BACKGROUND/OBJECTIVES:Umbilical cord leptin is increased in infants of women with obesity. We tested the hypothesis that a high cord leptin-to-fat mass ratio might be associated with adverse outcomes at birth and in early childhood. METHODS:A secondary analysis of vitamin D And Lifestyle Intervention for gestational diabetes mellitus prevention (DALI) trial was conducted. Cord leptin-to-fat mass ratios were classified into top (TT), middle, and low (LT) tertiles overall and within sexes. Relationship with neonatal outcomes and offspring BMI z-scores were compared between TT and LT groups. RESULTS:Among 323 infants (maternal pre-pregnancy BMI 33.7 ± 4.2 kg/m2, 52% male) female (vs. male) offspring had higher cord leptin, fat mass percentage, and leptin-to-fat mass ratio (median (IQR): 21.4 (13.4, 30.99) vs. 15.5 (8.3, 25.9), p < 0.001). Compared to the LT group, infants in the TT group (58% females) had higher cord leptin but similar fat mass percentage. Among males (but not in females), the C-peptide-to-glucose ratio was elevated in the TT group (vs. LT) (0.2 (0.1-0.2) vs. 0.1(0.02-0.2), p < 0.001), while birthweight (3.5 ± 0.5 vs. 3.7 ± 0.4 kg, p = 0.045), fat mass percentage (11.1 ± 3.9 vs. 13.0 ± 3.6, p = 0.008), and BMI z-scores (at age 1 only) were lower (median (IQR): -0.15 (-0.67, 0.98) vs. 1.35 (-0.06, 1.67), p = 0.03). CONCLUSIONS:Relative cord hyperleptinaemia was associated with reduced offspring BMI among males.

INTRODUCTION:Vitamin D (vitD) plays a role in metabolic regulation, including lipid metabolism and insulin sensitivity. During pregnancy, profound physiological changes in lipid handling and ketogenesis occur to support fetal development. However, the extent to which maternal vitamin D status influences these metabolic adaptations and fetal metabolic markers remains unclear. METHODS:In this secondary analysis, we examined lipid distribution throughout pregnancy-from before 20 weeks' gestation to delivery-in women with overweight or obesity, stratified by vitamin D status (deficiency, insufficiency, or sufficiency), assessing both maternal and cord blood. Main inclusion criteria were: age > =18 years, singleton pregnancy, < 20 weeks' gestation, BMI ≥ 29 kg/m2. Women with GDM < 20 weeks' gestation were excluded. In total, 962 pregnant women were divided into vitD deficient (< 30 nmol/L, n = 102), insufficient (30-50 nmol/L, n = 222) and sufficient (> 50 nmol/L, n = 638) groups. VitD levels and lipid concentrations were assessed at < 20, 24-28 and 35-37 weeks' gestation and in cord blood. RESULTS:Compared with vitD sufficient women, women with vitD deficiency had significantly larger increases in LDL-C throughout pregnancy and ß-OH-butyrate at 24-28 weeks' gestation, in adjusted analysis. VitD in cord blood was highest in offspring of mothers with vitD sufficiency. In cord blood, significantly higher ß-OH-butyrate was observed with vitD deficiency; lipid concentrations were similar between groups. CONCLUSIONS:Early vitamin D deficiency before 20 weeks of gestation was associated with altered metabolic trajectories during pregnancy, including greater increases in LDL cholesterol and ketone body concentrations in women with overweight or obesity, as well as higher cord blood ketone levels in their offspring. These findings suggest that early maternal vitamin D status may influence maternal and fetal metabolic adaptations, although causal relationships and clinical implications require further investigation. TRIAL REGISTRATION:Trial registered at ISRCTN registry (https://doi.org/10.1186/ISRCTN70595832) trial number ISRCTN70595832. Registration date 02/12/2011.

Aim To assess the effectiveness of a specific mobile health application (ANíMATE) in promoting weight loss in Spanish adults with obesity. Materials and methods We conducted a 4-month exploratory randomized controlled trial (ClinicalTrials.gov registration number: NCT05236881; registration date: January 24, 2022). Thirty-six participants with class I/II obesity were randomized to usual care (3 face-to-face visits) or the intervention group (ANíMATE in addition to 3 face-to-face visits). The primary outcome was total weight loss percentage (%TWL) at 4 months. Secondary outcomes included patient-reported outcome measures, additional weight-related variables, adherence, and satisfaction with the application. Results At 4 months, no differences were observed in the primary outcome, %TWL: 2.73% (0.86; 5.06) in the intervention group versus 1.23% (−0.23; 3.21) in the control group (P=.283). Differences were also not observed in secondary outcomes, with the exception of physical activity at 4 months, which was higher in the control group (2721 [1049; 5940] vs 923 [−8081; 639] MET-min; P=.020), and the frequency of weekly self-weighing at 2 months, also higher in the control group (76.9% vs 36.4%; P=.042). Mean user satisfaction with the application, evaluated using an ad hoc questionnaire, was high (16.5 out of 20). Conclusions In people with obesity, intervention with the ANíMATE mobile application added to usual care did not demonstrate additional benefits in %TWL, the primary outcome, in a study with limited statistical power. Further long-term research is needed to develop tailored mobile health strategies for weight management interventions that promote active user engagement.

ObjectivesMatching insulin injection timing with meals to optimize postprandial glucose excursions is a daily challenge for individuals with diabetes on a multiple daily injection (MDI) regimen. We aimed to analyze the impact of using a connected insulin pen cap (CIPC) on insulin injection timing and glycemic control.Research design and methodsPragmatic, real-life, multicenter, prospective, open-label, observational study, including one week of run-in and a 6-week follow-up, split into a two-week masked mode phase and a four-week active phase. Continuous glucose monitoring (CGM) and automatically tracked insulin injection data in individuals with insulin-treated diabetes (ITD) who started using the CIPC Insulclock. The baseline and five hours of paired CGM and rapid-acting insulin data collected from Insulclock v2.0® users were analyzed using the ROC detection methodology to identify meal events and the timing of insulin doses.ResultsOf 82 recruited patients, 52 completed the study (54.4 y, 56.6% women, 60.4% with type 1 diabetes [T1D]) across three hospitals and one primary care center in Spain. The CGM glucometrics comparison between the consecutive masked and active phases showed: Glucose Management Indicator (GMI) 8.1 + 1.7 vs 7.8 + 1.4% (-0.3%, p 0.034); Time in Range 70-180 (TIR): 56.9 + 24.5 vs 61.9 + 21.6% (+5.0%, p 0.0054); Time below range <70 (TBR70): 2.5 + 3.3 vs 1.76 + 2.6% (-0.74%, p 0.0015); Time above range >180 (TAR180): 40.9 + 25.3 vs 36.6 + 22.4% (-5.3%, p 0.016). The on-time insulin injections increased: 45.5 + 15.52 to 54.4 + 16.6% (p 0.0017). The timing of insulin injection relative to the post-meal glycemic excursions shifted from +5.6 min (IQR –19.8 to +34.0) in the masked phase (n = 231 events) to –5.9 min (IQR –27.6 to +33.9) in the active phase (n = 467 events) (p = 0.023). An earlier injection was associated with a reduction in TAR180 (p = 0.042). Questionnaires measuring patients’ reported outcomes (PROs) indicated a reduction in perceived treatment burden with the use of the Insulclock v2.0® CIPC.ConclusionsThe use of Insulclock v2.0® connected insulin pen cap is associated with improved insulin injection timing and glucometrics.

OBJECTIVE:To estimate the impact of detection and treatment of early gestational diabetes mellitus on short-term maternal, fetal, and neonatal outcomes. We defined 2 maternal (gestational diabetes prevalence and cesarean section) and 2 neonatal (preterm birth and macrosomia) primary outcomes. We also defined 5 maternal and 12 fetal-neonatal secondary outcomes. DATA SOURCES:Ovid Medline, Cochrane CENTRAL, and Embase since inception. The search was updated in November 2024. STUDY ELIGIBILITY CRITERIA:Inclusion criteria: randomized controlled trials addressing detection and treatment of early gestational diabetes (diagnosed before 20 completed weeks). EXCLUSION CRITERIA:pregestational diabetes or overt diabetes in pregnancy. STUDY APPRAISAL AND SYNTHESIS METHODS:The Cochrane Handbook was used to guide data extraction and interpretation including risk of bias assessment (Risk of Bias 2 tool). Aggregation and comparison of results were performed with Revman 5.4.1. Pooled relative risk and mean differences were calculated with 95% confidence intervals using random-effects models. The quality of the evidence for primary outcomes was summarized using Grading of Recommendations Assessment, Development and Evaluation criteria. RESULTS:We identified 1221 unique references. Seven articles addressing early gestational diabetes met the eligibility criteria with a total of 30,791 participants. These studies used 2 strategies: (1) treatment vs usual care of women with a diagnosis of early gestational diabetes and (2) population-based approaches, either performing screening (vs not) or using different cutoffs for diagnosis. In studies comparing treatment vs usual care, differences were observed only in secondary outcomes: more drug treatment, less maternal weight gain, lower birthweight, and less respiratory distress. In studies comparing different population-based strategies, primary outcomes differed for a higher rate of early and overall gestational diabetes (relative risk, 5.50; 95% confidence interval, 3.56-8.48 and 1.83; 95% confidence interval, 1.41-2.38, respectively) and a lower rate of primary cesarean section (relative risk, 0.88; 95% confidence interval, 0.84-0.93); as to secondary outcomes, differences were observed in terms of higher total pregnancy-induced hypertension and preeclampsia. The quality of evidence for most outcomes was low/very low. CONCLUSION:Detection and treatment of early gestational diabetes mellitus do not offer indisputable benefits either in treated women or at the population level. More studies are required to elucidate this issue.

Cardiovascular disease (CVD) risk prediction models for the general population may not provide accurate predictions in individuals with bipolar disorder (BD) who have elevated risks of cardiometabolic conditions and premature mortality. Therefore, we aimed to: 1) develop a five-year CVD risk prediction model in this population by using nationwide register data from Sweden, 2) investigate whether the performance improved when we considered additional risk factors, including psychiatric comorbidity, psychotropic medication, and socio-demographic variables, compared to using established CVD risk factors only, and 3) whether machine learning approach provided improvements compared to standard logistic regression models. We followed 33,933 persons with BD aged 30-82 years old, without previous CVD, from the date of BD diagnosis registered between 2007-2014, for up to five years. The logistic regression model containing only established risk factors yielded an area under the receiver operating characteristic curve (AUC) of 0.76 (95% confidence interval 0.74-0.78) in the test dataset, while the logistic regression model and the best performing machine learning model including additional predictors yielded similar results (AUC was 0.77 (0.75, 0.79) in both models). The performance of logistic regression models slightly improved with additional predictors when continuous risk scores were used. In conclusion, standard logistic regression and established CVD risk factors may be sufficient to predict CVD in individuals with BD when using population register-based data from Sweden. External validation across diverse healthcare settings and rigorous assessment of clinical impact will be crucial next steps before implementing these models in clinical practice.

BACKGROUND:Preexisting diabetes (PDM) increases the risk of maternal and perinatal mortality and morbidity. Reduction of maternal hyperglycemia prior to and during pregnancy can reduce these risks. Despite compelling evidence that preconception care (PCC), which includes achieving strict glycemic goals, reduces the risk of congenital malformations and other adverse pregnancy outcomes, only a minority of individuals receive PCC. Suboptimal pregnancy outcomes demonstrated in real-world data highlight the need to further optimize prenatal glycemia. New evolving technology shows promise in helping to achieve that goal. Dysglycemia is not the only driver of poor pregnancy outcomes in PDM. The increasing impact of obesity on pregnancy outcomes underscores the importance of optimal nutrition and management of insulin sensitizing medications during prenatal care for PDM. OBJECTIVE:To provide recommendations for the care of individuals with PDM that lead to a reduction in maternal and neonatal adverse outcomes. METHODS:The Guideline Development Panel (GDP) composed of a multidisciplinary panel of clinical experts, along with experts in guideline methodology and systematic literature review, identified and prioritized 10 clinically relevant questions related to the care of individuals with diabetes before, during and after pregnancy. The GDP prioritized randomized controlled trials (RCTs) evaluating the effects of different interventions (eg, PCC, nutrition, treatment options, delivery) during the reproductive life cycle of individuals with diabetes, including type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Systematic reviews queried electronic databases for publications related to these 10 clinical questions. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology was used to assess the certainty of evidence and develop recommendations. The approach incorporated perspectives from 2 patient representatives and considered patient values, costs and resources required, acceptability and feasibility, and impact on health equity of the proposed recommendations. RESULTS:In individuals with diabetes mellitus who have the possibility of becoming pregnant, we suggest asking a screening question about pregnancy intention at every reproductive, diabetes, and primary care visit. Screening for pregnancy intent is also suggested at urgent care/emergency room visits when clinically appropriate (2 | ⊕OOO). This was suggested based on indirect evidence demonstrating a strong association between PCC and both reduced glycated hemoglobin (HbA1c) at the first prenatal visit and congenital malformations.In individuals with diabetes mellitus who have the possibility of becoming pregnant, we suggest use of contraception when pregnancy is not desired (2 | ⊕⊕OO). This was suggested based on indirect evidence in women with diabetes, where PCC-including contraception as a key component-showed a clinically significant association with improvements in first-trimester HbA1c and the rate of congenital malformations, together with indirect evidence from the general population regarding the reduction of unplanned pregnancies and pregnancy terminations with the use of contraception.In individuals with T2DM, we suggest discontinuation of glucagon-like peptide-1 receptor agonist (GLP-1RA) before conception rather than discontinuation between the start of pregnancy and the end of the first trimester (2 | ⊕OOO). This was suggested based on limited data on risk of exposure to GLP-1RA receptor agonists during pregnancy.In pregnant individuals with T2DM already on insulin, we suggest against routine addition of metformin (2 | ⊕OOO). This was suggested based on the GDP judgment that the benefit of adding metformin to insulin to achieve decrease in rates of large for gestational age infants did not outweigh the potential harm of increasing the risk of small for gestational age infants or adverse childhood outcomes related to changes in body composition.In individuals with PDM, we suggest either a carbohydrate-restricted diet (<175 g/day) or usual diet (>175 g/day) during pregnancy (2 | ⊕OOO). This was suggested based on the GDP judgment that the available evidence was limited and very indirect, resulting in significant uncertainty about the net benefits or harms. As such, the evidence was insufficient to support a recommendation either for or against a carbohydrate intake cutoff of 175 g/day.In pregnant individuals with T2DM, we suggest either the use of a continuous glucose monitor (CGM) or self-monitoring of blood glucose (SMBG) (2 | ⊕OOO). There is lack of direct evidence supporting superiority of CGM use over SMBG for T2DM during pregnancy. There is indirect evidence supporting improved glucometrics with the use of CGM for individuals with T2DM outside of pregnancy, substantial improvements in neonatal outcomes for individuals with T1DM using CGM during pregnancy and the potential for decreasing adverse pregnancy outcomes with improved glucometrics in individuals with T2DM.In individuals with PDM using a CGM, we suggest against the use of a single 24-hour CGM target <140 mg/dL (7.8 mmol/L) in place of standard-of-care pregnancy glucose targets of fasting <95 mg/dL (5.3 mmol/L), 1-hour postprandial <140 mg/dL (7.8 mmol/L), and 2-hour postprandial < 120 mg/dL (6.7 mmol/L) (2 | ⊕OOO). This was suggested based on indirect evidence that associated adverse pregnancy outcomes with a fasting glucose > 126 mg/dL (7 mmol/L).In individuals with T1DM who are pregnant, we suggest the use of a hybrid closed-loop pump (pump adjusting automatically based on CGM) rather than an insulin pump with CGM (without an algorithm) or multiple daily insulin injections with CGM (2 | ⊕OOO). This was suggested based on a meta-analysis of RCTs which demonstrated improvement in glucometrics with increased time in range (MD +3.81%; CI -4.24 to 11.86) and reduced time below range (MD -0.85%; CI -1.98 to 0.28) with the use of hybrid closed-loop pump technology.In individuals with PDM, we suggest early delivery based on risk assessment rather than expectant management (2 | ⊕OOO). This was suggested based on indirect evidence that risks may outweigh benefits of expectant management beyond 38 weeks gestation and that risk assessment criteria may be useful to inform ideal delivery timing.In individuals with PDM (including those with pregnancy loss or termination), we suggest postpartum endocrine care (diabetes management), in addition to usual obstetric care (2 | ⊕OOO). As the postpartum period frequently overlaps with preconception, this was suggested based on indirect evidence demonstrating a strong association between PCC and both reduced HbA1c at the first prenatal visit and congenital malformations. CONCLUSION:The data supporting these recommendations were of very low to low certainty, highlighting the urgent need for research designed to provide high certainty evidence to support the care of individuals with diabetes before, during, and after pregnancy. Investment in implementation science for PCC is crucial to prevent significant mortality and morbidity for individuals with PDM and their children. RCTs to further define glycemic targets in pregnancy and refinement of emerging technology to achieve those targets can lead to significant reduction of harm and in the burden of diabetes care. Data on optimal nutrition and obesity management in pregnancy are lacking. More research on timing of delivery in women with PDM is also needed.

Maintaining tight glucose levels during pregnancy is crucial and challenging. We describe a pregnant woman with type 1 diabetes and obesity, treated with an advanced hybrid closed-loop MiniMed 780G since pre-pregnancy, who displayed a sustained improvement in her glucometrics after switching to lispro U-200.

Introduction: Achieving optimal glycemic control in patients with type 1 diabetes mellitus (PwT1DM) is essential to prevent complications. Continuous subcutaneous insulin infusion (CSII) systems combined with continuous glucose monitoring (CGM) have improved outcomes, but the effectiveness of additional technologies, such as mobile apps and hybrid closed-loop systems (HCLSs), remains unclear. This study evaluates glycemic control and quality of life (QoL) in adult PwT1DM transitioning from multiple daily injections (MDI) to a CSII, first with the Mylife™ Dose app and subsequently switching to an HCLS. Materials and Methods: This was a 10-month, multicenter, open-label sequential study involving 135 adults with type 1 diabetes (T1D), all of whom were using isCGM and MDI before transitioning to CSII, first with the Mylife Dose app and later to an HCLS. Glycemic control (glycated hemoglobin [HbA1c], time in range [TIR], time below range, time above range), insulin requirements, and QoL/treatment satisfaction/hypoglycemia perception (Diabetes Quality of Life questionnaire, Diabetes Treatment Satisfaction Questionnaire, Clarke's test) were measured at each of the four study visits. Results: Transitioning from MDI to CSII showed modest improvements in HbA1c (7.57%-7.42%; P = 0.02) and TIR (56.3%-60.4%; P < 0.01). The introduction of the Mylife Dose app did not provide significant additional improvements in glycemic control or QoL, although it provided an additional tool for diabetes management. However, switching to an HCLS resulted in substantial improvements in HbA1c (6.7%), TIR (73.1%), and QoL, with over 70% of patients achieving an HbA1c <7%. Insulin requirements increased slightly with the HCLS, primarily due to basal insulin. Adherence was high, with 88.1% completing the study. Conclusions: The Mylife Dose app does not improve glycemic control or QoL significantly but offers convenience for patients with T1D. In contrast, HCLSs provide significant metabolic and QoL benefits, supporting their integration into T1D management with appropriate reimbursement policies.

OBJECTIVE:To compare maternal glucose metrics and pregnancy outcomes of three advanced hybrid closed-loop (aHCL) systems (MiniMed 780G®, CamAPS® FX, and Tandem Control-IQ) in a real-world, multicenter cohort of pregnant women with type 1 diabetes. RESEARCH DESIGN AND METHODS:Cohort study including 137 pregnant women with type 1 diabetes using aHCL from 27 hospitals in Spain. Participants were grouped according to the aHCL system used: 85 MiniMed 780G (62%), 38 CamAPS FX (27.7%), and 14 Control-IQ (10.2%). Maternal glucose metrics (HbA1c and time spent within [TIRp], below [TBRp], and above [TARp] the pregnancy-specific glucose range 3.5-7.8 mmol/L), as well as pregnancy outcomes, were analyzed. Adjusted models were applied to account for potential confounding factors. RESULTS:No between-group differences in HbA1c levels were observed at baseline. By the third trimester, CamAPS FX and Control-IQ users had significantly lower HbA1c levels compared with the MiniMed 780G group (βadjusted -4.77 mmol/mol, 95% confidence interval [CI] -7.40 to -2.13; and βadjusted -4.79, 95% CI -8.53 to -1.06; respectively). In the second trimester, CamAPS FX was associated with a higher percentage of time in range (βadjusted +5.88%, 95% CI 1.09 to 10.67) and a lower percentage of time above range (βadjusted -6.36%, 95% CI -11.46 to -1.26) compared with MiniMed 780G, with no other significant differences observed in other trimesters. Both CamAPS FX and Control-IQ were associated with lower odds of large-for-gestational-age (LGA) infants (CamAPS FX: ORadjusted 0.25, 95% CI 0.08 to 0.77; Control-IQ: ORadjusted 0.10, 95% CI 0.01 to 0.99) compared with MiniMed 780G. CONCLUSIONS:In this multicenter observational study, CamAPS FX and Control-IQ users achieved better glycemic metrics and lower odds of delivering LGA infants compared with those using MiniMed 780G. These findings warrant investigation to confirm associations and inform individualized clinical decision-making in pregnant women with type 1 diabetes.

AIMS:To investigate the association between gestational weight gain (GWG) as per Institute of Medicine 2009 (IOM) and pregnancy outcomes in women with gestational (GDM) or preexisting diabetes mellitus (PDM), when applying or not a correction for gestational age (IOM-CGWG and IOM-GWG respectively). METHODS:We conducted a retrospective analysis of pregnant women with either GDM or PDM attended in our center. Exposure variables: IOM-GWG and IOM-CGWG. OUTCOME VARIABLES:Maternal and fetal/neonatal clinical outcomes. STATISTICS:Logistic regression with adjustment for other potential independent variables. RESULTS:In women with GDM, correction for gestational age did not affect the distribution of weight gain or the association with clinical outcomes (pregnancy-induced hypertension, preeclampsia, cesarean delivery, large-for-gestational age newborns (LGA), macrosomia and small-for-gestational age newborns (SGA)). In women with PDM, correction for gestational age, caused a shift in the distribution to a higher rate of excessive weight gain. In the adjusted analysis, IOM-GWG was significantly associated with cesarean delivery, preterm birth, LGA, macrosomia, SGA and neonatal respiratory distress. With IOM-CGWG, the association with preterm birth disappeared while an association with PIH emerged. Population-attributable and preventive fraction were substantial for both women with GDM and PDM. CONCLUSIONS:We conclude that the associations of IOM-GWG and IOM-CGWG are substantial in both women with GDM and PDM, indicating an area for potential intervention. In women with PDM, the modification of associations when gestational age is accounted for is relevant, highlighting the importance of considering this variable.

OBJECTIVE:The glucose management indicator (GMI) is widely used as a replacement for HbA1c, but information in pregnancy is very limited. We assessed the accuracy of GMI and associations with pregnancy outcomes in type 1 diabetes. RESEARCH DESIGN AND METHODS:We compared HbA1c, continuous glucose monitoring (CGM) metrics, GMI at 12, 24, and 34 weeks' gestation and outcomes in 220 women from the Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) using logistic/linear regression and Bland-Altman plots. RESULTS:GMI equations performed less accurately in pregnancy, with higher bias, especially in first and third trimesters. GMI and mean CGM glucose had equivalent predictive capability over pregnancy outcomes. GMI did not offer additional predictive capability over time in range (63-140 mg/dL; 3.5-7.8 mmol/L), time above range (>140 mg/dL; >7.8 mmol/L), and average CGM glucose concentrations. CONCLUSIONS:GMI is not an accurate replacement for HbA1c in pregnancy in women with type 1 diabetes.

Introduction and Objective: Cord blood leptin is high in neonates with high adiposity; however, little is known about the association of these levels with childhood adiposity. We compare the BMI of children with and without relative cord hyperleptinemia born to mothers with overweight/obesity in the Vitamin D and Lifestyle Intervention for Gestational Diabetes Mellitus Prevention (DALI) study. Methods: DALI mothers were contacted annually for available offspring weight and height over 5 years. Neonatal fat mass was calculated using Deierlein’s formula. Cord leptin-to-fat mass ratios were classified into low (LT), middle, and top (TT) tertiles overall and within sexes. Relationship with birthweight, cord C-peptide-to-glucose ratio, and offspring BMI were compared between LT and TT groups. Results: Among 324 babies (31% of total: maternal pre-pregnancy BMI 33.7±4.2 kg/m2, 83% European ethnicity, 52% boys, median cord leptin 8.3 (4.5-13.6) ng/ml), the median (IQR) cord leptin-to-fat mass ratio was 21.07 (12.0-34.8). Female (vs male) offspring had higher cord leptin (10.6 (5.6-16.3) vs. 6.7 (4.0-11.2), p<0.001) but lower fat mass % (10.4±3.8 vs. 12.4± 3.7, p<0.001), with similar cord C-peptide-to-glucose ratios at birth. Infants in the TT group (72% girls) had higher cord leptin (14.8 (10.7-20.7) vs. 4.0 (2.5-5.5), p<0.001) and lower fat mass % (9.8±3.5 vs. 12.6±3.9, p<0.001) and birthweight (kg) (3.4±0.5 vs. 3.6±0.5, p=0.002) compared to the LT group. Among boys, but not girls, the C-peptide-to-glucose ratio was elevated in the TT group (0.19±0.1 vs. 0.12±0.1, p<0.001). There was a trend of lower BMI in the TT group from age 1 through age 5, with a significant difference at age 2 (17.7±1.9 vs 16.5±1.4 (kg/m2), p=0.01). The trend was more remarkable in boys than girls. Conclusion: Relative cord hyperleptinemia in the offspring of women who are overweight/obese is associated with lower birthweight and BMI into early childhood. Longitudinal studies are needed to determine the long-term implications of these associations. J. Immanuel: None. S. Chirayath: None. G. Desoye: None. M. van Poppel: None. R. Corcoy: None. J. Harreiter: None. P. Damm: None. A. Kautzky-Willer: None. A. Lapolla: None. A. Bertolotto: None. D.J. Hill: None. D. Simmons: Research Support; Novo Nordisk, AMSL. Other Relationship; Abbott, Abbott, Boehringer-Ingelheim. Speaker's Bureau; Ascensia Diabetes Care. This project received funding from the European Community’s 7th Framework Program(FP7/2007–2013; grant agreement no. 242187). In the Netherlands, additional funding wasprovided by the Netherlands Organization for Health Research and Development (ZonMW) (Grant nr 200310013). In the UK, the DALI team acknowledges the support received from theNIHR Clinical Research Network: Eastern, especially the local diabetes clinical and research teams based in Cambridge. In Spain, additional funding was provided by CAIBER 1527–B–226.

Abstract Purpose We aimed to evaluate, in women with thyroid disorders the relationship between maternal thyroid status in each trimester and GWG according to Institute of Medicine (IOM).Methods Retrospective analysis of 782 pregnant women either receiving treatment with levothyroxine or attended because of hyperthyroidism. We used four summary measures of maternal thyroid status as predictors of GWG according to IOM: individual trimesters/at some point during pregnancy, subclinical and overt conditions combined/split.Results In women treated with levothyroxine, associations between maternal thyroid status and GWG were observed in three models. As an example, hyperthyroidism (subclinical/overt combined) in the second trimester, was associated with both insufficient (aOR: 2.96, 95% CI: 1.07–8.22) and excessive GWG (aOR: 3.25, 95% CI: 1.10–9.62). In women followed by hyperthyroidism, associations were observed in the four models. As an example, overt hypothyroidism at some point during pregnancy was associated with both insufficient GWG (aOR: 10.61, 95% CI: 2.23–50.36) and excessive GWG (aOR: 5.36, 95% CI: 1.34–21.51).Conclusions In these cohorts of pregnant women treated with levothyroxine or attended for hyperthyroidism, both maternal hypo and hyperthyroidism status display strong associations with GWG according to IOM both in expected and unexpected directions.

Self-management interventions (SMIs) offer a promising approach to actively engage patients in the management of their chronic diseases. Within the scope of the COMPAR-EU project, our goal is to provide evidence-based recommendations for the utilisation and implementation of SMIs in the care of adult individuals with type 2 diabetes mellitus (T2DM). A multidisciplinary panel of experts, utilising a core outcome set (COS), identified critical outcomes and established effect thresholds for each outcome. The panel formulated recommendations using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach, a transparent and rigorous framework for developing and presenting the best available evidence for the formulation of recommendations. All recommendations are based on systematic reviews (SR) of the effects and of values and preferences, a contextual analysis, and a cost-effectiveness analysis. The COMPAR-EU panel is in favour of using SMIs rather than usual care (UC) alone (conditional, very low certainty of the evidence). Furthermore, the panel specifically is in favour of using ten selected SMIs, rather than UC alone (conditional, low certainty of the evidence), mostly encompassing education, self-monitoring, and behavioural techniques. The panel acknowledges that, for most SMIs, moderate resource requirements exist, and cost-effectiveness analyses do not distinctly favour either the SMI or UC. Additionally, it recognises that SMIs are likely to enhance equity, deeming them acceptable and feasible for implementation.

The trial protocol and the data that support the findings of this study are available from the corresponding author upon reasonable request.