Probiotics for preventing gestational diabetes

  • Review
  • Intervention

Authors

  • Helen L Barrett,

    Corresponding author
    1. Royal Brisbane and Women's Hospital, Internal Medicine, Herston, Queensland, Australia
    2. The University of Queensland, School of Medicine, Herston, Australia
    3. The University of Queensland, The UQ Centre for Clinical Research, Herston, Australia
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  • Marloes Dekker Nitert,

    1. The University of Queensland, School of Medicine, Herston, Australia
    2. The University of Queensland, The UQ Centre for Clinical Research, Herston, Australia
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  • Louise S Conwell,

    1. Royal Children's Hospital, Endocrinology and Diabetes, Brisbane, Queensland, Australia
    2. School of Medicine, Queensland Children's Medical Research Institute, Herston, Queensland, Australia
    3. University of Queensland, School of Medicine and Queensland Children's Medical Research Institute, Herston, Queensland, Australia
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  • Leonie K Callaway

    1. Royal Brisbane and Women's Hospital, Internal Medicine, Herston, Queensland, Australia
    2. The University of Queensland, School of Medicine, Herston, Australia
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Abstract

Background

Gestational diabetes mellitus (GDM) is associated with a range of adverse pregnancy outcomes for mother and infant. The prevention of GDM using lifestyle interventions has proven difficult. The gut microbiome (the composite of bacteria present in the intestines) influences host inflammatory pathways, glucose and lipid metabolism and, in other settings, alteration of the gut microbiome has been shown to impact on these host responses. Probiotics are one way of altering the gut microbiome but little is known about their use in influencing the metabolic environment of pregnancy.

Objectives

To assess the effects of probiotic supplementation when compared with other methods for the prevention of GDM.

Search methods

We searched the Cochrane Pregnancy and childbirth Group's Trials Register (31 August 2013) and reference lists of the articles of retrieved studies.

Selection criteria

Randomised and cluster-randomised trials comparing the use of probiotic supplementation with other methods for the prevention of the development of GDM. Cluster-randomised trials were eligible for inclusion but none were identified. Quasi-randomised and cross-over design studies are not eligible for inclusion in this review. Studies presented only as abstracts with no subsequent full report of study results would also have been excluded.

Data collection and analysis

Two review authors independently assessed study eligibility, extracted data and assessed risk of bias of included study. Data were checked for accuracy.

Main results

Eleven reports (relating to five possible trials) were found. We included one study (six trial reports) involving 256 women. Four other studies are ongoing.

The included trial consisted of three treatment arms: probiotic with dietary intervention, placebo and dietary intervention, and dietary intervention alone; it was at a low risk of bias. The study reported primary outcomes of a reduction in the rate of gestational diabetes mellitus (risk ratio (RR) 0.38, 95% confidence interval (CI) 0.20 to 0.70), with no statistical difference in the rates of miscarriage/intrauterine fetal death (IUFD)/stillbirth/neonatal death (RR 2.00, 95% CI 0.35 to 11.35). Secondary outcomes reported were a reduction in infant birthweight (mean difference (MD) -127.71 g, 95% CI -251.37 to -4.06) in the probiotic group and no clear evidence of increased risk of preterm delivery (RR 3.27, 95% CI 0.44 to 24.43), or caesarean section rate (RR 1.23, 95% CI 0.65 to 2.32). The primary infant outcomes of rates of macrosomia and large-for-gestational age infants were not reported. The following secondary outcomes were not reported: maternal gestational weight gain, pre-eclampsia, and the long-term diagnosis of diabetes mellitus; infant body composition, shoulder dystocia, admission to neonatal intensive care, jaundice, hypoglycaemia and long-term rates of obesity and diabetes mellitus.

Authors' conclusions

One trial has shown a reduction in the rate of GDM when women are randomised to probiotics early in pregnancy but more uncertain evidence of any effect on miscarriage/IUFD/stillbirth/neonatal death. There are no data on macrosomia. At this time, there are insufficient studies to perform a quantitative meta-analysis. Further results are awaited from four ongoing studies.

Résumé scientifique

Probiotiques pour la prévention du diabète gestationnel

Contexte

Le diabète gestationnel (DG) est associé à un éventail de conséquences néfastes sur la grossesse pour la mère et le nourrisson. La prévention du DG à l'aide d'interventions axées sur le mode de vie s'est avérée difficile. Le microbiome intestinal (composite de bactéries présentes dans l'intestin) influence les chemins inflammatoires de l'hôte, le métabolisme du glucose et des lipides et, dans d'autres environnements, il a été démontré que l'altération du microbiome intestinal avait eu un impact sur ces réponses de l'hôte. Les probiotiques sont une façon d'altérer le microbiome intestinal mais nous savons peu de choses sur leur utilisation pour influencer l'environnement métabolique de la grossesse.

Objectifs

Évaluer les effets de la supplémentation en probiotiques par rapport à d'autres méthodes pour la prévention du DG.

Stratégie de recherche documentaire

Nous avons effectué des recherches dans le registre des essais du groupe Cochrane sur la grossesse et l'accouchement (le 31 août 2013) et dans les références bibliographiques d'articles des études trouvées.

Critères de sélection

Essais randomisés et randomisés en grappes comparant l'utilisation de la supplémentation en probiotiques avec d'autres méthodes pour la prévention du développement de DG. Les essais randomisés en grappes étaient éligibles pour inclusion, mais aucun n'a été identifié. Les essais quasi randomisés et croisés n'étaient pas éligibles pour inclusion dans cette revue. Les études présentées uniquement sous forme de résumé sans rapport complet ultérieur sur les résultats auraient également été exclues.

Recueil et analyse des données

Deux auteurs de la revue ont indépendamment évalué l'éligibilité des études, extrait les données et évalué le risque de biais des études incluses. L'exactitude des données a été vérifiée.

Résultats principaux

Onze rapports (sur cinq essais potentiels) ont été trouvés. Nous avons inclus une étude (six rapports d'essai) portant sur 256 femmes. Quatre autres études sont en cours.

L'essai inclus était composé de trois bras de traitement : probiotiques avec intervention diététique, placebo avec intervention diététique et intervention diététique seule ; elle présentait un faible risque de biais. L'étude a rapporté en critères de jugement principaux une réduction du taux de diabète gestationnel (risque relatif (RR) 0,38, intervalle de confiance (IC) à 95 % de 0,20 à 0,70), sans aucune différence statistique dans les taux de fausse couche/mort fœtale intra-utérine (MFIU)/mortinaissance/mortalité néonatale (RR 2,00, IC à 95 % 0,35 à 11,35). Les critères de jugement secondaires rapportés étaient une réduction dans le poids de naissance du bébé (différence moyenne (DM) -127,71 g, IC à 95 % -251,37 à -4,06) dans le groupe avec probiotiques et aucune preuve d'un risque accru d'accouchement prématuré (RR 3,27, IC à 95 % 0,44 à 24,43), ou le taux de césarienne (RR 1,23, IC à 95 % 0,65 à 2,32). Les critères de jugement principaux relatifs à l'enfant des taux de macrosomie et de nourrissons de grande taille pour l'âge gestationnel n'étaient pas rapportés. Les critères de jugement secondaires suivants n'étaient pas rapportés : prise de poids gestationnelle, pré-éclampsie et diagnostic du diabète à long terme chez la mère ; composition corporelle, dystocie des épaules, admission en unités néonatales de soins intensifs, ictère, hypoglycémie et taux d'obésité et de diabète à long terme chez l'enfant.

Conclusions des auteurs

Un essai a montré une réduction du taux de DG lorsque les femmes étaient randomisées aux probiotiques en début de grossesse, mais les preuves d'un quelconque effet sur les taux de fausse couche/MFIU/mortinaissance/décès néonatal sont plus incertaines. Aucune donnée n'est disponible sur la macrosomie. À ce jour, il n'existe pas suffisamment d'études pour réaliser une méta-analyse quantitative. D'autres résultats sont attendus de quatre études en cours.

アブストラクト

妊娠糖尿病予防のためのプロバイオティクス

背景

妊娠糖尿病(GDM)は母子におけるさまざまな有害妊娠アウトカムに関連している。生活習慣への介入によるGDM予防は、難しいとことがわかっている。消化管内マイクロバイオーム(腸管に存在するバクテリアの複合体)は、宿主の炎症性経路、グルコースと脂質代謝に影響を与える。そして他の状況においては、消化管内マイクロバイオームが変化してこれらの宿主応答に影響を与えることが示されている。プロバイオティクスは消化管内マイクロバイオームを変化させる1つの方法であるが、妊娠の代謝環境に影響を与えるという利用法についてはほとんどわかっていない。

目的

GDM予防のための他の方法と比較した場合のプロバイオティクス補充療法の効果を評価すること。

検索戦略

Cochrane Pregnancy and childbirth Group’s Trials Register (2013年8月31日)と検索した研究論文の参考文献を調べた。

選択基準

GDM発症予防に対し、プロバイオティクス補充療法を他の方法と比較したランダム化試験およびクラスターランダム化試験。クラスターランダム化試験は、選択対象として適格ではあったが、同定されなかった。準ランダム化試験とクロスオーバーデザイン試験は、本レビューにおいては選択対象として適格ではない。単に抄録として発表され、研究結果に関するその後の十分な報告のない研究も同じく除外された。

データ収集と分析

2名のレビュー著者が独立して研究の適格性を評価し、データを抽出し、研究のバイアスのリスクを評価した。データの精度を確認した。

主な結果

11の報告(5つの対象試験に関連)が確認された。256例の女性を含む1つの試験(6つの試験報告)を含めた。他の4つの試験は進行中である。

対象となった試験は以下の3治療群からなる:食事療法の介入によるプロバイオティクス群、プラセボ+食事療法の介入群、および食事療法の介入単独群。この試験はバイアスのリスクが低かった。この研究では、主要アウトカムとして妊娠糖尿病の割合の低下(リスク比(RR)0.38,95%信頼区間(CI)0.20〜0.70)が報告され、流産/子宮内胎児死亡(IUFD)/死産/新生児死亡(RR2.00、95%CI 0.35〜11.35)における統計学的な有意差は確認されなかった。報告された副次的評価項目は、プロバイオティクス群における出生児体重の減少(平均差(MD)-127.71g、95%CI -251.3〜-4.06)であった。そして早産のリスクの増大(RR 3.27、95% CI 0.44〜 24.43)、または帝王切開率(RR 1.23, 95% CI 0.65〜2.32)についての明確なエビデンスは確認されていない。巨大児および身長、体重ともに90パーセンタイル以上の新生児の割合である主要乳児アウトカムは報告されていない。以下のような副次的評価項目は報告されなかった:妊婦体重増加、子癇前症、および糖尿病の長期にわたる診断;出生児の体組成、肩甲難産、新生児集中治療室への入院、黄疸、低血糖および肥満と糖尿病の長期にわたる診断。

著者の結論

1つの試験では、女性を妊娠早期プロバイオティクスにランダム化した場合、GDMの割合の低下が認められたが、流産/IUFD/死産/新生児死亡に対するいかなる効果もそのエビデンスは不確かであった。巨大児についてのデータはない。この時点で、定量的メタアナリシスを実施するのに十分な数の研究が存在しない。進行中の4つの研究から、追加の結果が待たれる。

訳注


《実施組織》厚生労働省「「統合医療」に係る情報発信等推進事業」(eJIM:http://www.ejim.ncgg.go.jp/)[2016.1.9]《注意》この日本語訳は、臨床医、疫学研究者などによる翻訳のチェックを受けて公開していますが、訳語の間違いなどお気づきの点がございましたら、eJIM事務局までご連絡ください。なお、2013年6月からコクラン・ライブラリーのNew review, Updated reviewとも日単位で更新されています。eJIMでは最新版の日本語訳を掲載するよう努めておりますが、タイム・ラグが生じている場合もあります。ご利用に際しては、最新版(英語版)の内容をご確認ください。

Plain language summary

Probiotics to prevent gestational diabetes mellitus

Gestational diabetes mellitus is a condition where the mother has high blood sugar levels during pregnancy. It is associated with a range of adverse pregnancy outcomes for the mother, such as pre-eclampsia (high blood pressure with protein in the urine) and instrumental or operative delivery, as well as for the infants who may be born large-for-gestational age. Current treatment includes diet with or without medication. Prevention of this condition would be preferable to treatment. Preventative diet and lifestyle interventions are time consuming and do not always reduce the number of women getting gestational diabetes. Probiotics - 'good' bacteria that are usually taken in the form of capsules or drinks - supplement the gut bacteria. They have the potential to change a person's metabolism and so prevent gestational diabetes mellitus. This review was designed to look at whether there is evidence to show if this is true or not. At the moment there is only one randomised controlled study, which involved 256 women. This study does show a lower rate of gestational diabetes mellitus in women who took probiotics from early pregnancy, with the rate of diagnosis of gestational diabetes mellitus being reduced by two-thirds and their babies on average weighed 127 g less at birth. This study did not find differences in the rates of miscarriage, intrauterine or neonatal death or stillbirth. There was no clear evidence of a change in the proportion of women delivered by caesarean section or in the risk of preterm delivery. The study did not report on how much weight the mothers gained during pregnancy or how many babies were large-for-gestational age or that weighed more than 4000 g at birth or on the body composition of the babies. One study is not enough to draw any definite conclusions at the moment. There are other studies underway.

Résumé simplifié

Les probiotiques pour prévenir le diabète de grossesse

Le diabète gestationnel est une maladie dans laquelle la mère a des taux de glycémie élevés pendant la grossesse. Il est associé à un éventail de conséquences néfastes sur la grossesse pour la mère, tels que la pré-éclampsie (pression artérielle élevée avec des protéines dans les urines) et l'accouchement avec assistance instrumentale ou opératoire, ainsi que pour l'enfant qui peut naître avec une grande taille pour l'âge gestationnel. Le traitement actuel inclut un régime alimentaire avec ou sans traitement médicamenteux. La prévention de cette maladie serait préférable au traitement. Les interventions préventives portant sur le régime alimentaire et le mode de vie sont longues et ne réduisent pas toujours le nombre de femmes contractant le diabète gestationnel. Les probiotiques - de « bonnes » bactéries qui sont habituellement prises sous forme de capsules ou de boissons - complètent les bactéries intestinales. Ils ont le potentiel de changer le métabolisme d'une personne et donc de prévenir le diabète gestationnel. Cette revue a été conçue pour examiner s'il existe des preuves pour montrer si cela est vrai ou non. À l'heure actuelle, il n'existe qu'une seule étude contrôlée randomisée, qui portait sur 256 femmes. Cette étude a montré un taux plus faible de diabète gestationnel chez les femmes ayant pris des probiotiques dès le début de la grossesse ; le taux de diagnostic de diabète gestationnel était réduit de deux tiers et leurs bébés pesaient en moyenne 127 g de moins à la naissance. Cette étude n'a pas trouvé de différences dans les taux de fausses couches, de décès intra-utérins et néonataux ou de mortinatalité. Il n'y avait aucune preuve claire d'un changement dans la proportion de femmes ayant accouché par césarienne ou dans le risque d'accouchement prématuré. L'étude ne rendait pas compte de la prise de poids des mères pendant la grossesse ou du nombre de bébés de grande taille pour l'âge gestationnel ou pesant plus de 4 000 g à la naissance, ni de la composition corporelle des bébés. Une étude n'est pas suffisante pour pouvoir tirer des conclusions définitives pour le moment. D'autres études sont en cours.

Notes de traduction

Traduit par: French Cochrane Centre 15th June, 2014
Traduction financée par: Financeurs pour le Canada : Instituts de Recherche en Santé du Canada, Ministère de la Santé et des Services Sociaux du Québec, Fonds de recherche du Québec-Santé et Institut National d'Excellence en Santé et en Services Sociaux; pour la France : Ministère en charge de la Santé

Laički sažetak

Probiotici za sprječavanje dijabetesa u trudnoći (gestacijskog dijabetes melitusa)

Gestacijski dijabetes melitus je stanje povišenog krvnog šećera u trudnice. To je povezano s mnogim nepovoljnim ishodima trudnoće za majku, primjerice pre-eklampsija (povišeni krvni tlak i bjelančevine u mokraći) i carski rez odnosno porod uz pomagala, ali i za dijete koje može biti veće za gestacijsku dob. Trenutačne preporuke uključuju dijetu sa ili bez lijekova. Sprječavanje nastanka tog stanja bilo bi bolje od liječenja. Dijeta i promjene životnih navika zahtijevaju mnogo vremena i nisu uvijek učinkovite u sprječavanju nastanka gestacijskog dijabetesa. Probiotici su pripravci "korisnih" bakterija u obliku napitka ili kapsula te obogaćuju crijevne bakterije. To može imati učinka na metabolizam i tako spriječiti gestacijski dijabetes mellitus. Ovaj Cochrane sustavni pregled je istražio dokaze o učinkovitosti tih pripravaka. Nađena je samo jedna randomizirana kontrolirana studija koja je uključila 256 žena. U žena koje su uzimale probiotike već na početku trudnoće je bila manja učestalost gestacijskog dijabetes mellitusa za dvije trećine, a njihova djeca su bila za 127 g lakša u doba porođaja. Nisu nađene razlike između pojavnosti pobačaja, intrauterine ili novorođenačke smrtnosti ili mrtvorođene djece. Nije bilo jasnog dokaza za razliku u pojavnosti potrebe za carskim rezom ili događaja preranog poroda. U studiji nije naveden prirast tjelesne težine majki i broj novorođenčadi koja su bila velika za gestacijsku dob ili koja su bila teža od 4000 g odn. podaci o sastavu tijela djece. Jedna studija nije dostatna za pouzdane zaključke. U tijeku su druge studije pa će prilikom sljedećeg obnavljanja ovog sustavnog pregleda vjerojatno biti moguće uključiti nove dokaze ako se te studije u međuvremenu završe.

Bilješke prijevoda

Hrvatski Cochrane
Prevela: Vesna Kušec
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平易な要約

妊娠糖尿病を予防することを目的としたプロバイオティクス

妊娠糖尿病とは、妊娠中の母親の血糖値が高い疾患である。それは、子癇前症(尿蛋白を伴う高血圧)、器具や手術による分娩のような、母親ならびに不当重量児として産まれた新生児にとってのさまざまな有害妊娠アウトカムに関連する。本治療には、投薬の有無にかかわらず食事療法が含まれる。この疾患の予防は、治療より好ましいであろう。食事療法と生活習慣に関する予防的介入は、時間がかかり、必ずしも妊娠糖尿病になる女性の数を減らすわけではない。通常カプセルや飲料の形で摂取する「善玉」バクテリアであるプロバイオティクスは、消化管内バクテリアを補充する。プロバイオティクスは、人の代謝を変え、妊娠糖尿病を予防する可能性がある。本レビューは、これが事実か否かを示すエビデンスが存在するかどうか確かめるためにデザインされた。現時点で、256例の女性を含めた1つのランダム化比較試験が報告されているのみである。本研究では、プロバイオティクスを妊娠初期から実施した女性の妊娠糖尿病の割合が低下することが示されている。妊娠糖尿病の診断率が2/3低下し、そして出生児の出生時平均体重が127g減少している。本研究では、流産、子宮内胎児死亡、新生児死亡または死産の割合に有意差は認められなかった。帝王切開により分娩した女性の割合の変化や早産の危険性の変化についての明確なエビデンスは得られなかった。この研究では、妊娠中の母親の体重増加量、不当体重児数または出生時体重が4000gを超える出生児数、または出生児の体組成について報告されなかった。1つの研究だけでは、現時点で明確な結論を導き出すには不十分である。進行中の他の研究が存在する。

訳注


《実施組織》厚生労働省「「統合医療」に係る情報発信等推進事業」(eJIM:http://www.ejim.ncgg.go.jp/)[2016.1.9]《注意》この日本語訳は、臨床医、疫学研究者などによる翻訳のチェックを受けて公開していますが、訳語の間違いなどお気づきの点がございましたら、eJIM事務局までご連絡ください。なお、2013年6月からコクラン・ライブラリーのNew review, Updated reviewとも日単位で更新されています。eJIMでは最新版の日本語訳を掲載するよう努めておりますが、タイム・ラグが生じている場合もあります。ご利用に際しては、最新版(英語版)の内容をご確認ください。

Streszczenie prostym językiem

Probiotyki w zapobieganiu cukrzycy ciążowej

Cukrzyca ciężarnych to choroba charakteryzująca się wysokim poziomem cukru we krwi u kobiet w czasie ciąży. Związane jest to z szeregiem niekorzystnych skutków związanych z ciążą dla matki, takich jak stan przedrzucawkowy (wysokie ciśnienie krwi i białkomocz) oraz poród instrumentalny lub za pomocą cesarskiego cięcia, jak również dla niemowląt, które są duże w stosunku do wieku płodowego. Obecne leczenie obejmuję dietę z lub bez stosowania leków. Profilaktyka w tej chorobie byłaby korzystniejsza niż leczenie. Interwencje profilaktyczne dotyczące diety i stylu życia są czasochłonne i nie zawsze skutkują zmniejszeniem liczby kobiet u których występuje cukrzyca ciążowa. Probiotyki - dobre bakterie, które zazwyczaj przyjmowane są w postaci kapsułek lub napojów - stanowią uzupełnienie bakterii jelitowych. Mają zdolność zmiany metabolizmu organizmu i tym samym mogą zapobiegać cukrzycy ciążowej. Niniejszy przegląd został zaprojektowany, aby sprawdzić czy dane naukowe potwierdzają to czy też nie. Obecnie, istnieje tylko jedno badanie z randomizacją obejmujące 256 kobiet. To badanie wykazało rzadsze występowanie cukrzycy ciążowej u kobiet przyjmujących probiotyki od początku ciąży oraz zmniejszenie o dwie trzecie częstości rozpoznania cukrzycy ciężarnych oraz zmniejszenie masy urodzeniowej dziecka o średnio 127 g. To badanie nie wykazało różnicy w częstości poronień, zgonów wewnątrzmacicznych płodu lub zgonów noworodka lub martwych urodzeń. Nie było jasnych danych naukowych dotyczących zmian w częstości porodów za pomocą cesarskiego cięcia lub ryzyku przedwczesnego porodu. W badaniu nie opisano ile wynosił przyrost masy ciała u kobiet w czasie ciąży lub ile dzieci było zbyt dużych w stosunku do wieku płodowego lub ich masa urodzeniowa wynosiła więcej niż 4000 g lub jaki był skład ciała dzieci. Jedno badanie nie jest wystarczające, aby obecnie sformułować jakiekolwiek wnioski. Inne badania są w trakcie realizacji.

Uwagi do tłumaczenia

Tłumaczenie Magdalena Koperny Redakcja Joanna Zając

Background

Description of the condition

Gestational diabetes mellitus (GDM) is currently defined as carbohydrate intolerance first diagnosed during pregnancy (Hadar 2009). There are a number of different diagnostic criteria world wide (Table 1). Rates of GDM are increasing in the obstetric population of both the developed (ACOG Committee 2005; Moore 2010) and developing world (Hossain 2007; Seshiah 2008), driven by increasing rates of overweight and obesity. Applying the new International Association of the Diabetes and Pregnancy Study Groups (IADPSG) diagnostic criteria, 18% of pregnancies in the United States are affected by GDM (HAPO 2008). India and other developing nations are also seeing an increase with rates varying from ˜ 18% in urban populations to 10% in rural populations (Seshiah 2008).

Table 1. Diagnostic criteria for GDM
  1. # International Association of the Diabetes and Pregnancy Study Groups has separate criteria for diabetes diagnosed during pregnancy (as compared to gestational diabetes) to differentiate cases where diabetes is probably pre-existing and does not resolve postpartum.

    ## Australasian Diabetes in Pregnancy Society

    ### American Diabetes Association

    OGTT: oral glucose tolerance test

    * In New Zealand, the 2-hour post glucose diagnostic cut-off is 9 mmol/L

 IADPSG (ACOG Committee 2005) #ADIPS ## (Hoffman 1998)ADA ### (ADA criteria) 
OGTT (g)7575100 
Fasting (mmol/L)5.115.55.33 
1 Hour (mmol/L)10-10 
2 Hour (mmol/L)8.58 *8.6 
3 Hour (mmol/L)--7.8 

GDM is associated with increased rates of maternal and fetal morbidity and mortality, both during the pregnancy and in the longer term (Davey 2005). Maternal pregnancy complications include pre-eclampsia (a syndrome of hypertension and proteinuria) and instrumental or operative delivery. Fetal complications include macrosomia (birthweight greater than 4000 g), polyhydramnios (excessive amniotic fluid), preterm birth, shoulder dystocia (obstruction of vaginal delivery by the infant's shoulder), and neonatal complications of admission to high-level care, respiratory distress, hypoglycaemia (low blood sugar), and jaundice. Both women with GDM and their infants are at increased risk of diabetes mellitus and metabolic dysfunction later in life (Shah 2008; Vohr 2008).

Treatment of GDM improves pregnancy outcomes with significant reductions in the rate of serious perinatal outcomes including macrosomia, shoulder dystocia and caesarean delivery (Crowther 2005; Landon 2009). Current management practices for GDM are expensive but also cost effective for healthcare systems in the short and longer term (Ohno 2011). Primary prevention of GDM rather than treatment would however be ideal in preventing both the economic and health costs associated with GDM.

Efforts to prevent GDM have focused on lifestyle interventions (including diet and exercise) (Chuang 2010). These interventions have proven challenging, both to perform and in the analysis of effect due to heterogeneity, small study size, limited patient adherence to the intervention and methodological issues. Also, it is known that adherence to even simple measures such as folate supplementation is poor (Callaway 2009). Recent systematic reviews have concluded that no firm statement on the utility of nutritional interventions in controlling maternal weight or preventing GDM can be made (Dodd 2010; Streuling 2010). A Cochrane review examining the use of dietary advice in pregnancy for prevention of GDM has found that a low glycaemic diet was beneficial for some outcomes including a reduced rate of large-for-gestational-age infants; the results from the review were inconclusive (Tieu 2008). Another Cochrane review examining the utility of exercise is currently underway (Han 2011). Therefore, even if complex lifestyle intervention strategies were shown to prevent GDM, compliance with these interventions for the general population would be low. If probiotic supplementation were shown to be an effective method of reducing rates of GDM, there would be considerable benefits through improving maternal health and reducing pregnancy complications as well as a potential reduction in health service costs related to the management of GDM.

Description of the intervention

The World Health Organization defines probiotics as  “microorganisms ... able to confer defined health benefits on the host” (FAO/WHO 2001). Most probiotic products are either in food items (such as fermented milks or yogurts available in the supermarkets) or supplied as dietary supplements that typically are for sale in health food stores, pharmacies or natural food grocery stores. These products vary considerably in their microbial composition and number (dosage) of viable bacteria. Interventions of oral intake of probiotics in any form during pregnancy will be included for the review.

How the intervention might work

The relationship between diet, host metabolism and gut microbiome (the variety of bacterial strains in the gut) is multidirectional. Diet can influence microbiotal composition and gene expression as well as altering host metabolism directly. Altering the gut microbiome directly can also influence the host, including altering ease of nutrient absorption (Turnbaugh 2006), and influencing host inflammatory pathways, glucose and lipid metabolism (Backhed 2004; Musso 2010). Inflammation has been implicated in preterm labour and probiotics have been used in the prevention of preterm labour with inconclusive results (Othman 2007).

Obesity (Backhed 2009) and type 2 diabetes (Larsen 2010) are associated with divergent changes in the gut microbiome (the composite of bacteria present in the intestines). The gut microbiome in obese rodents and humans shows an overall decrease in microbiotal diversity, with an increase in Firmicutes phylum of bacteria, mainly of the Mollicutes class and a fall in the species belonging to the Bacteroidetes phylum of bacteria (Turnbaugh 2008; Turnbaugh 2009). Patients with type 2 diabetes have significantly reduced numbers of species belonging to the Firmicutes phylum. The ratio of Bacteroidetes:Firmicutes species in type 2 diabetes correlates positively with plasma glucose concentration but not body mass index. Bacteroidetes species are Gram negative bacteria, containing lipopolysaccharides in their outer wall, which could contribute to insulin resistance (Larsen 2010). A trial of supplementation of the probiotic strain Lactobacillus acidophilus NCFMTM in men with type 2 diabetes showed a preservation of insulin sensitivity but no change in inflammatory markers over a four-week period (Andreasen 2010). Improvements in glycaemia and lipids have been reported in other trials of probiotics in type 2 diabetes (Ejtahed 2012; Moroti 2012). Women with GDM are known to be at high risk of developing type 2 diabetes, and have a similar abnormal insulin resistance and alteration in lipid metabolism (Davey 2005). The gut microbiome has not been explored in GDM.

Why it is important to do this review

A recent study examining probiotics in pregnancy suggested a benefit in reducing the incidence of gestational diabetes (Laitinen 2008). Gestational diabetes is increasingly common and carries significant risks for both maternal and infant health. Other types of interventions, such as diet and exercise have proven difficult to carry out and have mixed results (Dodd 2010; Streuling 2010). Implementation of these interventions on a large scale practical clinical level would prove challenging and expensive. Probiotic supplementation, if beneficial, would be much easier to use in clinical practice. A systematic review of the available literature is required to establish whether there is any evidence to support the use of probiotic supplements during pregnancy for preventing gestational diabetes.

Objectives

To systematically assess the effects of probiotic supplements used either alone or in combination with pharmacological and non-pharmacological interventions on the incidence of gestational diabetes.

Methods

Criteria for considering studies for this review

Types of studies

Randomised and cluster-randomised trials. Cluster-randomised trials were eligible for inclusion but none were identified. Quasi-randomised and cross-over design studies are not eligible for inclusion in this review. Studies presented only as abstracts with no subsequent full report of study results would also have been excluded.

Types of participants

Studies that included pregnant women not previously diagnosed with diabetes mellitus. Studies of women with GDM in a previous pregnancy but no evidence of diabetes mellitus or GDM in the current pregnancy before entering the trial were eligible for inclusion.

Types of interventions

Probiotic supplementation for prevention of gestational diabetes, either alone or in combination with pharmacological (e.g. metformin) or non-pharmacological interventions (e.g. diet/lifestyle interventions).

Probiotic supplementation (administered by any method) should have been commenced prior to the diagnosis of gestational diabetes and continued for any duration.

Comparison interventions of any type were eligible, e.g. placebo, diet, exercise, pharmacological therapy (e.g. metformin).

Trials may have used other interventions in a comparison arm or in combination with the probiotic. These other interventions may have included pharmaceutical probiotic supplements as well as food items supplemented with probiotics.

Types of outcome measures

Primary outcomes
Maternal
  • Diagnosis of gestational diabetes mellitus, by the local criteria where the study was performed.

Infant
  • Macrosomia and large-for-gestational age.

  • Death (including intrauterine fetal death (IUFD), stillbirth and neonatal death).

Secondary outcomes
Maternal
  • Pre-eclampsia.

  • Changes in maternal gestational weight gain.

  • Preterm delivery.

  • Caesarean section.

  • Long-term outcome - diagnosis of diabetes mellitus.

Infant
  • Birthweight/birth centile, body composition.

  • Shoulder dystocia.

  • Admission to neonatal intensive care.

  • Jaundice.

  • Hypoglycaemia.

  • Longitudinal data - rates of obesity, rates of diabetes mellitus, body composition.

Search methods for identification of studies

Electronic searches

We searched the Cochrane Pregnancy and Childbirth Group’s Trials Register by contacting the Trials Search Co-ordinator (31 August 2013). 

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

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

  2. weekly searches of MEDLINE;

  3. weekly searches of Embase;

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

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

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

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

Searching other resources

We searched the reference lists of all retrieved studies.

We did not apply any language restrictions.

Data collection and analysis

Selection of studies

Two review authors (Helen Barrett and Marloes Dekker Nitert) independently assessed for inclusion all the potential studies we identified as a result of the search strategy. We resolved any disagreement through discussion or, if required, we consulted review author Leonie Callaway.

Data extraction and management

We designed a form to extract data. For the one eligible study, two review authors extracted the data using the agreed form. There were no discrepancies in data extraction on the form. We entered data into Review Manager software (RevMan 2012) and checked it for accuracy.

All information regarding any of the above was clear, and we made no attempt to contact authors of the original report to provide further details.

Assessment of risk of bias in included studies

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

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

We described the method used to generate the allocation sequence in sufficient detail to assess whether it produced 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 the methods used to conceal allocation to interventions prior to assignment and assessed whether the intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment.

We assessed the methods as:

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

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

  • unclear risk of bias.

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

We described the methods used to conceal the allocation sequence and determine whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment.
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 the methods used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. We considered that studies would be at low risk of bias if they were blinded, or if we judged that the lack of blinding would be unlikely to affect results. We assessed blinding separately for different outcomes or classes of outcomes.

We assessed the methods as:

  • low, high or unclear risk of bias.

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

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

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 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 is clear that all of the study’s prespecified outcomes and all expected outcomes of interest to the review have been reported);

  • high risk of bias (where not all the study’s pre-specified outcomes have been reported; one or more reported primary outcomes were not pre-specified; outcomes of interest are reported incompletely and so cannot be used; study fails 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 any important concerns we had about other possible sources of bias.
We assessed whether the included 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 the included study was at high risk of bias, according to the criteria given in the Handbook (Higgins 2011). 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.

Measures of treatment effect

Dichotomous data

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

Continuous data

For continuous data, we used the mean difference if outcomes were measured in the same way between trials. We planned to use the standardised mean difference to combine trials that measure the same outcome, but used different scales.  

Unit of analysis issues

Cluster-randomised trials

We did not identify any cluster-randomised trials for inclusion. However, if we identify cluster-randomised trials in future updates of this review, we will include cluster-randomised trials in the analyses along with individually-randomised trials. We will adjust their effect measure using the methods described in the Handbook using an estimate of the intracluster correlation co-efficient (ICC) derived from the trial (if possible), from a similar trial or from a study of a similar population. Where the cluster-randomised trial properly accounts for the cluster design, we will extract an estimate of the effect measure directly. Where the cluster-randomised trial does not properly account for the clustering, we will calculate the effective sample size of the intervention and placebo groups by dividing the sample size by the design effect. The design effect is 1+ (m-1)*ICC where the ICC is the intracluster correlation coefficient and m the average cluster size. The assessment of cluster-randomised trials and the calculation of the effective sample size will be performed with the assistance of a statistician. If we use ICCs from other sources, we will report this and conduct sensitivity analyses to investigate the effect of variation in the ICC. If we identify both cluster-randomised trials and individually-randomised trials, we plan to synthesise the relevant information. We will consider it reasonable to combine the results from both 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.

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

Dealing with missing data

The one included study had a low level of attrition over the follow-up period of 12 months postpartum of 18.75%. In future updates, we will explore the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis.

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

Assessment of heterogeneity

We planned to assess statistical heterogeneity in each meta-analysis using the T², I² and Chi² statistics. We would have regarded heterogeneity as substantial if the I² was greater than 30% and either the T² 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

Given only one study has reported results, reporting biases analysis has not yet been undertaken. In future updates of this review, if there are 10 or more studies in the meta-analysis we will investigate reporting biases (such as publication bias) using funnel plots. We will assess funnel plot asymmetry visually. If asymmetry is suggested by a visual assessment, we will perform exploratory analyses to investigate it.

Data synthesis

We carried out statistical analysis using the Review Manager software (RevMan 2012). We planned to use fixed-effect meta-analysis for combining data where it was reasonable to assume that studies were estimating the same underlying treatment effect: i.e. where trials examined the same intervention, and the trials’ populations and methods were judged sufficiently similar. As only one study has reported results, heterogeneity analysis has not yet been undertaken. If more studies are included in future updates of this review, and there is clinical heterogeneity sufficient to expect that the underlying treatment effects differ between trials, or if substantial statistical heterogeneity is detected, we will use random-effects meta-analysis to produce an overall summary, if an average treatment effect across trials is considered clinically meaningful. The random-effects summary will be treated as the average range of possible treatment effects and we will discuss the clinical implications of treatment effects differing between trials. If the average treatment effect is not clinically meaningful, we will not combine trials.

If we use random-effects analyses, the results will be presented as the average treatment effect with 95% confidence intervals, and the estimates of  T² and I².

For multi-arm trials, where there is a blinded placebo and unblinded control as well as treatment arm(s), the arms will be compared separately without double counting of participants. Where there is more than one treatment arm, each arm will be compared separately to each of the other arms, without double counting of participants.

Subgroup analysis and investigation of heterogeneity

Given only one study has reported results, subgroup analysis has not yet been undertaken. If we identify substantial heterogeneity in future updates as more trials are included, we will investigate it using subgroup analyses and sensitivity analyses. We will consider whether an overall summary is meaningful, and if it is, use random-effects analysis to produce it.

We plan to carry out the following subgroup analyses.

  1. Maternal body mass index (BMI): normal/overweight/obese. Subgroups defined by BMI. BMI will be categorised as underweight (BMI less than 18.49), normal weight (18.5 to 24.99), overweight (25.00 to 29.99), obesity class I (30.00 to 34.99), class II (35.00 to 39.99), class III (greater than 40.00) (WHO 2000; WHO Expert Consultation 2004). (underweight versus normal versus overweight versus obese).

  2. Past history of GDM (yes versus no).

  3. Family history of type 2 diabetes (yes versus no).

  4. Probiotic dose (more than 5 billion colony-forming units (CFU) versus less than 5 billion CFU).

  5. Probiotic bacterial species (each species versus others).

  6. Probiotic duration of treatment (early pregnancy versus more than 20 weeks).

  7. Probiotic mode of delivery (capsule versus other).

  8. Probiotic frequency of administration (daily versus other).

Subgroup analysis will be restricted to the review's primary outcomes.

We will assess subgroup differences by interaction tests available within RevMan (RevMan 2012). We will report the results of subgroup analyses quoting the χ2 statistic and p-value, and the interaction test I² value.

Sensitivity analysis

As only one study has reported results, sensitivity analysis has not yet been undertaken. Sensitivity analysis will be carried out, where necessary, to explore the influence of diagnostic criteria for GDM, and high drop-out rates (more than 20%).

Results

Description of studies

Results of the search

The search of the Cochrane Pregnancy and Childbirth Group's Trials Register retrieved eight citations. Review of the reference lists of these studies, and the reference lists of citations found in these studies yielded three further citations. The 11 citations related to five independent randomised controlled trials. Only one of these trials has reported results and has been included (Laitinen 2008). The other four studies are (Ahmed 2012; Callaway 2012; McAuliffe 2012; Wickens 2012) are ongoing (see Characteristics of ongoing studies) (see: Figure 1).

Figure 1.

Study flow diagram.

Included studies

Laitinen 2008 is the only study that has reported results and hence is the only included study at this point. The study was a double blind (for probiotics) randomised controlled trial carried out in Finland, with three treatment arms: placebo/diet and placebo/probiotic and diet. It included 256 women, of whom 7% were obese and 21% overweight, without any metabolic or chronic disease. The study duration for the woman was from early pregnancy until the end of exclusive breastfeeding, with follow-up until 24 months postpartum. The probiotic strains used were: Lactobacillus rhamnosus GG, ATCC 53 103, Valio Ltd, Helsinki, Finland and Bifidobacterium lactis Bb12, Chr. Hansen, Hoersholm, Denmark, 1010 colony-forming units/day each). Placebo was microcrystalline cellulose and dextrose anhydrate. The intensive dietary counselling was to conform to the currently recommended pregnancy diet.

Excluded studies

There are no excluded studies.

Risk of bias in included studies

See Characteristics of included studies. The included study was assessed to be at low risk of bias across all risk of bias domains. In the future, when the results of the study that three of the authors of this review are involved in (Helen Barrett, Marloes Dekker Nitert and Leonie Callaway) (Callaway 2012), the fourth author (Louise Conwell) will assess risk of bias with the assistance from the Cochrane Pregnancy and Childbirth Group in order to minimise the effects of conflict of interest.

Allocation

Laitinen 2008 used computer-generated block randomisation of six women in each block. The randomisation list was generated by a non-investigator statistician, and placed in sealed envelopes (Laitinen 2008).

Blinding

Placebo/probiotic allocation was blind to both participants and personnel, however, dietary therapy was not blinded to study staff (Laitinen 2008).

Incomplete outcome data

There was minimal loss to follow-up at the time of testing for gestational diabetes mellitus (Laitinen 2008).

Selective reporting

All findings reported (Laitinen 2008).

Other potential sources of bias

None.

Effects of interventions

Laitinen 2008 is the only currently completed study; the results of the study are described below. We used two comparisons from the three treatment arms in the study (probiotics + diet, placebo + diet and diet alone), halving the sample size and any relevant denominators for binary data from probiotic group data.

Probiotics versus control (diet or placebo)

Primary outcomes
Maternal outcome
Diagnosis of gestational diabetes

The use of probiotics was associated with a reduction in the rate of gestational diabetes (risk ratio (RR) 0.38, 95% confidence interval (CI) 0.20 to 0.70) (Analysis 1.1) (Figure 2).

Figure 2.

Forest plot of comparison: 1 Primary maternal and infant outcomes: Probiotics vs placebo or diet, outcome: 1.1 Diagnosis of gestational diabetes.

Infant outcome
Death (including miscarriage/IUFD/stillbirth/neonatal death)

The use of probiotics did not alter the rates of death at any stage of the pregnancy or in early infancy (RR 2.00, 95% CI 0.35 to 11.35) (Analysis 1.2) (Figure 3).

Figure 3.

Forest plot of comparison: 1 Primary maternal and infant outcomes: Probiotics vs placebo or diet, outcome: 1.2 Miscarriage/IUFD/Stillbirth/Neonatal death.

Macrosomia/large-for-gestational-age babies

This outcome was not assessed (Analysis 1.3).

Secondary outcomes
Maternal outcomes
Rates of pre-eclampsia.

This outcome was not reported on (Analysis 2.1).

Maternal gestational weight gain

This outcome was not reported on (Analysis 2.2).

Preterm delivery

The use of probiotics did not affect the rates of preterm delivery (RR 3.27, 95% CI 0.44 to 24.43) (Analysis 2.3) (Figure 4) .

Figure 4.

Forest plot of comparison: 2 Secondary maternal outcomes: probiotics vs placebo or diet, outcome: 2.3 Preterm delivery < 37 weeks' gestation.

Caesarean section

Probiotic supplementation did not change the rate of caesarean section (RR 1.23, 95% CI 0.65 to 2.32) (Analysis 2.4) ( Figure 5).

Figure 5.

Forest plot of comparison: 2 Secondary maternal outcomes: probiotics vs placebo or diet, outcome: 2.4 Caesarean section.

Long-term risk of diabetes mellitus

This outcome was not reported on (Analysis 2.5).

Infant outcomes
Infant birthweight, birth centile and body composition

Infant birthweight was assessed and there was a reduction of birthweight in the women taking probiotics supplementation (mean difference (MD) -127.71 g, 95% CI -251.37 to -4.06) (Analysis 3.1) (Figure 6). Birth centile (Analysis 3.2) and infant body composition Analysis 3.3 were not reported on.

Figure 6.

Forest plot of comparison: 3 Secondary infant outcomes: probiotics vs placebo or diet, outcome: 3.1 Birthweight.

Shoulder dystocia

This outcome was not reported (Analysis 3.4).

Admission to neonatal intensive care unit

This outcome was not reported (Analysis 3.5).

Jaundice

This outcome was not reported (Analysis 3.6).

Hypoglycaemia

This outcome was not reported (Analysis 3.7).

Long-term outcomes

The outcomes childhood obesity (Analysis 3.8), rate of diabetes mellitus (Analysis 3.9) and childhood body composition (Analysis 3.10) were not reported in the included study.

Discussion

Summary of main results

We included one study, involving 256 women. However, this study does show a 60% decrease in the rate of diagnosis of gestational diabetes mellitus in women taking probiotics from early pregnancy. No further analysis was done at this time due to there being only one completed study. No subgroup analyses have been undertaken as yet for the same reason. This will be addressed when the results of the ongoing studies are reported.

Overall completeness and applicability of evidence

The one completed study (Laitinen 2008) reported multiple maternal and infant outcomes across their various publications. They did not report on all the primary and secondary outcome measures to be included in this systematic review.

Quality of the evidence

The one study completed (Laitinen 2008) is a double blind, randomised trial of 256 women who were followed up for 12 months postpartum. The positive results of this study require confirmation with other studies also in populations at increased risk for developing gestational diabetes mellitus. There are four studies currently ongoing.

Potential biases in the review process

This review addresses a new area of research with only a limited number of studies identified. The search for studies in this area was performed using the Cochrane Pregnancy and Childbirth Group’s Trials Register which is updated weekly to monthly with information from the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, handsearches from 30 journals and conference proceeding of major conferences and alerts for a further 44 journals. It is unlikely that studies that have concluded have been missed, however, ongoing studies that have not been registered in clinical trial registries could be missing. This would not alter the conclusion of the current review since there would not be any results to analyse yet. There was a low risk of bias within the one completed study for selection bias, performance bias, reporting bias and attrition bias. The data were extracted from the six publications relating to this study, however, the investigators were not contacted to obtain additional data. The data analysis for this study has necessarily been limited until further studies with relevant outcomes are reported.

Agreements and disagreements with other studies or reviews

Since this review addresses a new area of research, there have only been two reviews of the impact of probiotics on gestational diabetes mellitus, one written by the authors of this review (Barrett 2012) and one with a broader focus on maternal outcomes (Lindsay 2013). The inclusion criteria were slightly different between the reviews but the outcomes reported are in agreement with the ones reported in this Cochrane review.

Authors' conclusions

Implications for practice

The results from the included study (involving 256 women) suggest that probiotics may reduce the risk of gestational diabetes mellitus. This requires confirmation with further studies and especially in populations with higher risks of developing gestational diabetes mellitus. There are inadequate data to determine the effect of probiotics on fetal or neonatal death and macrosomia.

Implications for research

Further studies are needed to confirm the results of Laitinen 2008. Probiotics may have beneficial effects on other outcomes than gestational diabetes mellitus such as rates of macrosomia/large-for-gestational-age infants, infant body composition, maternal pre-eclampsia, delivery by caesarean section, and future risk of metabolic disease for mother and infant. These outcomes should be addressed in further studies. Potential additional aspects to be addressed in future studies include dosage of the probiotics, strain specificity, storage conditions and shelf life of the probiotics.

Acknowledgements

As part of the pre-publication editorial process, this review has been commented on by three peers (an editor and two referees who are external to the editorial team), a member of the Pregnancy and Childbirth Group's international panel of consumers and the Group's Statistical Adviser.

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

Data and analyses

Download statistical data

Comparison 1. Primary maternal and infant outcomes: probiotics versus placebo or diet
Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size
1 Diagnosis of gestational diabetes1225Risk Ratio (M-H, Fixed, 95% CI)0.38 [0.20, 0.70]
1.1 Probiotics versus placebo1111Risk Ratio (M-H, Fixed, 95% CI)0.38 [0.16, 0.92]
1.2 Probiotics versus diet1114Risk Ratio (M-H, Fixed, 95% CI)0.37 [0.15, 0.89]
2 Miscarriage/IUFD/Stillbirth/Neonatal death1256Risk Ratio (M-H, Fixed, 95% CI)2.0 [0.35, 11.35]
2.1 Probiotics versus diet1127Risk Ratio (M-H, Fixed, 95% CI)6.0 [0.25, 144.22]
2.2 Probiotics versus placebo1129Risk Ratio (M-H, Fixed, 95% CI)1.0 [0.09, 10.72]
3 Macrosomia00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
3.1 Probiotics versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
3.2 Probiotics versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
Analysis 1.1.

Comparison 1 Primary maternal and infant outcomes: probiotics versus placebo or diet, Outcome 1 Diagnosis of gestational diabetes.

Analysis 1.2.

Comparison 1 Primary maternal and infant outcomes: probiotics versus placebo or diet, Outcome 2 Miscarriage/IUFD/Stillbirth/Neonatal death.

Comparison 2. Secondary maternal outcomes: probiotics versus placebo or diet
Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size
1 Pre-eclampsia00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
1.1 Probiotics versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
1.2 Probiotics versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
2 Gestational weight gain00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
2.1 Probiotic versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
2.2 Probiotic versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
3 Preterm delivery < 37 weeks' gestation1238Risk Ratio (M-H, Fixed, 95% CI)3.27 [0.44, 24.43]
3.1 Probiotics versus placebo1119Risk Ratio (M-H, Fixed, 95% CI)1.98 [0.13, 30.76]
3.2 Probiotics versus diet1119Risk Ratio (M-H, Fixed, 95% CI)5.85 [0.24, 140.54]
4 Caesarean section1218Risk Ratio (M-H, Fixed, 95% CI)1.23 [0.65, 2.32]
4.1 Probiotics versus placebo1109Risk Ratio (M-H, Fixed, 95% CI)1.26 [0.51, 3.11]
4.2 Probiotics versus diet1109Risk Ratio (M-H, Fixed, 95% CI)1.20 [0.49, 2.93]
5 Maternal diagnosis of diabetes mellitus postpartum00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
5.1 Probiotics versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
5.2 Probiotics versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
Analysis 2.3.

Comparison 2 Secondary maternal outcomes: probiotics versus placebo or diet, Outcome 3 Preterm delivery < 37 weeks' gestation.

Analysis 2.4.

Comparison 2 Secondary maternal outcomes: probiotics versus placebo or diet, Outcome 4 Caesarean section.

Comparison 3. Secondary infant outcomes: probiotics versus placebo or diet
Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size
1 Birthweight1256Mean Difference (IV, Random, 95% CI)-127.71 [-251.37, -4.06]
1.1 Probiotics versus placebo1128Mean Difference (IV, Random, 95% CI)-144.0 [-320.46, 32.46]
1.2 Probiotics versus diet1128Mean Difference (IV, Random, 95% CI)-112.0 [-285.33, 61.33]
2 Birthweight centile00Mean Difference (IV, Fixed, 95% CI)0.0 [0.0, 0.0]
2.1 Probiotics versus placebo00Mean Difference (IV, Fixed, 95% CI)0.0 [0.0, 0.0]
2.2 Probiotics versus diet00Mean Difference (IV, Fixed, 95% CI)0.0 [0.0, 0.0]
3 Percentage body fat (neonatal)00Mean Difference (IV, Fixed, 95% CI)0.0 [0.0, 0.0]
3.1 Probiotics versus placebo00Mean Difference (IV, Fixed, 95% CI)0.0 [0.0, 0.0]
3.2 Probiotics versus diet00Mean Difference (IV, Fixed, 95% CI)0.0 [0.0, 0.0]
4 Shoulder dystocia00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
4.1 Probiotics versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
4.2 Probiotics versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
5 Admission to neonatal intensive care00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
5.1 Probiotics versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
5.2 Probiotics versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
6 Jaundice00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
6.1 Probiotics versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
6.2 Probiotics versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
7 Hypoglycaemia00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
7.1 Probiotics versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
7.2 Probiotics versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
8 Childhood obesity00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
8.1 Probiotics versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
8.2 Probiotics versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
9 Infant diagnosis of diabetes mellitus00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
9.1 Probiotics versus placebo00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
9.2 Probiotics versus diet00Risk Ratio (M-H, Fixed, 95% CI)0.0 [0.0, 0.0]
10 Percentage body fat (childhood)00Mean Difference (IV, Fixed, 95% CI)0.0 [0.0, 0.0]
10.1 Probiotics versus placebo00Mean Difference (IV, Fixed, 95% CI)0.0 [0.0, 0.0]
10.2 Probiotics versus diet00Mean Difference (IV, Fixed, 95% CI)0.0 [0.0, 0.0]
Analysis 3.1.

Comparison 3 Secondary infant outcomes: probiotics versus placebo or diet, Outcome 1 Birthweight.

Contributions of authors

Helen Barrett and Marloes Dekker Nitert developed the protocol. Louise Callaway and Leonie Conwell edited and commented on the protocol. Helen Barrett and Marloes Dekker Nitert wrote the review, assessed the citations and studies found for inclusion, risk of bias and data analysis. Leonie Callaway and Louise Conwell assisted with data interpretation, and edited and commented on the review.

Declarations of interest

Louise Conwell - none known.

Leonie Callaway, Marloes Dekker Nitert and Helen Barrett are investigators in a trial examining the use of probiotics for preventing gestational diabetes mellitus (Callaway 2012) - Leonie Callaway is the primary investigator of this trial. In future updates of this review, these investigators will not be involved in any decisions relating to their trial: assessment of the trial for inclusion, assessment of risk of bias and data extraction will be carried out by individuals who are not directly involved in the trial. Louise Conwell (review author) and a third party will carry out these tasks.

Sources of support

Internal sources

  • The University of Queensland, School of Medicine, Australia.

    salary

External sources

  • Royal Brisbane and Women's Hospital, Foundation, Australia.

    salary

Differences between protocol and review

None.

Characteristics of studies

Characteristics of included studies [ordered by study ID]

Laitinen 2008

  1. a

    Hb: haemoglobin
    HOMA: homeostasis model assessment
    QUICKI: quantitative insulin sensitivity check index

Methods

DESIGN: randomised controlled trial.

BLINDING: double blind for probiotics/placebo, single blind for dietary intervention.

UNIT OF COMPARISON: individuals.

DURATION: supplementation with probiotic/placebo from early pregnancy until the end of exclusive breastfeeding.

FOLLOW-UP: 24 months postpartum.

LOCATION: Finland.

Participants

TOTAL NUMBER: 256.

No metabolic or chronic diseases.

7% of women were obese, 21% were overweight.

Interventions

PROBIOTIC: Lactobacillus rhamnosus GG, ATCC 53 103, Valio Ltd, Helsinki, Finland and Bifidobacterium lactis Bb12, Chr. Hansen, Hoersholm, Denmark, 1010 colony-forming units/d each).

PLACEBO: microcrystalline cellulose and dextrose anhydrate.

DIETARY: intensive dietary counselling aiming to conform to currently recommended pregnancy diet.

OutcomesPRIMARY: maternal glucose metabolism as measured by plasma glucose, blood HbA1c, serum insulin and HOMA and QUICKI indices at baseline, third trimester of pregnancy, 1, 6 and 12 months postpartum.
NotesNCT00167700
Risk of bias
BiasAuthors' judgementSupport for judgement
Random sequence generation (selection bias)Low riskComputer-generated block randomisation of 6 women. The use of only 1 block size could make it possible to guess the randomisation of the dietary intervention of the last individuals of each block. However, since this randomisation was only blinded to the participants and not the study personnel, the selection bias risk is still considered to be low.
Allocation concealment (selection bias)Low riskRandomisation list generated by a non-investigator statistician, sealed envelopes.
Blinding of participants and personnel (performance bias)
All outcomes
Low riskPlacebo/probiotic allocation was blind to both participants and personnel, dietary therapy was not blinded to personnel.
Blinding of outcome assessment (detection bias)
All outcomes
Low riskAll personnel who handled or analysed blood samples were blind to the intervention.
Incomplete outcome data (attrition bias)
All outcomes
Low riskMinimal loss to follow-up by assessment of glucose tolerance. Total loss to follow-up was 18.75% by 1 year postpartum.
Selective reporting (reporting bias)Low riskReported all outcomes they intended to report.
Other biasLow riskNo other biases detected.

Characteristics of ongoing studies [ordered by study ID]

Ahmed 2012

Trial name or titleProbiotics (Lactobacillus Rhamnosus) in reducing glucose intolerance during and after pregnancy (GRIP).
Methods

DESIGN: randomised controlled trial.

BLINDING: double blind for probiotics/placebo.

DURATION: supplementation with probiotic/placebo from early pregnancy until delivery.

FOLLOW-UP: 6 weeks postpartum.

LOCATION: Pakistan.

ParticipantsWomen in early pregnancy, 18-45 years with 1 or more of: BMI > 23 OR family history of diabetes in first-degree relatives, or maternal age > 35.
InterventionsPROBIOTIC: Lactobacillus rhamnosus 1010 colony-forming units/d each.
OutcomesGlucose tolerance by OGTT using ADA guidelines between 24-28 weeks' gestation and at 6-8 weeks' postpartum.
Starting dateOctober 2011.
Contact informationPrincipal Investigator: Bilal Ahmed, MSc, Aga Khan University.
NotesNCT01436448

Callaway 2012

Trial name or titleSPRING: an RCT study of probiotics in the prevention of gestational diabetes mellitus in overweight and obese women.
Methods

DESIGN: randomised controlled trial.

BLINDING: double blind for probiotics/placebo.

DURATION: supplementation with probiotic/placebo from early pregnancy until delivery.

LOCATION: Australia.

ParticipantsOverweight and obese women, < 16 weeks' gestation at study entry, 18-45 years.
Interventions

PROBIOTIC: Lactobacillus rhamnosus GG and Bifidobacterium lactis Bb12, Chr. Hansen, Hoersholm, Denmark, 109 colony-forming units/d each).

PLACEBO: microcrystalline cellulose and dextrose anhydrate.

OutcomesGlucose tolerance by OGTT using IADPSG guidelines between 24-28 weeks' gestation.
Starting dateNovember 2012.
Contact informationA/Prof Leonie Callaway, The University of Queensland.
NotesACTRN12611001208998

McAuliffe 2012

Trial name or titleProbiotics in Pregnancy Study (ProP Study).
Methods

DESIGN: randomised controlled trial.

BLINDING: double blind for probiotics/placebo.

DURATION: supplementation with probiotic/placebo from early pregnancy until delivery.

LOCATION: Ireland.

Participants

1) Part A: Prevention of GDM: obese women aged 18-45 years, < 22 weeks' gestation.

2) Part B: Treatment of GDM: women with GDM or Impaired glucose tolerance, any BMI, aged 18-45 years, < 36 weeks' gestation.

Interventions

PROBIOTIC:

PLACEBO:

Outcomes1) Part A: difference between the control and probiotic groups in fasting blood glucose.
2) Part B: difference between the control and probiotic groups in fasting blood glucose.
Starting date20/02/2012.
Contact informationProf  Fionnuala  McAuliffe.
NotesISRCTN97241163

Wickens 2012

  1. a

    AFA: American Diabetes Association
    ADIPS: Australasian Diabetes in Pregnancy Society
    BMI: body mass index
    CFU: colony forming unit
    GDM: gestational diabetes mellitus
    IADPSG: International Association of the Diabetes and Pregnancy Study Groups
    OGTT: oral glucose tolerance test
    RCT: randomised controlled trial

Trial name or titleA randomised placebo-controlled trial of the effects of the probiotic Lactobacillus rhamnosus HN001 taken from the 1st trimester of pregnancy till 6 months postpartum, if breastfeeding, on the development of eczema and atopic sensitisation in infants by age 12 months. (PIP)
Methods

DESIGN: randomised controlled trial.

BLINDING: double blind for probiotics/placebo.

DURATION: supplementation with probiotic/placebo from early pregnancy until 6 months postpartum.

LOCATION: New Zealand.

ParticipantsWomen 14-16 weeks' gestation, if they or the infant's father has a history of asthma, eczema or allergic rhinitis. No weight or age limits.
Interventions

PROBIOTIC: Lactobacillus rhamnosus HN001 administered daily as capsules. The starting viable cell number is 6.1x1010 CFU* per g, which equates to a dose per capsule of 9.2x109 CFU.

PLACEBO: the placebo will be identical in appearance and smell and contain maltodextran only.

Outcomes

PRIMARY: infant eczema and atopic sensitisation at age 12 months.

SECONDARY: gestational diabetes mellitus (OGTT 75g using ADIPS criteria), bacterial vaginosis, group B strep, breast milk cytokines, maternal and infant anthropometry, maternal lipids and incretin hormones.

Starting date20/12/2012.
Contact informationDr Kristin Wickens, University of Otago, New Zealand.
NotesACTRN12612000196842

Ancillary