Ignite Creation Date:
2025-12-24 @ 10:33 PM
Ignite Modification Date:
2026-01-02 @ 11:57 PM
Study NCT ID:
NCT06704035
Status:
NOT_YET_RECRUITING
Last Update Posted:
2024-11-25
First Post:
2024-10-17
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Early Screening for Gestational Diabetes Mellitus in a Low Risk Population
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D016640', 'term': 'Diabetes, Gestational'}, {'id': 'D011248', 'term': 'Pregnancy Complications'}], 'ancestors': [{'id': 'D005261', 'term': 'Female Urogenital Diseases and Pregnancy Complications'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'SCREENING', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'Classic two parallel arm study in a 1:1 ratio. Participants will be assigned at random using a computerised database to either an experimental group (early "OGTT Results Revealed"), or a control group (early "OGTT Results Concealed"). The investigators, healthcare providers and participants will know which study arm they are allocated to, but the early OGTT results will only be made known for the "OGTT Results Revealed" group.'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 120}}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2024-12-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-09', 'completionDateStruct': {'date': '2026-11-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-11-21', 'studyFirstSubmitDate': '2024-10-17', 'studyFirstSubmitQcDate': '2024-11-21', 'lastUpdatePostDateStruct': {'date': '2024-11-25', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-11-25', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-04-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Composite of perinatal/neonatal morbidity/mortality', 'timeFrame': 'At birth to one month postpartum', 'description': "Display at least one of the following outcomes: preterm birth \\<37 weeks' gestation, large for gestational age neonate \\>90th centile of birthweight, birth trauma, shoulder dystocia, neonatal hypoglycaemia, neonatal respiratory distress, jaundice requiring phototherapy, stillbirth/neonatal death."}], 'secondaryOutcomes': [{'measure': 'Pre-eclampsia and hypertensive disorders of pregnancy', 'timeFrame': 'Up to 49 weeks, from the estimated date of conception (based on menstrual and ultrasound scan data) up to 6 weeks postpartum', 'description': 'Number and proportion of participants who experience new onset hypertension in pregnancy, pre-eclampsia, eclampsia, or superimposed pre-eclampsia on chronic hypertension, with or without signs of progressive multi-system disorder or end-organ involvement, including cases of atypical pre-eclampsia where hypertension is not the predominant feature.'}, {'measure': 'Antenatal and Peripartum obstetric events', 'timeFrame': 'Up to 49 weeks, from the estimated date of conception (based on menstrual and ultrasound scan data) up to 6 weeks postpartum', 'description': 'Number and proportion of participants who experience antenatal complications, undergo caesarean section, suffer perineal trauma, experience postpartum haemorrhage, or require other delivery interventions, including labour induction, extended labour duration, use of oxytocin, instrumental delivery, and high dependency care.'}, {'measure': 'Birthweight', 'timeFrame': 'At Birth', 'description': 'Raw birthweight, macrosomia defined as birthweight \\>4000g, low birthweight \\<2500g, Large for Gestational Age (\\>90th centile) and Small for Gestational Age (\\<10th centile) using customised/standardised birthweight references.'}, {'measure': 'Neonatal complications and treatments', 'timeFrame': 'From Birth to 3 months post-delivery', 'description': 'Admission to neonatal unit (including level of unit and length of stay), infant weight gain, hyperbilirubinaemia, infections, treatments (including antibiotics, iv/tube feeding, blood products, oxygen, breathing aids) and other neonatal conditions requiring medical care.'}, {'measure': 'Maternal depression and anxiety symptoms', 'timeFrame': "Before 16 weeks' gestation, at around 24-28 weeks gestation (accepted up to 32 weeks and 6 days), postpartum (~1 month; accept 3-6 weeks post-delivery)", 'description': 'Scores of maternal depression and anxiety symptoms on validated questionnaires (Edinburgh Postnatal Depression Scale and Generalized Anxiety Disorder-7 Scale). The scores on the Edinburgh Postnatal Depression Scale range from 0 to 30, with higher scores indicating more depression symptoms. The scores on the Generalized Anxiety Disorder-7 range from 0 to 21, where higher scores indicate more anxiety symptoms.'}, {'measure': 'Breastfeeding', 'timeFrame': 'Postpartum (~1 month; accept 3-6 weeks post-delivery)', 'description': 'Interviewer-administered questionnaire to evaluate the incidence and timing of skin-to-skin post-delivery, first suckle, duration of exclusivity of breastfeeding, and intake of formula feeds (timing of onset, duration, and frequency).'}, {'measure': 'Prevalences of pre-existing diabetes mellitus and postpartum dysglycaemia (diabetes and pre-diabetes)', 'timeFrame': 'Oral glucose tolerance test (OGTT) before 16 weeks of gestation and at around 6-12 weeks postpartum', 'description': 'Pre-existing diabetes is identified based on glucose concentrations in a 75g OGTT defined by the World Health Organization (WHO) diagnostic criteria for non-pregnant adults. The following values are used to diagnose pre-existing diabetes: fasting glucose (0-hour): ≥ 7.0 mmol/L or 2-hour post-load glucose: ≥ 11.1 mmol/L. If either of these is met during the early pregnancy OGTT and post-partum OGTT (6-12 weeks post-delivery), the participant is diagnosed with pre-existing diabetes. Postpartum OGTT results will be obtained from medical records. Pre-diabetes postpartum will be identified by a 75g OGTT following the 2006 WHO criteria: Impaired fasting glucose (IFG) will be diagnosed when fasting plasma glucose (FPG) is between 6.1-6.9 mmol/L, while impaired glucose tolerance (IGT) will be defined by a 2-hour plasma glucose of 7.8-11.0 mmol/L.'}, {'measure': 'Gestational diabetes incidence (early and late diagnosis)', 'timeFrame': 'Pregnancy Oral Glucose Tolerance Test (OGTT) before 16 weeks of gestation and/or at around 24-28 weeks of gestation (accept all results till 32 weeks and 6 days)', 'description': 'GDM is diagnosed based on criteria set by the International Association of Diabetes and Pregnancy Study Groups (IADPSG) and WHO (2013). If at least one plasma glucose value meet the following criteria during a 75g three time point OGTT, it will indicate GDM: fasting glucose: ≥ 5.1 mmol/L, 1-hour post-load glucose: ≥ 10.0 mmol/L or 2-hour post-load glucose: ≥ 8.5 mmol/L.'}, {'measure': 'Predictive performance of a novel machine-learning-derived algorithm', 'timeFrame': 'Up to 54 weeks, from the estimated date of conception (based on menstrual and ultrasound scan data) up to the time of latest OGTT (32 weeks and 6 days gestation or OGTT at 6-12 weeks postpartum)', 'description': 'A novel machine-learning-derived algorithm, specifically designed for the Singapore pregnant population, will use clinical data collected in early pregnancy (including maternal age, ethnicity, mean arterial blood pressure) to predict GDM development. The sensitivity, specificity, positive predictive and negative predictive value, receiver operating characteristic curve (ROC curve) will be evaluated for GDM and glucose intolerance as well as for pregnancy and neonatal outcomes.'}, {'measure': 'Continuous Glucose Monitor (CGM) Data Measurements and predictive performance', 'timeFrame': 'Up to 48 weeks, from recruitment up to the time of latest OGTT (32 weeks and 6 days gestation or OGTT at 6-12 weeks postpartum)', 'description': 'Identification of the key metrics from CGM evaluation that predict GDM, glucose intolerance, later pregnancy/postpartum dysglycaemia, and pregnancy and neonatal outcomes.'}, {'measure': 'Gingival crevicular fluid (GCF) and circulating biomarkers', 'timeFrame': 'Up to 48 weeks, from recruitment up to the time of latest OGTT (32 weeks and 6 days gestation or OGTT at 6-12 weeks postpartum)', 'description': 'Identification of the key biomarkers from metabolomic, proteomic, and transcriptomic analyses on gingival crevicular fluid samples and blood obtained in early pregnancy that associate with GDM and glucose intolerance, later pregnancy/postpartum dysglycaemia, and pregnancy and neonatal outcomes.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Early screening', 'Gestational diabetes', 'Oral glucose tolerance test (OGTT)', 'Neonatal complications', 'Pregnancy complications', 'Machine learning algorithm', 'Continuous glucose monitoring (CGM)', 'Gingival crevicular fluid (GCF)', 'IADPSG criteria', 'WHO 2013 gestational diabetes criteria'], 'conditions': ['Gestational Diabetes Mellitus (GDM)', 'Glucose Intolerance During Pregnancy']}, 'referencesModule': {'references': [{'pmid': '35141761', 'type': 'BACKGROUND', 'citation': 'Teo E, Hassan N, Tam W, Koh S. Effectiveness of continuous glucose monitoring in maintaining glycaemic control among people with type 1 diabetes mellitus: a systematic review of randomised controlled trials and meta-analysis. Diabetologia. 2022 Apr;65(4):604-619. doi: 10.1007/s00125-021-05648-4. Epub 2022 Feb 9.'}, {'pmid': '35629058', 'type': 'BACKGROUND', 'citation': 'Majewska A, Stanirowski PJ, Wielgos M, Bomba-Opon D. Efficacy of Continuous Glucose Monitoring on Glycaemic Control in Pregnant Women with Gestational Diabetes Mellitus-A Systematic Review. J Clin Med. 2022 May 23;11(10):2932. doi: 10.3390/jcm11102932.'}, {'pmid': '18463375', 'type': 'BACKGROUND', 'citation': 'HAPO Study Cooperative Research Group; Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, Coustan DR, Hadden DR, McCance DR, Hod M, McIntyre HD, Oats JJ, Persson B, Rogers MS, Sacks DA. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med. 2008 May 8;358(19):1991-2002. doi: 10.1056/NEJMoa0707943.'}, {'pmid': '35784581', 'type': 'BACKGROUND', 'citation': 'Li LJ, Huang L, Tobias DK, Zhang C. Gestational Diabetes Mellitus Among Asians - A Systematic Review From a Population Health Perspective. Front Endocrinol (Lausanne). 2022 Jun 16;13:840331. doi: 10.3389/fendo.2022.840331. eCollection 2022.'}, {'pmid': '29793404', 'type': 'BACKGROUND', 'citation': 'Simmons D, Hague WM, Teede HJ, Cheung NW, Hibbert EJ, Nolan CJ, Peek MJ, Girosi F, Cowell CT, Wong VW, Flack JR, McLean M, Dalal R, Robertson A, Rajagopal R. Hyperglycaemia in early pregnancy: the Treatment of Booking Gestational diabetes Mellitus (TOBOGM) study. A randomised controlled trial. Med J Aust. 2018 Nov 5;209(9):405-406. doi: 10.5694/mja17.01129. Epub 2018 May 28.'}, {'pmid': '30061318', 'type': 'BACKGROUND', 'citation': 'Vinter CA, Tanvig MH, Christensen MH, Ovesen PG, Jorgensen JS, Andersen MS, McIntyre HD, Jensen DM. Lifestyle Intervention in Danish Obese Pregnant Women With Early Gestational Diabetes Mellitus According to WHO 2013 Criteria Does Not Change Pregnancy Outcomes: Results From the LiP (Lifestyle in Pregnancy) Study. Diabetes Care. 2018 Oct;41(10):2079-2085. doi: 10.2337/dc18-0808. Epub 2018 Jul 30.'}, {'pmid': '31926951', 'type': 'BACKGROUND', 'citation': 'Harper LM, Jauk V, Longo S, Biggio JR, Szychowski JM, Tita AT. Early gestational diabetes screening in obese women: a randomized controlled trial. Am J Obstet Gynecol. 2020 May;222(5):495.e1-495.e8. doi: 10.1016/j.ajog.2019.12.021. Epub 2020 Jan 9.'}, {'pmid': '34262311', 'type': 'BACKGROUND', 'citation': 'Minschart C, Beunen K, Benhalima K. An Update on Screening Strategies for Gestational Diabetes Mellitus: A Narrative Review. Diabetes Metab Syndr Obes. 2021 Jul 5;14:3047-3076. doi: 10.2147/DMSO.S287121. eCollection 2021.'}, {'pmid': '27208326', 'type': 'BACKGROUND', 'citation': 'Logan KM, Emsley RJ, Jeffries S, Andrzejewska I, Hyde MJ, Gale C, Chappell K, Mandalia S, Santhakumaran S, Parkinson JR, Mills L, Modi N. Development of Early Adiposity in Infants of Mothers With Gestational Diabetes Mellitus. Diabetes Care. 2016 Jun;39(6):1045-51. doi: 10.2337/dc16-0030. Epub 2016 May 12.'}, {'pmid': '27208333', 'type': 'BACKGROUND', 'citation': 'Sovio U, Murphy HR, Smith GC. Accelerated Fetal Growth Prior to Diagnosis of Gestational Diabetes Mellitus: A Prospective Cohort Study of Nulliparous Women. Diabetes Care. 2016 Jun;39(6):982-7. doi: 10.2337/dc16-0160. Epub 2016 Apr 7.'}, {'pmid': '15951574', 'type': 'BACKGROUND', 'citation': 'Crowther CA, Hiller JE, Moss JR, McPhee AJ, Jeffries WS, Robinson JS; Australian Carbohydrate Intolerance Study in Pregnant Women (ACHOIS) Trial Group. Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. N Engl J Med. 2005 Jun 16;352(24):2477-86. doi: 10.1056/NEJMoa042973. Epub 2005 Jun 12.'}, {'pmid': '29790168', 'type': 'BACKGROUND', 'citation': 'Chaparro A, Zuniga E, Varas-Godoy M, Albers D, Ramirez V, Hernandez M, Kusanovic JP, Acuna-Gallardo S, Rice G, Illanes SE. Periodontitis and placental growth factor in oral fluids are early pregnancy predictors of gestational diabetes mellitus. J Periodontol. 2018 Sep;89(9):1052-1060. doi: 10.1002/JPER.17-0497.'}, {'pmid': '37342498', 'type': 'BACKGROUND', 'citation': 'Abouzaid M, Howidi N, Badran Z, Mohammed G, Mousa NA. The potential role of the gingival crevicular fluid biomarkers in the prediction of pregnancy complications. Front Med (Lausanne). 2023 Jun 5;10:1168625. doi: 10.3389/fmed.2023.1168625. eCollection 2023.'}, {'pmid': '31242249', 'type': 'BACKGROUND', 'citation': 'Monteiro LJ, Varas-Godoy M, Monckeberg M, Realini O, Hernandez M, Rice G, Romero R, Saavedra JF, Illanes SE, Chaparro A. Oral extracellular vesicles in early pregnancy can identify patients at risk of developing gestational diabetes mellitus. PLoS One. 2019 Jun 26;14(6):e0218616. doi: 10.1371/journal.pone.0218616. eCollection 2019.'}, {'pmid': '27552375', 'type': 'BACKGROUND', 'citation': 'Ozcaka O, Ceyhan-Ozturk B, Gumus P, Akcali A, Nalbantsoy A, Buduneli N. Clinical periodontal status and inflammatory cytokines in gestational diabetes mellitus. Arch Oral Biol. 2016 Dec;72:87-91. doi: 10.1016/j.archoralbio.2016.08.012. Epub 2016 Aug 11.'}, {'pmid': '31198325', 'type': 'BACKGROUND', 'citation': 'Subbarao KC, Nattuthurai GS, Sundararajan SK, Sujith I, Joseph J, Syedshah YP. Gingival Crevicular Fluid: An Overview. J Pharm Bioallied Sci. 2019 May;11(Suppl 2):S135-S139. doi: 10.4103/JPBS.JPBS_56_19.'}, {'pmid': '36299907', 'type': 'BACKGROUND', 'citation': 'Di Filippo D, Ahmadzai M, Chang MHY, Horgan K, Ong RM, Darling J, Akhtar M, Henry A, Welsh A. Continuous Glucose Monitoring for the Diagnosis of Gestational Diabetes Mellitus: A Pilot Study. J Diabetes Res. 2022 Oct 17;2022:5142918. doi: 10.1155/2022/5142918. eCollection 2022.'}, {'pmid': '30822494', 'type': 'BACKGROUND', 'citation': 'Afandi B, Hassanein M, Roubi S, Nagelkerke N. The value of Continuous Glucose Monitoring and Self-Monitoring of Blood Glucose in patients with Gestational Diabetes Mellitus during Ramadan fasting. Diabetes Res Clin Pract. 2019 May;151:260-264. doi: 10.1016/j.diabres.2019.01.036. Epub 2019 Feb 26.'}, {'pmid': '31681170', 'type': 'BACKGROUND', 'citation': 'Yu Q, Aris IM, Tan KH, Li LJ. Application and Utility of Continuous Glucose Monitoring in Pregnancy: A Systematic Review. Front Endocrinol (Lausanne). 2019 Oct 11;10:697. doi: 10.3389/fendo.2019.00697. eCollection 2019.'}, {'pmid': '35124096', 'type': 'BACKGROUND', 'citation': 'Kumar M, Chen L, Tan K, Ang LT, Ho C, Wong G, Soh SE, Tan KH, Chan JKY, Godfrey KM, Chan SY, Chong MFF, Connolly JE, Chong YS, Eriksson JG, Feng M, Karnani N. Population-centric risk prediction modeling for gestational diabetes mellitus: A machine learning approach. Diabetes Res Clin Pract. 2022 Mar;185:109237. doi: 10.1016/j.diabres.2022.109237. Epub 2022 Feb 4.'}, {'pmid': '25273851', 'type': 'BACKGROUND', 'citation': 'Chong YS, Cai S, Lin H, Soh SE, Lee YS, Leow MK, Chan YH, Chen L, Holbrook JD, Tan KH, Rajadurai VS, Yeo GS, Kramer MS, Saw SM, Gluckman PD, Godfrey KM, Kwek K; GUSTO study group. Ethnic differences translate to inadequacy of high-risk screening for gestational diabetes mellitus in an Asian population: a cohort study. BMC Pregnancy Childbirth. 2014 Oct 2;14:345. doi: 10.1186/1471-2393-14-345.'}, {'pmid': '37144983', 'type': 'BACKGROUND', 'citation': 'Simmons D, Immanuel J, Hague WM, Teede H, Nolan CJ, Peek MJ, Flack JR, McLean M, Wong V, Hibbert E, Kautzky-Willer A, Harreiter J, Backman H, Gianatti E, Sweeting A, Mohan V, Enticott J, Cheung NW; TOBOGM Research Group. Treatment of Gestational Diabetes Mellitus Diagnosed Early in Pregnancy. N Engl J Med. 2023 Jun 8;388(23):2132-2144. doi: 10.1056/NEJMoa2214956. Epub 2023 May 5.'}, {'pmid': '34964875', 'type': 'BACKGROUND', 'citation': 'American Diabetes Association Professional Practice Committee. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022. Diabetes Care. 2022 Jan 1;45(Suppl 1):S17-S38. doi: 10.2337/dc22-S002.'}, {'pmid': '10691156', 'type': 'BACKGROUND', 'citation': "Griffin ME, Coffey M, Johnson H, Scanlon P, Foley M, Stronge J, O'Meara NM, Firth RG. Universal vs. risk factor-based screening for gestational diabetes mellitus: detection rates, gestation at diagnosis and outcome. Diabet Med. 2000 Jan;17(1):26-32. doi: 10.1046/j.1464-5491.2000.00214.x."}, {'pmid': '36750271', 'type': 'BACKGROUND', 'citation': 'Wicklow B, Retnakaran R. Gestational Diabetes Mellitus and Its Implications across the Life Span. Diabetes Metab J. 2023 May;47(3):333-344. doi: 10.4093/dmj.2022.0348. Epub 2023 Feb 8.'}, {'pmid': '32930949', 'type': 'BACKGROUND', 'citation': 'Pathirana MM, Lassi ZS, Ali A, Arstall MA, Roberts CT, Andraweera PH. Association between metabolic syndrome and gestational diabetes mellitus in women and their children: a systematic review and meta-analysis. Endocrine. 2021 Feb;71(2):310-320. doi: 10.1007/s12020-020-02492-1. Epub 2020 Sep 15.'}, {'pmid': '33658531', 'type': 'BACKGROUND', 'citation': 'Chen LW, Soh SE, Tint MT, Loy SL, Yap F, Tan KH, Lee YS, Shek LP, Godfrey KM, Gluckman PD, Eriksson JG, Chong YS, Chan SY. Combined analysis of gestational diabetes and maternal weight status from pre-pregnancy through post-delivery in future development of type 2 diabetes. Sci Rep. 2021 Mar 3;11(1):5021. doi: 10.1038/s41598-021-82789-x.'}, {'pmid': '33184151', 'type': 'BACKGROUND', 'citation': 'Yew TW, Chi C, Chan SY, van Dam RM, Whitton C, Lim CS, Foong PS, Fransisca W, Teoh CL, Chen J, Ho-Lim ST, Lim SL, Ong KW, Ong PH, Tai BC, Tai ES. A Randomized Controlled Trial to Evaluate the Effects of a Smartphone Application-Based Lifestyle Coaching Program on Gestational Weight Gain, Glycemic Control, and Maternal and Neonatal Outcomes in Women With Gestational Diabetes Mellitus: The SMART-GDM Study. Diabetes Care. 2021 Feb;44(2):456-463. doi: 10.2337/dc20-1216. Epub 2020 Nov 12.'}, {'pmid': '12423867', 'type': 'BACKGROUND', 'citation': 'Sanchez-Ramos L, Bernstein S, Kaunitz AM. Expectant management versus labor induction for suspected fetal macrosomia: a systematic review. Obstet Gynecol. 2002 Nov;100(5 Pt 1):997-1002.'}, {'pmid': '10796277', 'type': 'BACKGROUND', 'citation': 'Boulvain M, Stan C, Irion O. Elective delivery in diabetic pregnant women. Cochrane Database Syst Rev. 2000;2001(2):CD001997. doi: 10.1002/14651858.CD001997.'}, {'pmid': '29675432', 'type': 'BACKGROUND', 'citation': 'Nguyen CL, Pham NM, Binns CW, Duong DV, Lee AH. Prevalence of Gestational Diabetes Mellitus in Eastern and Southeastern Asia: A Systematic Review and Meta-Analysis. J Diabetes Res. 2018 Feb 20;2018:6536974. doi: 10.1155/2018/6536974. eCollection 2018.'}]}, 'descriptionModule': {'briefSummary': 'This new feasibility pilot study aims to refine the design and protocols for a larger trial that will investigate the potential benefits of early oral glucose tolerance test (OGTT) screening in a population traditionally defined as low-risk for development of gestational diabetes. The study will evaluate its potential effectiveness in reducing the risks of neonatal morbidity/mortality and obstetric complications. Additionally, a machine learning algorithm to predict gestational diabetes mellitus (GDM) risk based on routinely obtained clinical information at pregnancy booking, and minimally invasive methods, such as continuous glucose monitoring (CGM) and gingival crevicular fluid (GCF) sampling, are being explored to predict the risk of hyperglycaemia. This study aims to investigate the utility of early pregnancy screening to enable timely detection and management of early gestational diabetes development in a low-risk population, ultimately promoting better health outcomes for mothers and their babies.', 'detailedDescription': "The Early Screening for Gestational Diabetes Mellitus in a Low-Risk Population (EaGeR) pilot study aims to inform a future trial that would evaluate whether early oral glucose tolerance test (OGTT) screening can improve pregnancy and neonatal outcomes among low-risk pregnant women in Singapore, a country that has one of the highest global incidences of gestational diabetes mellitus (GDM). GDM is associated with higher risks of neonatal and obstetric complications in the short-term, and in the long-term increased cardiometabolic risks in both mothers and their children.\n\nThe current local GDM screening practice comprises universal screening of all pregnancies (without pre-existing diabetes) with an OGTT around 24-28 weeks' gestation, and only offering early pregnancy screening to women with traditional high-risk factors for GDM development. The issue is that around 70% of diagnosed GDM cases in Singapore do not possess traditional high-risk factors, and they could have been potentially picked up earlier in gestation, if screened. Conversely, many women identified as high-risk in early pregnancy show normal glucose concentrations in an OGTT when screened in early gestation and when re-screened at 24-28 weeks. This study builds on findings from previous trials, which showed that early screening and treatment of mild glucose intolerance in high-risk women can reduce neonatal complications. The EaGeR Trial seeks to determine whether similar benefits can be achieved in an apparently low-risk Asian population.\n\nThis pilot study will recruit 120 low-risk pregnant women before 16 weeks' gestation. All participants will undergo an early OGTT before 16 weeks' and be randomly assigned to one of two arms: the experimental arm, where early OGTT results are revealed and immediate follow-up actions taken if GDM is diagnosed using the WHO 2013 criteria, and the control arm, where early OGTT results are concealed, with follow-up in accordance with standard care involving the routine OGTT screen at 24-28 weeks' gestation.\n\nData will be collected from the medical records to evaluate the primary and secondary outcomes which include pregnancy and neonatal events, as well as infant measures. Additionally, maternal symptoms and biomarkers, infant anthropometry and breastfeeding will be evaluated. Outcomes will be compared between study arms.\n\nFurther, the study will also test the utility of a newly developed machine learning algorithm as a novel and non-invasive method which uses clinical factors available at pregnancy booking to assess individual risk for GDM development. It will also explore the utility of other minimally invasive methods of continuous glucose monitoring (CGM) and gingival crevicular fluid (GCF) sampling at an early stage of pregnancy, in predicting the risk of GDM development.\n\nThis initial pilot study will help to refine the design and protocols of the definitive EaGeR Trial which will eventually guide the development of the optimal screening strategy for GDM among low-risk pregnant women in Singapore for improved neonatal and obstetric outcomes."}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT'], 'maximumAge': '39 Years', 'minimumAge': '21 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Pregnant women aged 21-39 years at recruitment\n2. Singleton pregnancy\n3. Less than 16 weeks pregnant at recruitment\n4. Intend to receive antenatal care and give birth at the National University Hospital\n\nExclusion Criteria:\n\n1. Known pre-existing type 1 or type 2 diabetes mellitus at recruitment\n2. Classified as high-risk for GDM at pregnancy booking using the traditional checklist:\n\n 2.1) Age ≥40 years 2.2) Overweight/obese, i.e., body mass index (BMI) ≥25.0 kg/m2 2.3) First degree relative with diabetes mellitus 2.4) Previously delivered a baby ≥4 kg 2.5) Previously diagnosed with GDM 2.6) Impaired glucose tolerance (IGT) or impaired fasting glycaemia (IFG) on previous testing 2.7) Polycystic ovarian syndrome (PCOS) 2.8) Poor obstetric history (e.g. recurrent pregnancy loss, previous intrauterine death, congenital malformations) 2.9) History of chronic hypertension, hyperlipidaemia or cardiovascular disease 2.10) Glycosuria ≥ 2+ on urine dipstick\n3. Taking systemic steroid medication or metformin\n4. Participation in another intervention trial'}, 'identificationModule': {'nctId': 'NCT06704035', 'acronym': 'EaGeR', 'briefTitle': 'Early Screening for Gestational Diabetes Mellitus in a Low Risk Population', 'organization': {'class': 'OTHER', 'fullName': 'National University Hospital, Singapore'}, 'officialTitle': 'Early Screening for Gestational Diabetes Mellitus in a Low Risk Population', 'orgStudyIdInfo': {'id': '2023/00970'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Early OGTT Results Revealed', 'description': "The results of the early OGTT conducted before 16 weeks' gestation will be revealed to the participants. If the results indicate gestational diabetes mellitus (GDM) by the WHO 2013 criteria, immediate follow-up actions, including appropriate treatments, will be taken. Those with a normal result will undertake the universally offered routine OGTT at 24-28 weeks' gestation.", 'interventionNames': ['Diagnostic Test: Early OGTT Results Revealed']}, {'type': 'NO_INTERVENTION', 'label': 'Early OGTT Results Concealed', 'description': "Participants in this arm will undergo an early oral glucose tolerance test (OGTT) before 16 weeks' gestation, however, the results will be concealed from the participants and study investigators, and results will not be acted upon (unless they are suggestive of pre-existing type 2 diabetes mellitus as reviewed by an independent clinician, in which case appropriate follow-up will be arranged). All participants (except those with results suggestive of type 2 diabetes) will undertake the routine OGTT at 24-28 weeks' gestation, as per standard care."}], 'interventions': [{'name': 'Early OGTT Results Revealed', 'type': 'DIAGNOSTIC_TEST', 'description': "Early pregnancy screening with a three-time point (fasting, 1h, 2h) 75g oral glucose tolerance test before 16 weeks' gestation with plasma glucose results revealed to the patient and clinician for appropriate management of any diabetes (gestational and type 2, if diagnosed) from early pregnancy onwards.", 'armGroupLabels': ['Early OGTT Results Revealed']}]}, 'contactsLocationsModule': {'locations': [{'zip': '119228', 'city': 'Singapore', 'country': 'Singapore', 'contacts': [{'name': 'Gladys Woon, BSc', 'role': 'CONTACT', 'email': 'gladys_woon@nuhs.edu.sg', 'phone': '+65 6516 4134'}, {'name': 'Shiao-Yng Chan, MBBChir (UK), FRCOG (UK), PhD', 'role': 'PRINCIPAL_INVESTIGATOR'}, {'name': 'Karen Lim, MBBS, MRCOG, MMED, MSc', 'role': 'SUB_INVESTIGATOR'}], 'facility': 'National University Hospital', 'geoPoint': {'lat': 1.28967, 'lon': 103.85007}}], 'centralContacts': [{'name': 'Gladys Woon, BSc', 'role': 'CONTACT', 'email': 'gladys_woon@nuhs.edu.sg', 'phone': '+65 6516 4134'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'National University Hospital, Singapore', 'class': 'OTHER'}, 'collaborators': [{'name': 'National University of Singapore', 'class': 'OTHER'}, {'name': 'Agency for Science, Technology and Research', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}