Skip to content

Digitalized Management Exploration for Gestational Diabetes Mellitus in China

Comparison of Conventional Mode and Combined Digitalized Mode of Management for Gestational Diabetes Mellitus in China

Status
UNKNOWN
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05003154
Enrollment
46
Registered
2021-08-12
Start date
2021-09-30
Completion date
2024-08-31
Last updated
2021-08-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gestational Diabetes Mellitus in Pregnancy

Brief summary

Gestational diabetes mellitus (GDM) can lead to adverse perinatal and long-term outcomes, and it is so important to manage this disease in pregnancy. Digitalized managements have been proved economical and effective in some chronic diseases like type II diabetes mellitus. The purpose of the current study was to develop and evaluate a digitalized mode for GDM management using mobile healthcare and some wearable devices. Subjects were randomly divided into a conventional management group and combined digitalized management group after diagnosed with GDM during 24-28 weeks of gestation. The conventional mangement group received conventional GDM management and could freely use the mobile healthcare application. The mobile management group received digitalized healthcare services from artificial intelligence under the supervision of obstetricians, in addition to conventional management. The effectiveness of digitalized management were evaluated mainly through the result values of the labotatory tests related to blood glucose controlling and perinatal outcomes.

Interventions

OTHERDigitalized management

In addition to conventional management, Patients also receive digitalized management, which provides personalized guidance in diet, excercise, prenatal visit, blood glucose monitoring,etc., from artificail intelliegence (AI) supevised by obstetricians, through a smartphone application and some werable devices (like sports bracelet). The pivotal AI are based on clinical experience from obstetricians, therapeutic principle from official Guidelines and abundant data in previous work, and it will works under strict supervision.

Sponsors

Hangzhou Jianhai Technology Company Limited
CollaboratorUNKNOWN
Quzhou Maternal and Child Health Care Hospital
CollaboratorUNKNOWN
Women's Hospital School Of Medicine Zhejiang University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE

Eligibility

Sex/Gender
FEMALE
Age
18 Years to 45 Years
Healthy volunteers
No

Inclusion criteria

1. The age of 18-45 years, single pregnancy, Han nationality; 2. GDM diagnosed between 24 to 28 weeks of gestation, either of the following: fasting plasma glucose ≥5.1 mmol/L, 60-minute plasma glucose ≥10.0 mmol/L, 120-minute plasma glucose ≥8.5 mmol/L, during a 75g oral glucose tolerance test (OGTT). 3. Plan to deliver the baby in Women's Hospital School Of Medicine Zhejiang University; 4. Can operate mobile phones and related software; 5. Voluntary participation in this study; 6. Education background: junior high school or above.

Exclusion criteria

1. Type I or II or other non GDM diabetes mellitus; 2. Severe pregnancy complications or complications: such as malignant tumor, preeclampsia, severe intrahepatic cholestasis of pregnancy syndrome, pregnancy with antiphospholipid antibody syndrome, severe anemia (hemoglobin\<90g/L, etc.), cardiac insufficiency cardiovascular disease (such as myocardial infarction, heart failure, pulmonary hypertension, stroke history, coronary heart disease, valvular heart disease, etc.), stroke (moderate), liver disease (such as hepatic insufficiency, acute viral hepatitis, etc.), lung disease (such as restrictive lung disease, emphysema, liver cirrhosis, pulmonary heart disease, etc.), kidney disease (such as nephrotic syndrome, chronic nephritis, renal insufficiency, etc.), chronic hypertension, thyroid disease (such as hyperthyroidism, hypothyroidism, thyroiditis, etc.), other endocrine diseases (such as Cushing's syndrome Acromegaly, venous or arterial thromboembolic diseases, rheumatic immune diseases, etc; 3. The combined conditions that may affect the diet exercise therapy include severe food allergy, dyskinesia (physical disability), history of bariatric surgery, major gastrointestinal diseases (such as gastrointestinal bleeding, inflammatory bowel disease, gastrointestinal tumor, active stage of peptic ulcer, chronic intestinal obstruction, etc.), restrictive lung disease, history of two or more adverse abortions, placenta previa, repeated and persistent bleeding threatened abortion, threatened premature birth, hyperemesis gravidarum, vegetarians, etc; 4. Other conditions: such as mental disorders, cervical incompetence, genital tract deformity, etc; 5. Patients who are taking medicine that may affect glucose metabolism, such as ritodrine, prednisone, etc; 6. Patients who are participating in other clinical studies; 7. The researchers believe patients who are not suitable for this study

Design outcomes

Primary

MeasureTime frameDescription
Concentration of glycosylated hemoglobin A1c37-42 weeks of gestationReflecting the average glucose level in the last 8-12 weeks

Secondary

MeasureTime frameDescription
Rate of neonate large for gestational ageAt the 1 day of deliveryMay reflecting maternal glucose level in pregnancy
rate of caesarean as the delivery modeAt the 1 day of deliveryAn indicator associated with fetal weight or perinatal condition
Hospitalization cost of neonate and puerperae for deliveryAt the 1 day discharging from hospitalA health economic indicator
Proportion of patients with abnormal resulets of postnatal oral glucose tolerance test42 days postpartumReflecting postpartum glucose metabolism

Countries

China

Contacts

Primary ContactDanqing Chen, PhD
chendq@zju.edu.cn+860571-87061501
Backup ContactMenglin Zhou, MD
marlin_zhou@zju.edu.cn+8613738008135

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 5, 2026