Maternal glycemic status and longitudinal fetal body composition and organ volumes based on three-dimensional ultrasonography
K. WagnerJessica L. GleasonZhen ChenCuilin ZhangStefanie N. HinkleDian HeWesley LeeRoger NewmanJohn OwenDaniel SkupskiWilliam A. GrobmanSeth ShermanFasil Tekola‐AyeleJagteshwar GrewalKatherine L. Grantz
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<p dir="ltr">Objective: Gestational diabetes mellitus (GDM) increases the risk of fetal overgrowth, as measured by two-dimensional (2D) ultrasonography. Whether fetal 3D soft tissue and organ volumes provide additional insight into fetal overgrowth is unknown. </p><p dir="ltr">Research Design & Methods: We prospectively evaluated longitudinal 3D fetal body composition and organ volumes in a diverse US singleton pregnancy cohort (2015-2019). Women were diagnosed with GDM, impaired glucose tolerance (IGT), or normal glucose tolerance (NGT). Up to five 3D ultrasound scans measured fetal body composition and organ volumes; trajectories were modeled using linear mixed models. Overall and weekly mean differences in fetal 3D trajectories were tested across glycemic status, adjusted for covariates.</p><p dir="ltr">Results: In this sample (N=2427), 5.2% of women had GDM and 3.0% had IGT. Fetuses of women who developed GDM, compared to NGT, had larger fractional arm and fractional fat arm volumes from 26-35 weeks, smaller fractional lean arm volume from 17-22 weeks, and larger abdominal area from 24-40 weeks. Fetuses of women with IGT had similar growth patterns, but manifested later in gestation and with larger magnitudes, and had larger fractional lean arm volume. No overall differences were observed among thigh or organ volumes across glycemic status.</p><p dir="ltr">Conclusions: Body composition differed in fetuses of GDM pregnancies, including larger arm and abdominal measures across the second and third trimesters. Patterns were similar in IGT pregnancies except occurred later in gestation and with larger magnitudes. Future research should explore how lifestyle and medication may alter fetal fat accumulation trajectories among hyperglycemic pregnancies. </p>Background We investigated whether patients' perceived glycemic control and self-reported diabetes self-care correlated with their actual glycemic control. Methods A survey was administered among patients with diabetes mellitus at an outpatient clinic with structured self-report questionnaires regarding perceived glycemic control and diabetes self-management. Actual glycemic control was defined as a change in glycated hemoglobin (A1C) or fasting plasma glucose (FPG) since the last clinic visit. Results Patients who perceived their glycemic control as "improved" actually showed a mild but significant decrease in the mean A1C (-0.1%, P=0.02), and those who perceived glycemic control as "aggravated" had a significant increase in the mean FPG (10.5 mg/dL or 0.59 mmol/L, P=0.04) compared to the "stationary" group. However, one-half of patients falsely predicted their actual glycemic control status. Subjective assessment of diabetes self-care efforts, such as adherence to a diet regimen or physical activity, correlated positively with perceived glycemic control but showed no association with actual glycemic control. Conclusion Patients should be encouraged to assess and monitor diabetes self-care more objectively to motivate behavioral modifications and improve their actual glycemic control. Keywords: Perceived glycemic control; Actual glycemic control; Diabetes self-care
Glycated hemoglobin
Outpatient clinic
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Although glycemic control is known to reduce complications associated with diabetes, it is an elusive goal for many patients with diabetes. The objective of this study was to identify factors associated with sustained poor glycemic control, some glycemic variability, and wide glycemic variability among diabetes patients over 3 years.This retrospective study was conducted among 2,970 diabetes patients with poor glycemic control (hemoglobin A1c [HbA1c] >9%) who were enrolled in a health plan in Hawaii in 2006. We conducted multivariable logistic regressions to examine factors related to sustained poor control, some glycemic variability, and wide glycemic variability during the next 3 years. Independent variables evaluated as possible predictors were age, sex, type of insurance coverage, morbidity, diabetes duration, history of cardiovascular disease, and number of medications.Longer duration of diabetes, being under age 35, and taking 15 or more medications were significantly associated with sustained poor glycemic control. Preferred provider organization and Medicare (vs health maintenance organization) enrollees and patients with high morbidity were less likely to have sustained poor glycemic control. Wide glycemic variability was significantly related to being younger than age 50, longer duration of diabetes, having coronary artery disease, and taking 5 to 9 medications per year.Results indicate that duration of diabetes, age, number of medications, morbidity, and type of insurance coverage are risk factors for sustained poor glycemic control. Patients with these characteristics may need additional therapies and targeted interventions to improve glycemic control. Patients younger than age 50 and those with a history of coronary heart disease should be warned of the health risks of wide glycemic variability.
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Continuous glucose monitoring (CGM) provides comprehensive assessment of daily glucose measurements for patients with diabetes and can reveal high and low blood glucose values that may occur even when a patient’s A1C is adequately controlled. Among the measures captured by CGM, the percentage of time in the target glycemic range, or “time in range,” (typically 70–180 mg/dL) has emerged as one of the strongest indicators of good glycemic control. This review examines the shift to using CGM to assess glycemic control and guide diabetes treatment decisions, with a focus on time in range as the key metric of glycemic control.
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Blood Glucose Self-Monitoring
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Introduction:Remogliflozin etabonate is the latest addition to the Sodium glucose co-transporter-2 (SGLT2) inhibitor class of drugs which is a potent and selective inhibitor of SGLT2.A real world non-randomized, single centre, retrospective study was done to assess changes in glycemic and extra glycemic parameters of type 2 diabetes mellitus (T2DM) patients who were well controlled (HbA1c ≤ 7%) with other SGLT2 inhibitors (Dapagliflozin and Empagliflozin), but had difficulty to afford the high cost of therapy from out of pocket expenditure and voluntarily requested for a switchover for economic reasons. Materials and methods:Retrospective observation of the variations in glycemic and extra glycemic parameters including blood pressure, body weight, lipid profile and eGFR of 32 patients was recorded, when they were initiated on Remogliflozin etabonate, replacing other SGLT2 inhibitors (19 were on Empagliflozin and 13 were on Dapagliflozin).The data was tabulated for a total of three visits (First -initial, Second -at three months from initial and Third-at six months from initial), after which analysis was done.Results: There were no significant changes in HbA1c value from baseline after initiation of remogliflozin etabonate from dapagliflozin and empagliflozin.There was also no significant reduction of blood pressure, body weight and eGFR from baseline for patients switched from Dapagliflozin.However, the change in blood pressure and body weight was statistically significant for patients switched from Empagliflozin (p<0.01). Conclusion:Remogliflozin etabonate given as 100 mg twice daily is non-inferior to Empagliflozin 10 mg / Dapagliflozin 10 mg given as once daily to patients of T2DM as far as their glycemic goals are concerned with favourable extra glycemic benefit and cost burden reduction of more than 50%.
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Continuous glucose monitoring (CGM) provides comprehensive assessment of daily glucose measurements for patients with diabetes and can reveal high and low blood glucose values that may occur even when a patient’s A1C is adequately controlled. Among the measures captured by CGM, the percentage of time in the target glycemic range, or “time in range” (typically 70–180 mg/dL), has emerged as one of the strongest indicators of good glycemic control. This review examines the shift to using CGM to assess glycemic control and guide diabetes treatment decisions, with a focus on time in range as the key metric of glycemic control.
Target range
Blood Glucose Self-Monitoring
Blood glucose monitoring
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Continuous glucose monitoring (CGM) provides comprehensive assessment of daily glucose measurements for patients with diabetes and can reveal high and low blood glucose values that may occur even when a patient’s A1C is adequately controlled. Among the measures captured by CGM, the percentage of time in the target glycemic range, or “time in range,” (typically 70–180 mg/dL) has emerged as one of the strongest indicators of good glycemic control. This review examines the shift to using CGM to assess glycemic control and guide diabetes treatment decisions, with a focus on time in range as the key metric of glycemic control.
Target range
Blood Glucose Self-Monitoring
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Herein I investigated the impact of vitamin D on glycemic control in patients with type 2 diabetes mellitus. 128 patients with type 2 diabetes mellitus were enrolled in this study (mean (S.D) age: 57.7±10 years, 26.6% were female). It was collected clinical and laboratory characteristics of patients from hospital records retrospectively. Patients were divided into two groups according to the HBA1c values: good glycemic control (HbA1c≤7%) and poor glycemic control (HbA1c>7%). It was compared 25 hydroxyvitamin (OH) D and other collected laboratory parameters between the two groups. The vitamin D deficiency rate was 98.3%. In the result with ROC curve analyzes and Mann Whitney U test vitamin D was'nt significantly associated with glycemic control (P value >0.05). Among other parameters result with ROC curve analyzes and student t test RDW-CV was found to be significantly associated with glycemic control (P value <0.05). Although high level of vitamin D deficiency, present study indicated that vitamin D was'nt significantly related to glycemic control in type 2 diyabetes mellitus. Even so RDW-CV was significantly related to glycemic control.
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Optimal glycemic control without the presence of diabetes-related complications is the primary goal for adequate diabetes management. Recent studies have shown that hemoglobin A1c level cannot fully evaluate diabetes management as glycemic fluctuations are demonstrated to have a major impact on the occurrence of diabetes-related micro- and macroangiopathic comorbidities. The use of continuous glycemic monitoring systems allowed the quantification of glycemic fluctuations, providing valuable information about the patients’ glycemic control through various indicators that evaluate the magnitude of glycemic fluctuations in different time intervals. This review highlights the significance of glycemic variability by describing and providing a better understanding of common and alternative indicators available for use in clinical practice.
Diabetes management
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