Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters










Database
Language
Publication year range
1.
Front Endocrinol (Lausanne) ; 14: 1168688, 2023.
Article in English | MEDLINE | ID: mdl-37361536

ABSTRACT

Background: Gestational diabetes mellitus (GDM) is a common complication of pregnancy associated with serious adverse outcomes for mothers and their offspring. Achieving glycaemic targets is the mainstream in the treatment of GDM in order to improve pregnancy outcomes. As GDM is usually diagnosed in the third trimester of pregnancy, the time frame for the intervention is very narrow. Women need to get new knowledge and change their diet very quickly. Usually, these patients require additional frequent visits to healthcare professionals. Recommender systems based on artificial intelligence could partially substitute healthcare professionals in the process of educating and controlling women with GDM, thus reducing the burden on the women and healthcare systems. We have developed a mobile-based personalized recommendation system DiaCompanion I with data-driven real time personal recommendations focused primarily on postprandial glycaemic response prediction. The study aims to clarify the effect of using DiaCompanion I on glycaemic levels and pregnancy outcomes in women with GDM. Methods: Women with GDM are randomized to 2 treatment groups: utilizing and not utilizing DiaCompanion I. The app provides women in the intervention group the resulting data-driven prognosis of 1-hour postprandial glucose level every time they input their meal data. Based on the predicted glucose level, they can adjust their current meal so that the predicted glucose level falls within the recommended range below 7 mmol/L. The app also provides reminders and recommendations on diet and lifestyle to the participants of the intervention group. All the participants are required to perform 6 blood glucose measurements a day. Capillary glucose values are retrieved from the glucose meter and if not available, from the woman's diary. Additionally, data on glycaemic levels during the study and consumption of major macro- and micronutrients will be collected using the mobile app with electronic report forms in the intervention group. Women from the control group receive standard care without the mobile app. All participants are prescribed with insulin therapy if needed and modifications in their lifestyle. A total of 216 women will be recruited. The primary outcome is the percentage of postprandial capillary glucose values above target (>7.0 mmol/L). Secondary outcomes include the percentage of patients requiring insulin therapy during pregnancy, maternal and neonatal outcomes, glycaemic control using glycated hemoglobin (HbA1c), continuous glucose monitoring data and other blood glucose metrics, the number of patient visits to endocrinologists and acceptance/satisfaction of the two strategies assessed using a questionnaire. Discussion: We believe that the approach including DiaCompanion I will be more effective in patients with GDM for improving glycaemic levels and pregnancy outcomes. We also expect that the use of the app will help reduce the number of clinic visits. Trial registration number: ClinicalTrials.gov, Identifier NCT05179798.


Subject(s)
Diabetes, Gestational , Pregnancy , Infant, Newborn , Female , Humans , Blood Glucose , Blood Glucose Self-Monitoring , Artificial Intelligence , Diet , Insulin , Randomized Controlled Trials as Topic
2.
Clin Chem Lab Med ; 43(11): 1223-6, 2005.
Article in English | MEDLINE | ID: mdl-16232090

ABSTRACT

Undiagnosed thyroid disease is a common problem with significant public health implications. This is especially true during pregnancy, when the health of both the mother and the developing child can be adversely affected by abnormal maternal thyroid function. Measurement of serum thyroid stimulating hormone (TSH) and thyroid peroxidase antibodies (TPO-Ab) are two common ways to assess maternal thyroid status. The objective of our study was to determine the prevalence of abnormal TSH and TPO-Ab tests in a population of pregnant women in the Samara region of the Russian Federation. Serum samples were obtained from 1588 pregnant women as part of their routine antenatal care. TSH and TPO-Ab were measured, and trimester-specific reference values for TSH (2.5-97.5 percentiles) were calculated using TPO-Ab-negative women. TSH results outside these ranges were considered abnormal; TPO-Ab levels outside the manufacturer's reference range (>12 IU/mL) were considered abnormal. Overall, the prevalence of abnormal results was 6.3% for TSH and 10.7% for TPO-Ab. High TSH (>97.5 trimester-specific percentile) and TPO-Ab-positive results were most common in the first trimester (5.7% and 13.8%, respectively). TSH levels were associated with gestational age and TPO-Ab status, and with maternal age in TPO-Ab-negative women. TPO-Ab status was associated with both maternal and gestational age. Women with TSH >2.5 mIU/L had a significantly increased risk of being TPO-Ab-positive, and this risk increased with age. Based on our data, we conclude that abnormal TSH and TPO-Ab are common in pregnant women of the Samara region. Given the association of thyroid dysfunction to adverse pregnancy outcomes, screening of this population for abnormal thyroid function should be considered.


Subject(s)
Antibodies/immunology , Iodide Peroxidase/analysis , Iodide Peroxidase/immunology , Thyroid Diseases/diagnosis , Thyrotropin/blood , Adolescent , Adult , Aging , Female , Humans , Middle Aged , Pregnancy , Pregnancy Complications/diagnosis , Pregnancy Complications/enzymology , Pregnancy Complications/immunology , Russia , Thyroid Diseases/enzymology , Thyroid Diseases/immunology
SELECTION OF CITATIONS
SEARCH DETAIL
...