Gestational Diabetes Mellitus (GDM)NCT07499622
Digital Health Intervention for Early Identification and Prevention of Gestational Diabetes Mellitus
A study testing Digital Health Lifestyle Intervention in people with Gestational Diabetes Mellitus (GDM), run by Peking University at 2 sites in China.
Trial summary
This study aims to develop and evaluate an early risk identification and digital health intervention strategy for gestational diabetes mellitus (GDM) among pregnant women in China. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Gestational Diabetes Mellitus (GDM)
- What is being tested?
- Digital Health Lifestyle Intervention
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,200 participants
- Where
- 2 sitesChina
- Study dates
- Jun 2026to Dec 2028
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Pregnant women in early pregnancy (within 13 weeks and 6 days of gestation)
- Planned delivery at a participating study hospital
- Age 18 years or older
- Singleton pregnancy
- Identified as high risk for gestational diabetes mellitus by the study risk assessment model
- Willing and able to provide informed consent
Who cannot join
- • Pre-pregnancy diabetes mellitus or overt diabetes diagnosed at the first antenatal visit (fasting blood glucose greater than or equal to 7.0 mmol/L)
- Pre-existing hypertension, autoimmune disease, major infection, or severe liver or kidney disease
- Use of medications that affect glucose metabolism, such as corticosteroids or metformin
- Severe psychiatric disorders
- Inability or unwillingness to comply with study procedures
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
China2 sites
Beijing Tongzhou Maternal and Child Health Hospital
Beijing, Beijing Municipality, 10010
Tao Su, PhD, +86 18605021872, 18605021872@163.com
Weifang Maternal and Child Health Hospital
Weifang, Shandong, 261042
Xiansheng Ding, +86 0536-5919002, 2411210109@stu.pku.edu.cn
About this study
Official title: A Multicenter Randomized Controlled Trial of a Digital Health Intervention for Risk Identification, Intelligent Early Warning, and Prevention of Gestational Diabetes Mellitus Based on Multi-Source Data Integration
This study aims to develop and evaluate an early risk identification and digital health intervention strategy for gestational diabetes mellitus (GDM) among pregnant women in China. Gestational diabetes mellitus is a common pregnancy complication associated with adverse maternal and neonatal outcomes, including excessive gestational weight gain, macrosomia, cesarean delivery, and increased long-term risk of metabolic disorders in both mothers and offspring.
The study includes two components. First, retrospective multi-source clinical data from maternal health records will be used to develop and validate a risk prediction model for early identification of pregnant women at high risk of GDM. Second, pregnant women identified as high risk in early pregnancy will be enrolled in a multicenter randomized controlled trial and assigned to either a digital health intervention group or a usual care group. The intervention includes online health education, individualized lifestyle guidance, behavioral self-management tools, and interactive consultation through a digital platform. The primary outcome is the incidence of GDM diagnosed during pregnancy. Secondary outcomes include gestational weight gain, cesarean delivery, macrosomia, and other maternal and neonatal outcomes.
This study is expected to provide evidence for improving early risk assessment, intelligent warning, and prevention strategies for GDM in the context of maternal health management in China.
Read the detailed description
Gestational diabetes mellitus (GDM) has become an increasingly important public health problem among pregnant women in China. GDM is associated with short-term adverse pregnancy outcomes and long-term health risks for both mothers and their offspring. Current routine screening for GDM is mainly based on oral glucose tolerance testing performed at 24 to 28 weeks of gestation, which may miss the optimal window for earlier risk identification and preventive intervention.
This study is designed to improve early identification and prevention of GDM through multi-source data integration and digital health intervention. The study is conducted in the context of maternal health management in China and includes a retrospective model development phase and a prospective randomized controlled trial phase.
In the model development phase, retrospective clinical data from maternal health information systems, including demographic characteristics, obstetric history, physical examination records, laboratory indicators, and pregnancy follow-up data, will be used to identify predictors of GDM and to construct an early risk prediction model. Statistical and machine learning methods, including random forest and other predictive modeling approaches, will be used to evaluate model performance and optimize discrimination, calibration, robustness, and interpretability.
In the intervention phase, pregnant women in early pregnancy who are identified as being at high risk for GDM will be recruited from participating maternal and child health hospitals and randomly assigned in a 1:1 ratio to either a digital health intervention group or a usual care group. Participants in the intervention group will receive additional support through a digital platform, including structured health education, individualized recommendations on diet, physical activity, gestational weight management, and sleep, as well as online consultation and self-management tools. Participants in the control group will receive routine antenatal care and standard health education materials.
Follow-up will be conducted during pregnancy and at delivery. The primary outcome is the incidence of GDM diagnosed according to routine clinical criteria during pregnancy. Secondary outcomes include gestational weight gain, cesarean delivery, macrosomia, and selected maternal and neonatal outcomes. Safety monitoring will focus on possible adverse events related to lifestyle intervention, such as hypoglycemic symptoms or other discomforts.
The findings of this study may help optimize strategies for early risk assessment, intelligent warning, and intervention for GDM, and may contribute to maternal and child health policy and practice in China.
- Conditions
- Gestational Diabetes Mellitus (GDM)
- Being tested
- Digital Health Lifestyle Intervention
- Medical subject headings
- Diabetes, Gestational
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Digital Health Lifestyle InterventionBehavioural
Participants receive a digital health lifestyle intervention in addition to routine antenatal care. The intervention is delivered through a digital platform and includes online health education, individualized lifestyle guidance, self-management tools, health information delivery, and interactive consultation. The intervention focuses on gestational weight management, diet, physical activity, sleep, and early prevention of gestational diabetes mellitus among pregnant women identified as high risk.
| Study group | Role | What they receive |
|---|---|---|
| Digital Health Intervention | Experimental | Participants in this arm will receive a digital health intervention in addition to routine antenatal care. The intervention includes online health education, individualized lifestyle guidance, self-management tools, health information delivery, and interactive consultation through a digital platform. The intervention focuses on gestational weight management, diet, physical activity, sleep, and prevention of gestational diabetes mellitus. Receives: Behavioral: Digital Health Lifestyle Intervention |
| Usual Care | No intervention | Participants in this arm will receive routine antenatal care and standard pregnancy health education provided by the hospital, without additional digital health intervention. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Incidence of Gestational Diabetes Mellitus
Gestational diabetes mellitus diagnosed during pregnancy according to routine oral glucose tolerance testing and the IADPSG/WHO diagnostic criteria used at participating hospitals.
Measured: At 24 to 28 weeks of gestation
Secondary outcomes (3)
Gestational Weight Gain
Total gestational weight gain during pregnancy based on routine antenatal records.
Measured: From enrollment to delivery
Cesarean Delivery
Mode of delivery recorded from hospital medical records.
Measured: At delivery
Macrosomia
Occurrence of macrosomia recorded in delivery records.
Measured: At delivery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Mar 2026
- Study startJun 2026 (estimated)
- Primary completionJun 2028 (estimated)
- Study completionDec 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Gestational Diabetes Mellitus (GDM)Studies of the same condition, open and under way.
- More trials run by Peking UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Participants identified as high risk for gestational diabetes mellitus in early pregnancy will be randomly assigned in a 1:1 ratio to either a digital health intervention group or a usual care group and followed through pregnancy and delivery.
- Masking
- None (open label)
- Enrolment
- 1,200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Peking University
- Sponsor type
- University, hospital or other
- Collaborators
- National Natural Science Foundation of China
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07499622
- Sponsor's protocol ID
- PKUGDM-2026
- Status last verified
- Mar 2026
- First submitted
- 24 Mar 2026
- Last updated
- 30 Mar 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be made publicly available because the study involves sensitive personal and health information from pregnant women, and data sharing is restricted by ethical approval, informed consent, and institutional data protection policies.
Publications
Artzi NS, Shilo S, Hadar E, Rossman H, Barbash-Hazan S, Ben-Haroush A, Balicer RD, Feldman B, Wiznitzer A, Segal E. Prediction of gestational diabetes based on nationwide electronic health records. Nat Med. 2020 Jan;26(1):71-76. doi: 10.1038/s41591-019-0724-8. Epub 2020 Jan 13.
PubMed 31932807Allotey J, Coomar D, Ensor J, Ruiz-Calvo G, Boath A, Ogwulu CO, Monahan M, Kabeya V, Zheng M, McNeill R, Meacham H, Mahmoud G, Simpson SA, Hitman GA, Nirantharakumar K, Heslehurst N, Pelaez M, Tonstad S, Yeo S, Cecatti JG, Facchinetti F, Motahari-Tabari NS, Renault KM, Guelfi KJ, Jensen DM, Harrison C, Khomami MB, Calle-Pascual AL, McAuliffe FM, Hauner H, Barakat R, Geiker NRW, Vinter CA, Phelan S, Kinnunen TI, Kothari A, Teede H, Poston L, Betran AP, Moss N, Iliodromiti S, Austin F, Roberts T, Zamora J, Riley RD, Thangaratinam S; i-WIP Collaborative Group. Effects of lifestyle interventions in pregnancy on gestational diabetes: individual participant data and network meta-analysis. BMJ. 2026 Jan 6;392:e084159. doi: 10.1136/bmj-2025-084159.
PubMed 41494781
Study at a glance
From the registry record, last updated by the sponsor on 30 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Multicenter Randomized Controlled Trial of a Digital Health Intervention for Risk Identification, Intelligent Early Warning, and Prevention of Gestational Diabetes Mellitus Based on Multi-Source Data Integration
- ClinicalTrials.gov ID
- NCT07499622
- Acronym / sponsor ID
- PKUGDM-2026
- Conditions
- Gestational Diabetes Mellitus (GDM)
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,200 participants (estimated)
- Lead sponsor
- Peking UniversityUniversity, hospital or other
- Collaborators
- National Natural Science Foundation of China
- Study start
- Jun 2026 (estimated)
- Primary completion
- Jun 2028 (estimated)
- Study completion
- Dec 2028 (estimated)
- First posted
- 30 Mar 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study aims to develop and evaluate an early risk identification and digital health intervention strategy for gestational diabetes mellitus (GDM) among pregnant women in China. Gestational diabetes mellitus is a common pregnancy complication associated with adverse maternal and neonatal outcomes, including excessive gestational weight gain, macrosomia, cesarean delivery, and increased long-term risk of metabolic disorders in both mothers and offspring.
The study includes two components. First, retrospective multi-source clinical data from maternal health records will be used to develop and validate a risk prediction model for early identification of pregnant women at high risk of GDM. Second, pregnant women identified as high risk in early pregnancy will be enrolled in a multicenter randomized controlled trial and assigned to either a digital health intervention group or a usual care group. The intervention includes online health education, individualized lifestyle guidance, behavioral self-management tools, and interactive consultation through a digital platform. The primary outcome is the incidence of GDM diagnosed during pregnancy. Secondary outcomes include gestational weight gain, cesarean delivery, macrosomia, and other maternal and neonatal outcomes.
This study is expected to provide evidence for improving early risk assessment, intelligent warning, and prevention strategies for GDM in the context of maternal health management in China.
Detailed description
Gestational diabetes mellitus (GDM) has become an increasingly important public health problem among pregnant women in China. GDM is associated with short-term adverse pregnancy outcomes and long-term health risks for both mothers and their offspring. Current routine screening for GDM is mainly based on oral glucose tolerance testing performed at 24 to 28 weeks of gestation, which may miss the optimal window for earlier risk identification and preventive intervention.
This study is designed to improve early identification and prevention of GDM through multi-source data integration and digital health intervention. The study is conducted in the context of maternal health management in China and includes a retrospective model development phase and a prospective randomized controlled trial phase.
In the model development phase, retrospective clinical data from maternal health information systems, including demographic characteristics, obstetric history, physical examination records, laboratory indicators, and pregnancy follow-up data, will be used to identify predictors of GDM and to construct an early risk prediction model. Statistical and machine learning methods, including random forest and other predictive modeling approaches, will be used to evaluate model performance and optimize discrimination, calibration, robustness, and interpretability.
In the intervention phase, pregnant women in early pregnancy who are identified as being at high risk for GDM will be recruited from participating maternal and child health hospitals and randomly assigned in a 1:1 ratio to either a digital health intervention group or a usual care group. Participants in the intervention group will receive additional support through a digital platform, including structured health education, individualized recommendations on diet, physical activity, gestational weight management, and sleep, as well as online consultation and self-management tools. Participants in the control group will receive routine antenatal care and standard health education materials.
Follow-up will be conducted during pregnancy and at delivery. The primary outcome is the incidence of GDM diagnosed according to routine clinical criteria during pregnancy. Secondary outcomes include gestational weight gain, cesarean delivery, macrosomia, and selected maternal and neonatal outcomes. Safety monitoring will focus on possible adverse events related to lifestyle intervention, such as hypoglycemic symptoms or other discomforts.
The findings of this study may help optimize strategies for early risk assessment, intelligent warning, and intervention for GDM, and may contribute to maternal and child health policy and practice in China.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Participants identified as high risk for gestational diabetes mellitus in early pregnancy will be randomly assigned in a 1:1 ratio to either a digital health intervention group or a usual care group and followed through pregnancy and delivery.
| Arm | Type | Receives |
|---|---|---|
| Digital Health Intervention | Experimental | Behavioral: Digital Health Lifestyle InterventionParticipants in this arm will receive a digital health intervention in addition to routine antenatal care. The intervention includes online health education, individualized lifestyle guidance, self-management tools, health information delivery, and interactive consultation through a digital platform. The intervention focuses on gestational weight management, diet, physical activity, sleep, and prevention of gestational diabetes mellitus. |
| Usual Care | No intervention | –Participants in this arm will receive routine antenatal care and standard pregnancy health education provided by the hospital, without additional digital health intervention. |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Pregnant women in early pregnancy (within 13 weeks and 6 days of gestation)
- Planned delivery at a participating study hospital
- Age 18 years or older
- Singleton pregnancy
- Identified as high risk for gestational diabetes mellitus by the study risk assessment model
Key exclusion criteria (5 listed)
- • Pre-pregnancy diabetes mellitus or overt diabetes diagnosed at the first antenatal visit (fasting blood glucose greater than or equal to 7.0 mmol/L)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Digital Health Lifestyle InterventionParticipants receive a digital health lifestyle intervention in addition to routine antenatal care. The intervention is delivered through a digital platform and includes online health education, individualized lifestyle guidance, self-management tools, health information delivery, and interactive consultation. The intervention focuses on gestational weight management, diet, physical activity, sleep, and early prevention of gestational diabetes mellitus among pregnant women identified as high risk. | Behavioural | Digital Health Intervention |
Primary outcome
Incidence of Gestational Diabetes Mellitus
Time frame: At 24 to 28 weeks of gestation
Gestational diabetes mellitus diagnosed during pregnancy according to routine oral glucose tolerance testing and the IADPSG/WHO diagnostic criteria used at participating hospitals.
3 secondary outcomes
Gestational Weight Gain
Time frame: From enrollment to delivery
Cesarean Delivery
Time frame: At delivery
Macrosomia
Time frame: At delivery
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Mar 2026.
- Results publication: PubMed 31932807Artzi NS, Shilo S, Hadar E, Rossman H, Barbash-Hazan S, Ben-Haroush A, Balicer RD, Feldman B, Wiznitzer A, Segal E. Prediction of gestational diabetes based on nationwide electronic health records. Nat Med. 2020 Jan;26(1):71-76. doi: 10.1038/s41591-019-0724-8. Epub 2020 Jan 13.
- Results publication: PubMed 41494781Allotey J, Coomar D, Ensor J, Ruiz-Calvo G, Boath A, Ogwulu CO, Monahan M, Kabeya V, Zheng M, McNeill R, Meacham H, Mahmoud G, Simpson SA, Hitman GA, Nirantharakumar K, Heslehurst N, Pelaez M, Tonstad S, Yeo S, Cecatti JG, Facchinetti F, Motahari-Tabari NS, Renault KM, Guelfi KJ, Jensen DM, Harrison C, Khomami MB, Calle-Pascual AL, McAuliffe FM, Hauner H, Barakat R, Geiker NRW, Vinter CA, Phelan S, Kinnunen TI, Kothari A, Teede H, Poston L, Betran AP, Moss N, Iliodromiti S, Austin F, Roberts T, Zamora J, Riley RD, Thangaratinam S; i-WIP Collaborative Group. Effects of lifestyle interventions in pregnancy on gestational diabetes: individual participant data and network meta-analysis. BMJ. 2026 Jan 6;392:e084159. doi: 10.1136/bmj-2025-084159.
- Individual participant dataSharing planned: No. Individual participant data will not be made publicly available because the study involves sensitive personal and health information from pregnant women, and data sharing is restricted by ethical approval, informed consent, and institutional data protection policies.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Digital Health Lifestyle Intervention in people with Gestational Diabetes Mellitus (GDM), run by Peking University at 2 sites in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 30 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Jue Liu, PhD (+86 13426455743, jueliu@bjmu.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Incidence of Gestational Diabetes Mellitus (time frame: At 24 to 28 weeks of gestation). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07499622, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 30 Mar 2026.