Postprandial blood glucose prediction is a crucial part of diabetes management. Recently, this topic has been of great interest, resulting in many research projects and published papers. Although different input parameters that might be beneficial for blood glucose prediction models were comprehensively discussed, specific data preprocessing, feature engineering and model tuning steps were not explained in detail in many of these papers. In this work, we developed and comprehensively described a data-driven blood glucose model based on a decision tree gradient boosting algorithm to predict different characteristics of postprandial glycemic responses; the model utilized meal-related data derived from a mobile app diary (including information on the glycemic index), food context (information on previous meals), characteristics of the individual patients and patient behavioral questionnaires. A set of rules was defined and implemented to detect incorrect meal records and to filter faulty data, and analyses were conducted on the overall food diary data and in particular, the data on the current meal for which the postprandial blood glucose response was calculated. Different gradient boosting models were trained and evaluated with parameters selected via random search cross-validation. The best models for the prediction of the incremental area under the blood glucose curve two hours after food intake had the following characteristics: R=0.631, MAE=0.373 mmol/L*h for the model not using data on current blood glucose; R=0.644, MAE=0.371 mmol/L*h for the model using data on the current blood glucose levels; and R=0.704, MAE=0.341 mmol/L*h for the model utilizing data on the continuous blood glucose trends before the meal. The impact of features was evaluated using Shapley values. The meal glycemic load, amount of carbohydrates in the meal, type of meal (e.g., breakfast), amount of starch and amount of food consumed 6 hours before the current meal were the most important contributors in the models.

Context: Interpretation of thyroid function tests during pregnancy is limited by the generalizability of reference intervals between cohorts due to inconsistent methodology. Objective: (1) To provide an overview of published reference intervals for thyrotropin (TSH) and free thyroxine (FT4) in pregnancy, (2) to assess the consequences of common methodological between-study differences by combining raw data from different cohorts. Methods: (1) Ovid MEDLINE, EMBASE, and Web of Science were searched until December 12, 2021. Studies were assessed in duplicate. (2) The individual participant data (IPD) meta-analysis was performed in participating cohorts in the Consortium on Thyroid and Pregnancy. Results: (1) Large between-study methodological differences were identified, 11 of 102 included studies were in accordance with current guidelines; (2) 22 cohorts involving 63 198 participants were included in the meta-analysis. Not excluding thyroid peroxidase antibody–positive participants led to a rise in the upper limits of TSH in all cohorts, especially in the first (mean +17.4%; range +1.6 to +30.3%) and second trimester (mean +9.8%; range +0.6 to +32.3%). The use of the 95th percentile led to considerable changes in upper limits, varying from –10.8% to –21.8% for TSH and –1.2% to –13.2% for FT4. All other additional exclusion criteria changed reference interval cut-offs by a maximum of 3.5%. Applying these findings to the 102 studies included in the systematic review, 48 studies could be used in a clinical setting. Conclusion: We provide an overview of clinically relevant reference intervals for TSH and FT4 in pregnancy. The results of the meta-analysis indicate that future studies can adopt a simplified study setup without additional exclusion criteria.

The incorporation of glycemic index (GI) and glycemic load (GL) is a promising way to improve the accuracy of postprandial glycemic response (PPGR) prediction for personalized treatment of gestational diabetes (GDM). Our aim was to assess the prediction accuracy for PPGR prediction models with and without GI data in women with GDM and healthy pregnant women. The GI values were sourced from University of Sydney’s database and assigned to a food database used in the mobile app DiaCompanion. Weekly continuous glucose monitoring (CGM) data for 124 pregnant women (90 GDM and 34 control) were analyzed together with records of 1489 food intakes. Pearson correlation (R) was used to quantify the accuracy of predicted PPGRs from the model relative to those obtained from CGM. The final model for incremental area under glucose curve (iAUC120) prediction chosen by stepwise multiple linear regression had an R of 0.705 when GI/GL was included among input variables and an R of 0.700 when GI/GL was not included. In linear regression with coefficients acquired using regularization methods, which was tested on the data of new patients, R was 0.584 for both models (with and without inclusion of GI/GL). In conclusion, the incorporation of GI and GL only slightly improved the accuracy of PPGR prediction models when used in remote monitoring.

Several meta-analyses found an association between low maternal serum 25-hydroxyvitamin D (25(OH)D) level and gestational diabetes mellitus (GDM). However, some of them reported significant heterogeneity. We examined the association of serum 25(OH)D concentration measured in the first and in the second halves of pregnancy with the development of GDM in Russian women surveyed in the periods of 2012–2014 and 2018–2021. We conducted a case–control study (including 318 pregnant women) nested on two previous studies. In 2012–2014, a total of 214 women (83 GDM and 131 controls) were enrolled before 15 weeks of gestation and maternal serum 25(OH)D concentrations were measured twice: at 8th–14th week of gestation and simultaneously with two-hour 75 g oral glucose tolerance test (OGTT) at 24th–32nd week of gestation. In the period of 2018–2021, 104 women (56 GDM and 48 controls) were included after OGTT and 25(OH)D concentrations were measured at 24th–32nd week of gestation. Median 25(OH)D levels were 20.0 [15.1–25.7] vs. 20.5 [14.5–27.5] ng/mL (p = 0.565) in GDM and control group in the first half of pregnancy and 25.3 [19.8–33.0] vs. 26.7 [20.8–36.8] ng/mL (p = 0.471) in the second half of pregnancy, respectively. The prevalence rates for vitamin D deficiency (25(OH)D levels < 20 ng/mL) were 49.4% and 45.8% (p = 0.608) in the first half of pregnancy and 26.2% vs. 22.1% (p = 0.516) in the second half of pregnancy in women who developed GDM and in women without GDM, respectively. The frequency of vitamin D supplements intake during pregnancy increased in 2018–2021 compared to 2012–2014 (p = 0.001). However, the third trimester 25(OH)D levels and prevalence of vitamin D deficiency (25.5 vs. 23.1, p = 0.744) did not differ in women examined in the periods of 2012–2014 and 2018–2021. To conclude, there was no association between gestational diabetes risk and maternal 25(OH)D measured both in the first and in the second halves of pregnancy. The increased prevalence of vitamin D supplements intake during pregnancy by 2018–2021 did not lead to higher levels of 25(OH)D.

Background. Subclinical hypothyroidism during pregnancy and gestational diabetes mellitus (GDM) is known to be associated with maternal and child morbidity. The concept of subclinical dysfunction of the thyroid gland in pregnant women depends on the population-specific and trimester-specific reference values so fixed universal cutoff concentrations for thyroid-stimulating hormone (TSH) that were recommended earlier now are put under the question. Population-specific and trimester-specific reference values have not been defined for pregnant women residing in Saint Petersburg. The data concerning the association of maternal thyroid status with GDM development are controversial. Aims. The aim of the study was to determine the reference values of TSH and free thyroxin (fT4) in the first trimester of pregnancy in women living in St. Petersburg, and to assess the relationship between thyroid status and the risk of subsequent development of GDM. Materials and methods. The levels of TSH, fT4 and thyroid peroxidase antibodies (TPO-Ab) were analyzed in 503 pregnant women before the 14th week of gestation. The women underwent oral glucose tolerance test (OGTT) at 2428 weeks to find out those with GDM. The association between thyroid function, thyroid autoimmunity and the risk of GDM we estimated. Results. The reference values for TSH were 0.07 4.40 mU /L, and for fT4 11.7 20.3 pmol/L. The prevalence of subclinical hypothyroidism in the 503 pregnant women was 16.9% according to the diagnostic criteria of TSH 2.5 mIU / L and 3.8% using our calculated reference interval. Hypothyroxinemia was registered in 5,3% using reference values recommended by diagnostic tests manufacturer and in 2,8% according to our calculated reference interval for fT4. GDM was diagnosed in 23% of women. Logistic regression analysis showed associations of hypothyroxinemia and TPO-Ab-positivity with the increased risk of GDM that remained significant after adjustments on age and body mass index (BMI) [adjusted OR (95% CI) = 7.39 (1.2742.93) for hypothyroxinemia, p=0.026; and adjusted OR (95% CI) = 2.02 (1.014.04) for TPO-Ab-positivity, p=0.047). Conclusions. Reference intervals for first trimester TSH and fT4 have been established for pregnant women living in St. Petersburg. Hypothyroxinemia and TPO-Ab-positivity were associated with the increased risk of GDM.

Obesity and type 2 diabetes mellitus (T2DM) are often combined and pathologically affect many tissues due to changes in circulating bioactive molecules. In this work, we evaluated the effect of blood plasma from obese (OB) patients or from obese patients comorbid with diabetes (OBD) on skeletal muscle function and metabolic state. We employed the mouse myoblasts C2C12 differentiation model to test the regulatory effect of plasma exposure at several levels: (1) cell morphology; (2) functional activity of mitochondria; (3) expression levels of several mitochondria regulators, i.e., Atgl, Pgc1b, and miR-378a-3p. Existing databases were used to computationally predict and analyze mir-378a-3p potential targets. We show that short-term exposure to OB or OBD patients’ plasma is sufficient to affect C2C12 properties. In fact, the expression of genes that regulate skeletal muscle differentiation and growth was downregulated in both OB- and OBD-treated cells, maximal mitochondrial respiration rate was downregulated in the OBD group, while in the OB group, a metabolic switch to glycolysis was detected. These alterations correlated with a decrease in ATGL and Pgc1b expression in the OB group and with an increase of miR-378a-3p levels in the OBD group.