comparability of groups; and (c) ascertainment of exposure and outcomes. Total scores range from 0 (lowest quality) to 9 (highest quality).

Statistical analysis

Data were analyzed using STATA version 13.0 (Stata Corp, College Station, TX, USA). The pooled relative risk (RR) was calculated with its 95% confidence interval (CI) to assess the strength of the association between the use of ART and GDM risk. To assess between study heterogeneity, both the Cochran Q test and the I2 statistic (the percentage of total variation across studies attributable to heterogeneity beyond chance) were calculated [27]. I2 values of 25, 50, and 75% were used as evidence of low, moderate, and high heterogeneity, respectively [27]. Subgroup analysis was performed to detect factors that may explain heterogeneity in outcome between each study. Publication bias was assessed using visual inspection of a funnel plot, Egger’s test, and Begg’s test [28, 29]. In all statistical tests, results with P < 0.05 were deemed statistically significant, except for the Cochran Q test where P < 0.10 was used.

Results

Study selection

The steps of the study selection are displayed in Fig. 1. A total of 950 related published articles were retrieved by using a search strategy in four international databases (638 from Scopus, 91 from PubMed, 62 from ISI Web of Knowledge, and 159 from Embase) and also seven records were identified from Google Scholar and reference lists of final included papers in the meta-analysis. In this study, 829 papers remained after removing duplicate papers using EndNote software. After title and abstract screening, 278 relevant articles were recognized as eligible and they were considered for additional full-text screening. After excluding 230 non-eligible studies, finally, 48 studies (four case-control studies, three cross-sectional studies, and 41 cohort studies) were included in this meta-analysis.

Fig. 1
figure1

Flow diagram of the literature search for studies included in meta-analysis

Study characteristics

The study characteristics of the included studies are summarized in Table 2. In total, we included 48 studies published from 1987 to 2017. Observational studies (i.e., cross-sectional, case control and cohort studies) were included in the meta-analysis, whereas non-English studies and studies without relevant data or partial data were excluded. Sample size in the ART group ranged from 31 to 21,615 cases and in the non-ART group it ranged from 20 to 595,168 cases. Of the 48 studies, 19 were conducted in Asia, 17 in Europe, and 12 in America. Fourteen studies were published before 2011 and 34 studies were published from 2011 to 2017.

Table 2 Characteristics of the primary studies included in the meta-analysis

Quantitative data synthesis

In the present study, 91,487 ART cases (with 6819 cases of GDM) and 2,525,234 non-ART cases (with 113,505 cases of GDM) were included in the analysis. RRs and their 95% CIs were calculated using the Mantel–Haenszel method and, because of significant heterogeneity between studies, random effect models were also used. The relationship of ART and the risk of GDM was estimated using 48 included primary studies. The summary estimate of RR in this meta-analysis suggested that ART significantly was associated with higher risk of GDM (pooled RR = 1.51, 95% CI = 1.18–1.93, P = 0.001); that is, the risk of GDM in the ART group is 1.51 times compared to that in the non-ART group (Fig. 2 and Table 3).

Fig. 2
figure2

Forest plot showing the risk of GDM following ART

Table 3 Summary of meta-analysis results and subgroups analysis

Heterogeneity analysis

To check the heterogeneity between studies, chi-square test, I-squared, and Tau-squared were conducted. Chi-square analysis revealed that there was a significant heterogeneity between primary studies (P < 0.001, I2 = 98.6%); consequently, to pool the effect sizes in this study, a random effect model was used. To find the source of heterogeneity between studies, subgroup analyses were performed on the basis of study design, study region, and study period (Table 3). Even after the aforementioned subgroup analyses, heterogeneity across the studies did not diminish successfully in all subgroups; for that reason, some estimations of pooled RR were measured by the random effects model and only pooled RR for case control studies and the papers that were published between 1987 and 2010 were estimated by a mixed-effect model (Figs. 3, 4 and 5).

Fig. 3
figure3

Forest plot showing the risk of GDM following ART on the basis of study design

Fig. 4
figure4

Forest plot showing the risk of GDM following ART on the basis of time period

Fig. 5
figure5

Forest plot showing the risk of GDM following ART on the basis of region

Risk of publication bias

Graphical (funnel plot) and statistical tools (Begg’s and Egger’s test) were done to test the existence of publication bias in the studies. The results of the symmetrical funnel plot (Fig. 6), Egger’s test (P = 0.331), and Begg’s test (P = 0.810) suggested that there was no significant publication bias in this study.

Fig. 6
figure6

Funnel plot to assess the presences of publication bias

Discussion

The current study aimed to assess the impact of ART on GDM using a systematic review of related articles. This meta-analysis included 344,021 cases, in which 91,487 cases used ART to achieve pregnancy. Statistical approaches were determined based on the heterogeneity of the included studies and publication bias was checked. Several subgroups were defined based on the study design, time period, and region.

The results from this meta-analysis revealed that GDM is strongly affected by the use of ART. The relative risk of GDM was significant regarding the use of ART. Regarding the magnitude of the RR, the results from different study designs were in accordance. However, the included cross-sectional studies did not report a significant pooled RR in contrast to cohort and case-control studies and this might be due to the lower number of cross-sectional studies. Moreover, the impact of ART on GDM did not differ in two distinct periods of time (2010 as the cut-off point). In contrast to America, consistent results were found in two regions of Asia and Europe. The pooled RR resulting from American studies showed a higher risk of GDM among those in the non-ART group.

The ART has been defined as treatments including in vitro handling of oocytes and sperm, and embryos, in which establishing pregnancy is the goal [76]. There have been many debates on the efficacy and safety of using ART regarding its increasing trend of use across most countries [77, 78]. It has been shown that ART is responsible for a high number of adverse pregnancy-related complications and obstetric outcomes such as polyhydramnios, low and very low infant birth weight, pregnancy-induced hypertension, pre-eclampsia, perinatal mortality, preterm and very preterm birth, placenta previa, antepartum hemorrhage, multiple pregnancy congenital malformation, higher risk of ectopic pregnancy, lower odds of vaginal delivery, postpartum hemorrhage, oligohydramnios, small for gestational age, and placental abruption [36, 79,80,81,82,83]. As mentioned, using ART was associated with GDM, which is diabetes diagnosed during pregnancy. Pregnancy may cause insulin resistance and hyperinsulinemia and can be followed by diabetes. GDM is defined as glucose intolerance with the first recognition during pregnancy and usually progresses in the second trimester [84]. GDM is associated with a large number of risk factors, such as elevated pre-pregnancy body mass index, older maternal age, history of GDM, diabetes among family members, polycystic ovary syndrome (PCOS), pre-existing hypertension, weight gain during pregnancy, smoking, ART, and higher parity [85,86,87]. The adverse effect of ART on GDM is discussed by several studies; however, the mechanism has not been well clarified [48, 52]. Several hypotheses are introduced in which GDM is influenced by the use of ART, including the etiology of infertility, the drugs used in the treatment procedure, the hormonal levels, and metabolic and vascular factors [19, 52]. However, it has been revealed that maternal age is the most effective factor on GDM [88]. Wang et al. have discussed the association between GDM and ART through impaired glucose tolerance in comparison to those of spontaneous conceptions. Moreover, they have exposed that for singleton mothers, GDM was more common among cases that underwent ART. However, the risk increases for singleton mothers younger than 40 [48]. Double embryo transfer has been introduced as a significant factor for multiple gestational pregnancy, which is followed by an elevated risk of GDM [89, 90]. Vitthala et al. assessed the risk of monozygotic twins after ART using a systematic review and they revealed that in comparison to cleavage embryo transfer, GDM is more affected by blastocyst transfer [91]. Hammoud et al. addressed the scientific question of whether it is important to diagnose GDM by screening or symptoms. They showed that GDM is strongly related to large-for-gestational-age births [92] and Sazonova et al. showed that babies after embryo transfer have a higher large for gestational age compared to fresh embryo transfer [93]. Pre-existing hypertension is associated with GDM [87] and this might be due to higher rates of ART mothers being of high maternal age [94]. Sibai and Ross assessed the pathophysiology and long-term consequences of hypertension in GDM. They demonstrated that mothers of twins are at a higher risk of GDM in contrast to those of singletons [90]. Risk of GDM among women with PCOS was assessed by Toulis et al. in a systematic review. They showed an increased likelihood of developing GDM among women with PCOS compared with general cases [95].

The current meta-analysis revealed a significant heterogeneity among the pooled studies, the cohort and cross-sectional studies, the studies conducted during 2011–2017, and the three regions of Asia, Europe, and America. Several statistical tools are available to check the heterogeneity of included studies in a meta-analysis and its selection mechanism depends on several factors such as sample size, the frequency of included studies, etc. The two common tests for heterogeneity (chi-square and the I2 value) can result in controversial conclusions regarding the number of included studies and the magnitude of the relative risks [96]. There might be many reasons for the presence of heterogeneity in the results, such as different cultural and ethnic conditions and diversity in the amount of regions’ development.

The present systematic review has several limitations that should be noted. First, the most important limitation for this study as for other meta-analysis studies is the lack of data for subgroup analysis based on type of pregnancy (singleton versus twin pregnancy), type of ART, or for data analysis controlling for known confounders. Second, there were no data on the relationship between ART and GDM for large regions such as Africa and Latin America, thus the generalizability of the results may be limited. Third, this study included only English papers.

In sum, the findings of the present systematic review and meta-analysis indicate that the use of ART is associated with a 1.51-fold increase in GDM. Women need to be counselled carefully before undergoing ART treatment about the possibility and risk of GDM.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

ART:

Assisted reproductive technology

CI:

Confidence interval

GDM:

Gestational diabetes mellitus

NOS:

Newcastle–Ottawa Scale

PCOS:

Polycystic ovary syndrome

RR:

Relative risk

References

  1. 1.

    Quintino-Moro A, Zantut-Wittmann DE, Tambascia M, Machado HdC, Fernandes A (2014) High prevalence of infertility among women with Graves’ disease and Hashimoto’s thyroiditis. Int J Endocrinol 2014:1–6

    Article  Google Scholar 

  2. 2.

    Kissin DM, Jamieson DJ, Barfield WD (2014) Monitoring health outcomes of assisted reproductive technology. N Engl J Med 371:91–93

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  3. 3.

    De Mouzon J, Lancaster P, Nygren KG, Sullivan E, Zegers-Hochschild F, Mansour R, Ishihara O, Adamson D (2009) World collaborative report on assisted reproductive technology, 2002. Hum Reprod 24:2310–2320

    PubMed  Article  PubMed Central  Google Scholar 

  4. 4.

    Pandey S, Shetty A, Hamilton M, Bhattacharya S, Maheshwari A (2012) Obstetric and perinatal outcomes in singleton pregnancies resulting from IVF/ICSI: a systematic review and meta-analysis. Hum Reprod Update 18:485–503

    PubMed  Article  PubMed Central  Google Scholar 

  5. 5.

    Helmerhorst FM, Perquin DA, Donker D, Keirse MJ (2004) Perinatal outcome of singletons and twins after assisted conception: a systematic review of controlled studies. BMJ 328:261

    PubMed  PubMed Central  Article  Google Scholar 

  6. 6.

    Jackson RA, Gibson KA, Wu YW, Croughan MS (2004) Perinatal outcomes in singletons following in vitro fertilization: a meta-analysis. Obstet Gynecol 103:551–563

    PubMed  Article  PubMed Central  Google Scholar 

  7. 7.

    McDonald SD, Murphy K, Beyene J, Ohlsson A (2005) Perinatal outcomes of singleton pregnancies achieved by in vitro fertilization: a systematic review and meta-analysis. J Obstet Gynaecol Can 27:449–459

    PubMed  Article  PubMed Central  Google Scholar 

  8. 8.

    McGovern PG, Llorens AJ, Skurnick JH, Weiss G, Goldsmith LT (2004) Increased risk of preterm birth in singleton pregnancies resulting from in vitro fertilization–embryo transfer or gamete intrafallopian transfer: a meta-analysis. Fertil Steril 82:1514–1520

    PubMed  Article  PubMed Central  Google Scholar 

  9. 9.

    Salmeen K (2016) Gestational diabetes testing: making sense of the controversy. J Midwifery Womens Health 61:203–209

    PubMed  Article  PubMed Central  Google Scholar 

  10. 10.

    Bartolo S, Vambergue A, Deruelle P (2016) Screening for gestational diabetes: Still many unsolved issues. J Gynecol Obstet Biol Reprod (Paris) 45:105–111

    CAS  Article  Google Scholar 

  11. 11.

    Metzger BE, Coustan DR, Committee O (1998) Summary and recommendations of the fourth international workshop-conference on gestational diabetes mellitus. Diabetes Care 21:B161–B167

    PubMed  PubMed Central  Google Scholar 

  12. 12.

    Association, A.D (2004) Gestational diabetes mellitus. Diabetes Care 27:S88–S90

    Article  Google Scholar 

  13. 13.

    Cheng YW, Block-Kurbisch I, Caughey AB (2009) Carpenter-Coustan criteria compared with the national diabetes data group thresholds for gestational diabetes mellitus. Obstet Gynecol 114:326–332

    PubMed  Article  PubMed Central  Google Scholar 

  14. 14.

    Kuhl C (1998) Etiology and pathogenesis of gestational diabetes. Diabetes Care 21:B19–B26

    PubMed  Article  PubMed Central  Google Scholar 

  15. 15.

    Schmidt MI, Duncan BB, Reichelt AJ, Branchtein L, Matos MC, e Forti AC, Spichler ER, Pousada JM, Teixeira MM, Yamashita T (2001) Gestational diabetes mellitus diagnosed with a 2-h 75-g oral glucose tolerance test and adverse pregnancy outcomes. Diabet Care 24:1151–1155

    CAS  Article  Google Scholar 

  16. 16.

    Casey BM, Lucas MJ, McIntire DD, Leveno KJ (1997) Pregnancy outcomes in women with gestational diabetes compared with the general obstetric population. Obstet Gynecol 90:869–873

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  17. 17.

    Bellamy L, Casas J-P, Hingorani AD, Williams D (2009) Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet 373:1773–1779

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  18. 18.

    Cunningham F, Leveno K, Bloom S, Spong CY, Dashe J (2014) Williams obstetrics. Mcgraw-hill, New York

    Google Scholar 

  19. 19.

    Grady R, Alavi N, Vale R, Khandwala M, McDonald SD (2012) Elective single embryo transfer and perinatal outcomes: a systematic review and meta-analysis. Fertil Steril 97:324–331

    PubMed  Article  PubMed Central  Google Scholar 

  20. 20.

    Zaib-un-Nisa S, Ghazal-Aswad S, Badrinath P (2003) Outcome of twin pregnancies after assisted reproductive techniques—a comparative study. Eur J Obstet Gynecol Reprod Biol 109:51–54

    PubMed  Article  PubMed Central  Google Scholar 

  21. 21.

    Saygan-Karamürsel B, Tekşam Ö, Aksu T, Yurdakök M, Önderoğlu L (2006) Perinatal outcomes of spontaneous twins compared with twins conceived through intracytoplasmic sperm injection. J Perinat Med 34:132–138

    PubMed  Article  PubMed Central  Google Scholar 

  22. 22.

    Adler-Levy Y, Lunenfeld E, Levy A (2007) Obstetric outcome of twin pregnancies conceived by in vitro fertilization and ovulation induction compared with those conceived spontaneously. Eur J Obstet Gynecol Reprod Biol 133:173–178

    PubMed  Article  PubMed Central  Google Scholar 

  23. 23.

    Kennelly M, McAuliffe F (2016) Prediction and prevention of Gestational Diabetes: an update of recent literature. Eur J Obstet Gynecol Reprod Biol 202:92–98

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  24. 24.

    Marchand E, Poncelet C, Carbillon L, Pharisien I, Tigaizin A, Chanelles O (2011) Is there more complications with pregnancies from the assisted reproductive technology than spontaneous pregnancies? A retrospective study over 6 years. J Gynecol Obstet Biol Reprod (Paris) 40:522–528

    CAS  Article  Google Scholar 

  25. 25.

    Moher D, Liberati A, Tetzlaff J, Altman DG (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 151:264–269

    PubMed  Article  PubMed Central  Google Scholar 

  26. 26.

    Wells GA, Shea B, O’connell D, Peterson J, Welch V, Losos M, Tugwell P. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Available at: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed 30 July 2017.

  27. 27.

    Higgins J, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21:1539–1558

    Google Scholar 

  28. 28.

    Begg CB, Mazumdar M (1994) Operating characteristics of a rank correlation test for publication bias. Biometrics 50:1088–1101

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  29. 29.

    Egger M, Smith GD, Schneider M, Minder C (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ 315:629–634

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  30. 30.

    Varma TR, Patel RH (1987) Outcome of pregnancy following investigation and treatment of infertility. Int J Gynaecol Obstet 25:113–120

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  31. 31.

    Vollenhoven B, Clark S, Kovacs G, Burger H, Healy D (2000) Prevalence of gestational diabetes mellitus in polycystic ovarian syndrome (PCOS) patients pregnant after ovulation induction with gonadotrophins. Aust N Z J Obstet Gynaecol 40:54–58

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  32. 32.

    Bjercke S, Dale PO, Tanbo T, Storeng R, Ertzeid G, Åbyholm T (2002) Impact of insulin resistance on pregnancy complications and outcome in women with polycystic ovary syndrome. Gynecol Obstet Invest 54:94–98

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  33. 33.

    Koivurova S, Hartikainen AL, Karinen L, Gissler M, Hemminki E, Martikainen H, Tuomivaara L, Järvelin MR (2002) The course of pregnancy and delivery and the use of maternal healthcare services after standard IVF in Northern Finland 1990-1995. Hum Reprod 17:2897–2903

    PubMed  Article  PubMed Central  Google Scholar 

  34. 34.

    Nassar AH, Usta IM, Rechdan JB, Harb TS, Adra AM, Abu-Musa AA (2003) Pregnancy outcome in spontaneous twins versus twins who were conceived through in vitro fertilization. Am J Obstet Gynecol 189:513–518

    PubMed  Article  PubMed Central  Google Scholar 

  35. 35.

    Pinborg A, Loft A, Schmidt L, Langhoff-Roos J, Andersen AN (2004) Maternal risks and perinatal outcome in a Danish national cohort of 1005 twin pregnancies: the role of in vitro fertilization. Acta Obstet Gynecol Scand 83:75–84

    PubMed  Article  PubMed Central  Google Scholar 

  36. 36.

    Shevell T, Malone FD, Vidaver J, Porter TF, Luthy DA, Comstock CH, Hankins GD, Eddleman K, Dolan S, Dugoff L (2005) Assisted reproductive technology and pregnancy outcome. Obstet Gynecol 106:1039–1045

    PubMed  Article  PubMed Central  Google Scholar 

  37. 37.

    Buckett WM, Chian RC, Holzer H, Dean N, Usher R, Tan SL (2007) Obstetric outcomes and congenital abnormalities after in vitro maturation, in vitro fertilization, and intracytoplasmic sperm injection. Obstet Gynecol 110:885–891

    PubMed  Article  PubMed Central  Google Scholar 

  38. 38.

    Eskandar M (2007) Outcome of twin ICSI pregnancy compared with spontaneous conceived twin pregnancy: A prospective, controlled, observational study. Middle East Fertil Soc J 12:97–101

    Google Scholar 

  39. 39.

    Krieg SA, Henne MB, Westphal LM (2008) Obstetric outcomes in donor oocyte pregnancies compared with advanced maternal age in in vitro fertilization pregnancies. Fertil Steril 90:65–70

    PubMed  Article  PubMed Central  Google Scholar 

  40. 40.

    Vasario E, Borgarello V, Bossotti C, Libanori E, Biolcati M, Arduino S, Spinelli R, Piane LD, Revelli A, Todros T (2010) IVF twins have similar obstetric and neonatal outcome as spontaneously conceived twins: A prospective follow-up study. Reprod BioMed Online 21:422–428

    PubMed  Article  PubMed Central  Google Scholar 

  41. 41.

    Suzuki S, Miyake H (2010) Perinatal outcomes of elderly primiparous dichorionic twin pregnancies conceived by in vitro fertilization compared with those conceived spontaneously. Arch Gynecol Obstet. 281:87–90

    PubMed  Article  PubMed Central  Google Scholar 

  42. 42.

    Tepper NK, Farr SL, Cohen BB, Nannini A, Zhang Z, Anderson JE, Jamieson DJ, Macaluso M (2012) Singleton preterm birth: risk factors and association with assisted reproductive technology. Matern Child Health J 16:807–813

    PubMed  Article  PubMed Central  Google Scholar 

  43. 43.

    Montoya JB, Muñoz ER, Rivera EC, Villaseñor BL, De La Jara Díaz JF, Canedo TH (2012) Resultados perinatales adversos en mujeres mexicanas con embarazos gemelares por reproducción asistida vs gemelares espontáneos. Ginecol Obstet Mex 80:445–453

    Google Scholar 

  44. 44.

    Moini A, Shiva M, Arabipoor A, Hosseini R, Chehrazi M, Sadeghi M (2012) Obstetric and neonatal outcomes of twin pregnancies conceived by assisted reproductive technology compared with twin pregnancies conceived spontaneously: a prospective follow-up study. Eur J Obstet Gynecol Reprod Biol 165:29–32

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  45. 45.

    Bamberg C, Fotopoulou C, Neissner P, Slowinski T, Dudenhausen JW, Proquitte H, Bührer C, Henrich W (2012) Maternal characteristics and twin gestation outcomes over 10 years: impact of conception methods. Fertil Steril 98:95–101

    PubMed  Article  PubMed Central  Google Scholar 

  46. 46.

    Le Ray C, Scherier S, Anselem O, Marszalek A, Tsatsaris V, Cabrol D, Goffinet F (2012) Association between oocyte donation and maternal and perinatal outcomes in women aged 43 years or older. Hum Reprod 27:896–901

    PubMed  Article  PubMed Central  Google Scholar 

  47. 47.

    Werder E, Mendola P, Männistö T, O’Loughlin J, Laughon SK (2013) Effect of maternal chronic disease on obstetric complications in twin pregnancies in a United States cohort. Fertil Steril 100:142–149

    PubMed  PubMed Central  Article  Google Scholar 

  48. 48.

    Wang Y, Nikravan R, Smith H, Sullivan E (2013) Higher prevalence of gestational diabetes mellitus following assisted reproductive technology treatment. Hum Reprod 28:2554–2561

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  49. 49.

    Farhi A, Reichman B, Boyko V, Hourvitz A, Ron-El R, Lerner-Geva L (2013) Maternal and neonatal health outcomes following assisted reproduction. Reprod. BioMed. Online 26:454–461

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  50. 50.

    Toshimitsu M, Nagamatsu T, Nagasaka T, Iwasawa-Kawai Y, Komatsu A, Yamashita T, Osuga Y, Fujii T (2014) Increased risk of pregnancy-induced hypertension and operative delivery after conception induced by in vitro fertilization/intracytoplasmic sperm injection in women aged 40 years and older. Fertil Steril 102:1065–1070

    PubMed  Article  PubMed Central  Google Scholar 

  51. 51.

    Caserta D, Bordi G, Stegagno M, Filippini F, Podagrosi M, Roselli D, Moscarini M (2014) Maternal and perinatal outcomes in spontaneous versus assisted conception twin pregnancies. Eur J Obstet Gynecol Reprod Biol 174:64–69

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  52. 52.

    Ashrafi M, Gosili R, Hosseini R, Arabipoor A, Ahmadi J, Chehrazi M (2014) Risk of gestational diabetes mellitus in patients undergoing assisted reproductive techniques. Eur J Obstet Gynecol Reprod Biol 176:149–152

    CAS  Article  Google Scholar 

  53. 53.

    Ashrafi M, Sheikhan F, Arabipoor A, Hosseini R, Nourbakhsh F, Zolfaghari Z (2014) Gestational diabetes mellitus risk factors in women with polycystic ovary syndrome (PCOS). Eur J Obstet Gynecol Reprod Biol 181:195–199

    PubMed  Article  PubMed Central  Google Scholar 

  54. 54.

    Silberstein T, Levy A, Harlev A, Saphier O, Sheiner E (2014) Perinatal outcome of pregnancies following in vitro fertilization and ovulation induction. J Matern Fetal Neonatal Med 27:1316–1319

    PubMed  Article  PubMed Central  Google Scholar 

  55. 55.

    Yang X, Li Y, Li C, Zhang W (2014) Current overview of pregnancy complications and live-birth outcome of assisted reproductive technology in mainland China. Fertil Steril 101:385–391

    PubMed  Article  PubMed Central  Google Scholar 

  56. 56.

    Domingues AP, Dinis SR, Belo A, Couto D, Fonseca E, Moura P (2014) Impact of induced pregnancies in the obstetrical outcome of twin pregnancies. Fertil Steril 101:172–177

    PubMed  Article  PubMed Central  Google Scholar 

  57. 57.

    Stern JE, Luke B, Tobias M, Gopal D, Hornstein MD, Diop H (2015) Adverse pregnancy and birth outcomes associated with underlying diagnosis with and without assisted reproductive technology treatment. Fertil Steril 103:1438–1445

    PubMed  PubMed Central  Article  Google Scholar 

  58. 58.

    Jie Z, Yiling D, Ling Y (2015) Association of assisted reproductive technology with adverse pregnancy outcomes. Iran J Reprod Med 13:169–180

    PubMed  PubMed Central  Google Scholar 

  59. 59.

    Nunes F, Noronha N, Neves F, Taborda A, Silva IS, Almeida M (2015) Obstetric And Perinatal Outcomes In Multifetal Gestations: Assisted Reproductive Technology Versus Spontaneous Conception. J Perinat Med 43:1208

    Google Scholar 

  60. 60.

    Barua S, Hng TM, Smith H, Bradford J, McLean M (2017) Ovulatory disorders are an independent risk factor for pregnancy complications in women receiving assisted reproduction treatments. Aust N Z J Obstet Gynaecol 57:286–293

    PubMed  Article  PubMed Central  Google Scholar 

  61. 61.

    Zhu LL, Zhang Y, Liu YF, Zhang RJ, Wu YQ, Huang Y, Liu F, Li MG, Sun SJ, Xing LF et al (2016) Maternal and Live-birth Outcomes of Pregnancies following Assisted Reproductive Technology: A Retrospective Cohort Study. Sci Rep:6

  62. 62.

    Martin AS, Monsour M, Kissin DM, Jamieson DJ, Callaghan WM, Boulet SL (2016) Trends in severe maternal morbidity after assisted reproductive technology in the United States, 2008-2012. Obstet Gynecol 127:59–66

    PubMed  Article  PubMed Central  Google Scholar 

  63. 63.

    Luke B, Stern JE, Kotelchuck M, Declercq ER, Anderka M, Diop H (2016) Birth outcomes by infertility treatment: Analyses of the population-based cohort: Massachusetts outcomes study of assisted reproductive technologies (MOSART). J Reprod Med 61:114–127

    PubMed  PubMed Central  Google Scholar 

  64. 64.

    Bashmakova NV, Davydenko NB, Malgina GB, Putilova NV (2016) Epidemiology of critical states during pregnancy after assisted reproductive technologies. Gynecol Endocrinol 32:47–51

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  65. 65.

    Rosato E, Perrone G, Capri O, Galoppi P, Candelieri M, Marcoccia E, Schiavi MC, Zannini I, Brunelli R (2016) Hypertension and early menopause after the use of assisted reproductive technologies in women aged 43 years or older: Long-term follow-up study. J Obstet Gynaecol Res 42:1782–1788

    PubMed  Article  PubMed Central  Google Scholar 

  66. 66.

    Valenzuela-Alcaraz B, Crispi F, Manau D, Cruz-Lemini M, Borras A, Balasch J, Gratacos E (2016) Differential effect of mode of conception and infertility treatment on fetal growth and prematurity. J Matern Fetal Neonatal Med 29:3879–3884

    PubMed  Article  PubMed Central  Google Scholar 

  67. 67.

    Marton V, Zadori J, Kozinszky Z, Kereszturi A (2016) Prevalences and pregnancy outcome of vanishing twin pregnancies achieved by in vitro fertilization versus natural conception. Fertil Steril 106:1399–1406

    PubMed  Article  PubMed Central  Google Scholar 

  68. 68.

    Beyer DA, Amari F (2016) Maternal risk factors and neonatal outcomes after ART treatment – A German monocenter experience. Middle East Fertil Soc J 21:155–160

    Article  Google Scholar 

  69. 69.

    Pourali L, Ayati S, Jelodar S, Zarifian A, Andalibi MSS (2016) Obstetrics and perinatal outcomes of dichorionic twin pregnancy following art compared with spontaneous pregnancy. Int J Reprod Biomed (Yazd) 14:317–322

    Google Scholar 

  70. 70.

    Ben-Yaakov RD, Kessous R, Shoham-Vardi I, Sergienko R, Pariente G, Sheiner E (2016) Fertility treatments in women who become pregnant and carried to viability, and the risk for long-term maternal cardiovascular morbidity. Am J Perinatol 33:1388–1393

    PubMed  Article  PubMed Central  Google Scholar 

  71. 71.

    Qin J, Liu X, Sheng X, Wang H, Gao S (2016) Assisted reproductive technology and the risk of pregnancy-related complications and adverse pregnancy outcomes in singleton pregnancies: A meta-analysis of cohort studies. Fertil Steril 105:73–85e76

    PubMed  Article  PubMed Central  Google Scholar 

  72. 72.

    Wang YPA, Chughtai AA, Farquhar CM, Pollock W, Lui K, Sullivan EA (2016) Increased incidence of gestational hypertension and preeclampsia after assisted reproductive technology treatment. Fertil Steril 105:920–926

    PubMed  Article  PubMed Central  Google Scholar 

  73. 73.

    Korosec S, Frangez HB, Steblovnik L, Verdenik I, Bokal EV (2016) Independent factors influencing large-for-gestation birth weight in singletons born after in vitro fertilization. J Assist Reprod Genet 33:9–17

    PubMed  Article  PubMed Central  Google Scholar 

  74. 74.

    Morency AM, Shah PS, Seaward PG, Whittle W, Murphy KE (2016) Obstetrical and neonatal outcomes of triplet births - spontaneous versus assisted reproductive technology conception. J Matern Fetal Neonatal Med 29:938–943

    PubMed  Article  PubMed Central  Google Scholar 

  75. 75.

    Luke B, Gopal D, Cabral H, Stern JE, Diop H (2017) Adverse pregnancy, birth, and infant outcomes in twins: effects of maternal fertility status and infant gender combinations; the Massachusetts Outcomes Study of Assisted Reproductive Technology. Am J Obstet Gynecol 217:330.e331–330.e315

    Article  Google Scholar 

  76. 76.

    Zegers-Hochschild F, Adamson GD, de Mouzon J, Ishihara O, Mansour R, Nygren K, Sullivan E, Van der Poel S (2009) The international committee for monitoring assisted reproductive technology (ICMART) and the world health organization (WHO) revised glossary on ART terminology, 2009. Hum Reprod 24:2683–2687

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  77. 77.

    Adamson GD, de Mouzon J, Lancaster P, Nygren K-G, Sullivan E, Zegers-Hochschild F, Technology, I.C.f.M.A.R (2006) World collaborative report on in vitro fertilization, 2000. Fertil Steril 85:1586–1622

    PubMed  Article  PubMed Central  Google Scholar 

  78. 78.

    Dickey RP (2007) The relative contribution of assisted reproductive technologies and ovulation induction to multiple births in the United States 5 years after the Society for Assisted Reproductive Technology/American Society for Reproductive Medicine recommendation to limit the number of embryos transferred. Fertil Steril 88:1554–1561

    PubMed  Article  PubMed Central  Google Scholar 

  79. 79.

    Stephansson O, Kieler H, Granath F, Falconer H (2009) Endometriosis, assisted reproduction technology, and risk of adverse pregnancy outcome. Hum Reprod 24:2341–2347

    PubMed  Article  PubMed Central  Google Scholar 

  80. 80.

    Qin J, Liu X, Sheng X, Wang H, Gao S (2016) Assisted reproductive technology and the risk of pregnancy-related complications and adverse pregnancy outcomes in singleton pregnancies: a meta-analysis of cohort studies. Fertil Steril 105:73–85

    PubMed  Article  PubMed Central  Google Scholar 

  81. 81.

    Qin J, Wang H, Sheng X, Liang D, Tan H, Xia J (2015) Pregnancy-related complications and adverse pregnancy outcomes in multiple pregnancies resulting from assisted reproductive technology: a meta-analysis of cohort studies. Fertil Steril 103:1492–1508

    PubMed  Article  PubMed Central  Google Scholar 

  82. 82.

    Kouhkan A, Khamseh ME, Pirjani R, Moini A, Arabipoor A, Maroufizadeh S, Hosseini R, Baradaran HR (2018) Obstetric and perinatal outcomes of singleton pregnancies conceived via assisted reproductive technology complicated by gestational diabetes mellitus: a prospective cohort study. BMC Pregnancy Childbirth 18:495

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  83. 83.

    Almasi-Hashiani A, Omani-Samani R, Mohammadi M, Amini P, Navid B, Alizadeh A, Morasae EK, Maroufizadeh S (2019) Assisted reproductive technology and the risk of preeclampsia: an updated systematic review and meta-analysis. BMC Pregnancy Childbirth 19:149

    PubMed  PubMed Central  Article  Google Scholar 

  84. 84.

    Association, A.D (2014) Diagnosis and classification of diabetes mellitus. Diabetes Care 37:S81–S90

    Article  Google Scholar 

  85. 85.

    DeSisto CL, Kim SY, Sharma AJ (2014) Prevalence estimates of gestational diabetes mellitus in the United States, pregnancy risk assessment monitoring system (PRAMS), 2007–2010. Prev Chronic Dis 11:E104

    PubMed  PubMed Central  Article  Google Scholar 

  86. 86.

    Leng J, Shao P, Zhang C, Tian H, Zhang F, Zhang S, Dong L, Li L, Yu Z, Chan JC (2015) Prevalence of gestational diabetes mellitus and its risk factors in Chinese pregnant women: a prospective population-based study in Tianjin, China. PloS one 10:e0121029

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  87. 87.

    Kjerulff LE, Sanchez-Ramos L, Duffy D (2011) Pregnancy outcomes in women with polycystic ovary syndrome: a metaanalysis. Am J Obstet Gynecol 204(558):e551–e556

    Google Scholar 

  88. 88.

    Bener A, Saleh NM, Al-Hamaq A (2011) Prevalence of gestational diabetes and associated maternal and neonatal complications in a fast-developing community: global comparisons. Int J Womens Health 3:367–373

    PubMed  PubMed Central  Article  Google Scholar 

  89. 89.

    Pinborg A, Lidegaard Ø, la Cour Freiesleben N, Andersen AN (2007) Vanishing twins: a predictor of small-for-gestational age in IVF singletons. Hum Reprod 22:2707–2714

    PubMed  Article  PubMed Central  Google Scholar 

  90. 90.

    Sibai BM, Ross MG (2010) Hypertension in gestational diabetes mellitus: pathophysiology and long-term consequences. J Matern Fetal Neonatal Med 23:229–233

    PubMed  Article  PubMed Central  Google Scholar 

  91. 91.

    Vitthala S, Gelbaya T, Brison D, Fitzgerald C, Nardo L (2008) The risk of monozygotic twins after assisted reproductive technology: a systematic review and meta-analysis. Hum Reprod Update 15:45–55

    PubMed  Article  PubMed Central  Google Scholar 

  92. 92.

    Hammoud NM, de Valk HW, Biesma DH, Visser GH (2013) Gestational diabetes mellitus diagnosed by screening or symptoms: does it matter? J Matern Fetal Neonatal Med 26:103–105

    PubMed  Article  PubMed Central  Google Scholar 

  93. 93.

    Sazonova A, Källen K, Thurin-Kjellberg A, Wennerholm U-B, Bergh C (2012) Obstetric outcome in singletons after in vitro fertilization with cryopreserved/thawed embryos. Hum Reprod 27:1343–1350

    PubMed  Article  PubMed Central  Google Scholar 

  94. 94.

    Luke B, Brown MB (2007) Elevated risks of pregnancy complications and adverse outcomes with increasing maternal age. Hum Reprod 22:1264–1272

    PubMed  Article  PubMed Central  Google Scholar 

  95. 95.

    Toulis KA, Goulis DG, Kolibianakis EM, Venetis CA, Tarlatzis BC, Papadimas I (2009) Risk of gestational diabetes mellitus in women with polycystic ovary syndrome: a systematic review and a meta-analysis. Fertil Steril 92:667–677

    PubMed  Article  PubMed Central  Google Scholar 

  96. 96.

    Higgins, J.P. and Green, S. (2011) Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0. The Cochrane Collaboration, 2011. Available from www.cochrane-handbook.org.

Download references

Acknowledgments

Not applicable.

Funding

Th is work received no specific grant from any agency in the public, commercial or not for profit sector.

Author information

Affiliations

Authors

Contributions

AA, MM, ROS, SM, and AAH conceived the study. MM, PA, BN, SM, EKM, and AA collected the data. AAH and SM analyzed the data. All authors contributed equally to draft the manuscript. All authors revised the manuscript and approved the final version.

Corresponding authors

Correspondence to Saman Maroufizadeh or Ahad Alizadeh.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mohammadi, M., Khedmati Morasae, E., Maroufizadeh, S. et al. Assisted reproductive technology and the risk of gestational diabetes mellitus: a systematic review and meta-analysis. Middle East Fertil Soc J 25, 6 (2020). https://doi.org/10.1186/s43043-020-0018-6

Download citation

Keywords

  • Assisted reproductive technology
  • Gestational diabetes mellitus
  • Infertility
  • Meta-analysis
  • Systematic review