HbA1c Levels Research Articles

Imbalance of Myoinositol and D‐Chiro‐Inositol in Saliva of Children With Type‐1 Diabetes Mellitus: A Cross‐Sectional Study

ABSTRACTObjectiveEarlier work suggests Myoinositol (MI) and D‐chiro‐ inositol (DCI) imbalance in urine and plasma of diabetic patients, and their potential for monitoring insulin resistance. This study aimed to assess levels of Myoinositol (MI) and D‐chiro‐ inositol (DCI) in saliva of children with type 1 diabetes mellitus (DM‐1) and controls, to verify if concentrations of MI and DCI are similarly altered in saliva, exploring their potential for monitoring DM‐1.Design, Patients and MeasurementsThis cross‐sectional clinical study enroled 45 patients (DM‐1, n = 25; Controls, n = 20). Children aged 3–12 years with fasting blood glucose levels > 126 mg/dL, and HbA1c levels > 7%. Saliva was collected, and salivary measurements included pH, flow rates and concentrations of MI, DCI and glucose, employing high‐performance liquid chromatography. Periodontal health was assessed using bleeding and plaque indices.ResultsChildren with DM‐1 showed elevated MI (p = 0.001), reduced DCI (p = 0.001), and increased MI‐DCI ratio (p = 0.001). The MI‐DCI ratio was elevated by 16‐fold among diabetic children. Plaque (p = 0.003) and gingival bleeding (p = 0.001) were higher in DM‐1 than controls. The MI increased the odds of an outcome of DM‐1 by 174%, while DCI reduced the odds by 63%, highlighting their strong and opposing effects on DM‐1.ConclusionsChildren with DM‐1 express higher MI and lower DCI levels, while non‐diabetic children show an inversion of these concentrations. Inositol imbalance in saliva of diabetic children resembles previous results in urine, and represents a possible venue for monitoring this disease, paving the way for future investigations into salivary inositols.

Corneal subepithelial nerve fibers in type 2 diabetes: potential biomarker of diabetic neuropathy

AIM: To observe the changes in corneal subepithelial nerve fibers (CNFs) and Langerhans cells (LCs) in patients with type 2 diabetes using corneal laser confocal microscopy (CLCM). METHODS: A total of 60 patients (64 eyes), including 40 patients with type 2 diabetes (DM group) and 20 subjects without diabetes (control group) were included with CLCM. Neuron J plugin of Image J software were used for quantitative analysis of CNF length (CNFL), CNF density (CNFD), corneal nerve branch fiber density (CNBD), main branch length density, branch length density, corneal nerve fiber tortuosity (NT) score, and LCs density. An independent samples t-test to analyze the variability between the two groups was performed, and Pearson correlation analysis was used to analyze the relationships between CNF and multiple biochemical indicators in the DM group. The predictive power of CNF for type 2 diabetes was assessed using the receiver operating characteristic (ROC) curve. RESULTS: There were significant differences in the CNFL, CNFD, and main branch length density between two groups. The results of Pearson correlation analysis showed a significant negative correlation between CNFD and the duration of diabetes as well as triglyceride levels and total cholesterol, and a significant positive correlation between CNFD and serum albumin. In addition, the NT score showed a positive correlation and urea nitrogen, similar to the positive correlation observed between LC density and glycosylated hemoglobin (HbA1c) levels. CNFD showed the highest area under the curve (AUC of ROC) value, followed by main branch length density and CNFL. The AUC of the ROC curve under the logistic regression model also demonstrated good predictive values. The cut-off values of CNFD, CNFL, and main branch length density for diabetes showed 31.25, 18.85, and 12.56, respectively. CONCLUSION: In patients with type 2 diabetes, there is a notable reduction in both CNFL and CNFD. These measurements can be influenced by various blood biochemical factors. However, the compromised nerve fibers can serve as valuable indicators for predicting the onset of type 2 diabetes and also as biomarkers for detecting diabetic neuropathy and its related complications.

Identification of heterozygous mutations of ABCC8 gene responsible for maturity-onset diabetes of the young with exome sequencing

Abstract Background Although the MODY12 subtype, caused by ABCC8 mutations, is rare, it is highly sensitive to sulfonylureas. The identification of ABCC8 mutations in patients clinically diagnosed with MODY has the ability to contribute to the precise management of diabetes. Methods Genetic analysis of two families with MODY were conducted using whole-exome sequencing (WES) and Sanger sequencing. The spatial structures of the mutant proteins were constructed using MODELLER and PyMOL software to provide further evidence of pathogenicity. Results The heterozygous missense mutations V357I and R1393H in ABCC8 were found in probands of two unrelated MODY pedigrees, which co-segregated with the hyperglycemic phenotypes in these two pedigrees. Detection of the V357I mutation enabled the proband of family A to successfully transfer from insulin to sulfonylurea (SU). After 3 months of follow-up for the SU trial, the HbA1c level of proband A improved from 12.4% at the initial diagnosis to 7.20%. Proband B was treated with insulin because of pregnancy and poor islet function. In silico analysis indicated that the R1393H mutation resulted in a longer hydrogen bond distance to L1389 and cleavage of carbon-hydrogen bonds to V1395, A1390, and L1389. Conclusions We have described two pathogenic missense mutations in ABCC8 in Chinese families with MODY. Our findings support the heterogeneity in the clinical features of MODY12 caused by ABCC8 mutations.

Determining how the gestational changes, including low hemoglobin influence the hba1c and estimated average glucose relationship

ABSTRACT Background: Gestational Diabetes Mellitus (GDM) affects up to 14% of pregnancies globally, with accurate glycemic control critical for preventing adverse outcomes. While HbA1c is a standard marker for long-term glucose control, its reliability in pregnant women with anemia is debated. This study explores the association between anemia and glycemic indicators (Glycosylated hemoglobin HbA1c, Random plasma glucose (rPG), and Estimated average glucose (eAG) in pregnant women with GDM. Additionally, it examined the correlation between average glucose levels or eAG, measured by random plasma glucose rPG, and HbA1C. Methods: A prospective case-control study was carried out over eight months at the Departments of Chemical Pathology and Obstetrics and Gynecology, Dow University of Health Sciences (DUHS). Pregnant women in their second trimester after being diagnosed for GDM through oral glucose tolerance test were classified into anemic (hemoglobin < 10.5 g/dL) and non-anemic groups. Blood samples were collected and analyzed for HbA1c, hemoglobin, and random plasma glucose levels. Data were processed using SPSS (version-26) different variables compared by using independent t-test and correlation analyses at a significance level of p < 0.05. Results: Mean values for eAG, HbA1C, and rPG were 174.22 ± 24.489 mg/dl, 8.342 ± 1.6152%, and 166.21 ± 21.478 mg/dl, respectively. Anemia was associated with significantly higher HbA1C (p < 0.001), eAG (p < 0.001), and rPG (p = 0.004). A strong positive correlation was observed between eAG and rPG (r = 0.958, p < 0.01), while eAG showed a moderate correlation with HbA1C (r = 0.501, p < 0.01). In contrast, the correlation between HbA1C and rPG was weaker (r = 0.331, p < 0.01). Conclusion: eAG proved to be a good indicator for assessing glycemic control in pregnant non-anemic women with GDM. Anemia significantly affected glycemic metrics, leading to higher HbA1C and glucose levels.

Comparison of HPLC with Tinia for hba1c measurement in diabetic and non-diabetic patient; a study from a tertiary care hospital of Baluchistan

Background: Diabetes mellitus, a disease with serious implications on human health ,is on continuous rise. It is the need of hour to find and establish the markers to measure its long term effects. Diabetes Control and Complication Trial has confirmed role of HbA1c in effective blood glucose level monitoring .New methods are being developed for measurement of HbA1c .Before using these methods, it is essential to analyze these methods for reliability .Therefore in our study we will compare and evaluate correlation and agreement between Turbidimetric Inhibition Immunoassay TINIA and High Performance Liquid Chromatography HPLC for HbA1c measurement. Methods: Three hundred and ninety-four samples were analyzed simultaneously on Roche Cobas 501 and D-10 HbA1c analyzer by Bio-Rad for HbA1c level estimation. The results were entered into SPSS version 26 for method validation. This is an observational study conducted at Department of Pathology CMH Quetta from January 2022 to August 2023. Results: Inter and intra run coefficient of variation (CV) was within the allowable limit of 2 %. Mean difference between results of Turbidimetric Inhibition Immunoassay TINIA and High-Performance Liquid Chromatography HPLC was very low with HPLC results slightly on higher side. For low control TINIA had between run CV of 0.3% (Low control) 0.8 % (High control) and within run CV of 0.3% (Low control), 0.6% (High control); while HPLC had between run CV of 0.6%(Low control) 1.8% (High control), and within run CV of 0.3% (Low control), and 0.7%. Linear regression analysis displayed high concordance and agreement between the results of both methods. Conclusion: Both methods have comparable results in HbA1c estimation.

Dermatological manifestations in diabetes mellitus and its relation with HbA1c levels – An observational study

Diabetes Mellitus is a chronic, metabolic disease characterised by elevated levels of blood glucose, which over time leads to serious damage. The most common is type 2 diabetes which occurs when body becomes resistant to insulin or doesn’t make enough insulin. Skin manifestations are seen generally in pre-diabetes, undiagnosed, long-term and uncontrolled diabetes mellitus. Skin symptoms may help in diagnosing a denovo case and may give an insight into the patient's diabetic status. This is a cross-sectional, observational study conducted in patients attending the outpatient departments of Dermatology, General Medicine and those admitted under these departments over a period of four months. Clearance from Institutional Ethics Committee was taken before the start of the study. A sample population of 100 was selected randomly based on inclusion and exclusion criteria. Glycaemic profiles including HbA1c were done. Infections (35%) were the most common cutaneous symptoms, followed by papulosquamous illnesses (19%), autoimmune diseases (7%), obesity-related (6%), diabetic vasculopathy-related (5%) and miscellaneous conditions (28%), which included generalised pruritus and xerosis etc. The majority of infections were superficial fungal infections, followed by bacterial and viral infections. Dermatophytosis accounted for a majority of superficial fungal infections. Significant correlation was found between higher HbA1c levels and infections, papulo-squamous diseases, auto-immune diseases, obesity-related manifestations.Higher HbA1c levels were found to be significantly associated with a variety of cutaneous symptoms such as infections, papulosquamous illnesses, autoimmune disorders, and obesity-related manifestations.

Lipophilic index of serum phospholipids in patients with type 2 diabetes and atherosclerotic cardiovascular disease: links with metabolic control, vascular inflammation and platelet activation.

Little is known about the mechanisms underlying the association of the serum phospholipid lipophilic index (LI) with atherosclerotic cardiovascular disease (ASCVD) in patients with type 2 diabetes (T2D). Therefore, we investigated whether the LI is associated with glucometabolic control, meta-inflammation, thrombin generation, fibrin clot properties, endothelial function and platelet activation in T2D patients with angiographically documented ASCVD. We studied 74 T2D patients with ASCVD, aged 65.6 ± 6.8 years, with a median diabetes duration of 10 years and median HbA1c of 7.0%. Serum phospholipid fatty acids (FAs) were measured by gas chromatography. The serum phospholipid LI was calculated as the sum of the products of the proportion (% of total FAs) with the melting points (°C) of each individual FA, divided by the sum of the proportions of all FAs. Levels of HbA1c, insulin, leptin, adiponectin, lipid profiles, inflammatory markers (hsCRP, interleukin-6, TNF-α), Lp-PLA2 (a biomarker of vascular inflammation), endothelial function (sICAM-1, sVCAM-1, FMD, NMD), thrombin generation, fibrin clot properties and platelet activation, measured by light transmission aggregometry with arachidonic acid [AA] and adenosine diphosphate [ADP], were assessed. Patients with LI > 16.9°C (median) had higher HbA1c concentrations by 5.9% compared to the remaining subjects (p = 0.035). In this group, HbA1c levels ≥ 7.0% were found more often than in individuals with LI ≤ 16.9°C (62.2 vs. 35.1%; p = 0.020). Subjects with LI > 16.9°C had higher levels of TCh by 17.1% (p = 0.012), LDL-Ch by 29.4% (p = 0.003), interleukin-6 by 22.2% (p = 0.031) and Lp-PLA2 by 32.4% (p = 0.040), compared to the remaining patients. Moreover, they had increased maximal platelet aggregation induced by AA (p = 0.045), but not by ADP. Serum phospholipid LI correlated with HbA1c (r = 0.24; p = 0.037), TCh (r = 0.36; p = 0.002), LDL-Ch (r = 0.38; p < 0.001), interleukin-6 (r = 0.27; p = 0.020) and Lp-PLA2 (r = 0.26; p = 0.026). There were no intergroup differences in endothelial function, thrombin generation and fibrin clot properties. Regression analysis showed that HbA1c ≥ 7.0% and serum levels of LDL-Ch, interleukin-6 and Lp-PLA2 were predictors of LI > 16.9°C in adjusted models. In well-controlled T2D patients with ASCVD, the higher serum phospholipid LI is associated with worse glucometabolic control, enhanced vascular inflammation and higher platelet reactivity during aspirin treatment at cyclooxygenase-1-selective doses.

Survival rate of diabetic-related lower extremity amputees in hospitals in the Eastern Cape

Background: Diabetes mellitus (DM) is a global health concern that has greatly affected South Africa. The gap in the current management of DM has resulted in complications such as lower extremity amputations (LEAs) and death. Eastern Cape province reflects this struggle, with disparities in access to healthcare and poor health outcomes. Understanding survival rates and associated factors between the urban Livingstone Hospital and the rural Nelson Mandela Academic Hospital can improve health interventions and outcomes.Objectives: This study compared the survival rate of patients in urban areas and those in rural areas.Method: This retrospective cohort study was conducted in an urban and a rural hospital by reviewing existing medical records of diabetic patients who underwent an LEA between 2016 and 2019.Results: The retrospective cohort study examined 439 diabetic-related LEA cases. This study found that residing in rural areas significantly decreased the risk of mortality by 62% compared with living in the urban areas. Factors such as haemoglobin A1c (HbA1c) levels, nephropathy, cardiovascular disease, human immunodeficiency virus (HIV), other comorbidities and level of amputation significantly influenced survival probabilities.Conclusion: Survival analysis indicated a significant difference in the 3-year survival probabilities of the two groups, favouring rural residency (p = 0.001). The biggest cause for concern between the two regions was uncontrolled blood glucose levels as this resulted in high mortality rates.Contribution: Insights from this study have shown that introducing podiatry and orthotics at primary healthcare (PHC) could improve foot care and reduce diabetic-related LEAs and mortality.

The outcomes of electronic personal health records in patients with heart failure or coronary artery disease.

There are limited data on the efficacy of smartphone-based personal health records (PHRs) in patients with cardiovascular disease. This study aimed to examine the processes, outcomes and challenges associated with the implementation of integrated PHRs in patients with heart failure (HF) or coronary artery disease (CAD). This prospective single-group study evaluated the effects of a PHR system with the capability to capture electronic health records and vital signs in patients with HF or CAD. The outcomes measured were the 6-month changes in blood pressure (BP), body weight (BW), brain natriuretic peptide (BNP) levels, lipid profiles and haemoglobin (Hb) A1c levels. Between June 2021 and March 2022, we enrolled 111 patients (median age: 61years and 47% women) with CAD and/or HF. Over 6months, the PHR review count distribution was skewed: median 749 times (lowest 2, highest 5724)/180days, suggesting both low and excessive PHR users. After 3days, 23% of the patients discontinued inputting their vital signs and medication status. At 6months, compared with patients who discontinued, those who continued to input their vital signs (N=86) showed a significant decrease in their systolic BP and LDL-C levels but not in the diastolic BP, BW, BNP, HDL-C, triglyceride or HbA1c levels. The implementation of smartphone-based PHRs in daily practice is challenging for patients with HF or CAD. However, we observed positive indications of the benefits of PHR in these patients. UMIN000044369.

Chromium supplementation and type 2 diabetes mellitus: an extensive systematic review.

Diabetes is a global public health concern with increasing prevalence worldwide. Chromium (Cr), a trace element found in soil, water, and food, has been proposed to have a possible positive effect in glucose metabolism and diabetes mellitus prevention. However, the relationship between trivalent chromium [Cr(III)] exposure, mainly through the consumption of diet supplements, and type 2 diabetes mellitus (T2DM) remains controversial. An extensive systematic review of the current literature on randomized controlled studies (RCTs) was conducted from 1 January 2000, to January 2024 using the databases PubMed, Scopus, ScienceDirect, and Cochrane, with specific keywords and inclusion as well as exclusion criteria. After close screening of the research studies retrieved from the mentioned websites was conducted, the most related studies were included in the final systematic review. The studies were evaluated for the degree of relevance, quality, and risk bias, using appropriate quality assessment tools. Several of the included RCT studies reported possible benefits of Cr(III) supplementation, mainly in the form of chromium picolinate (CrPic), chromium yeast (CY), chromium chloride (CrCl3), and chromium nicotinate (CrN). The dosage of chromium was between 50 and 1000μg/day and it was consumed from 2 to 6months. Glycemic control markers, including FPG, insulin, HbA1C, and HOMA-IR levels, significantly decrease following chromium supplementation, mainly in studies with a longer intervention period. Supplementing with chromium (Cr) indicated that could significantly improve lipid profile by raising high-density lipoprotein and lowering triglyceride and total cholesterol while having little effect on low-density lipoprotein. However, most research findings include significant limitations, such as inconsistent dosage and type of chromium, formulation of supplements, and study duration. Further well-designed and high-quality research is needed to fully understand the role of chromium dietary supplementation and the potential risks related to its mechanisms of action, type, and dose, in the prevention and treatment of type 2 diabetes mellitus.

Metformin plus lifestyle interventions versus lifestyle interventions alone for the delay or prevention of type 2 diabetes in individuals with prediabetes: a meta-analysis of randomized controlled trials.

We conducted this meta-analysis of randomized controlled trials (RCTs) to compare the efficacy of adding metformin to lifestyle interventions versus lifestyle interventions alone in individuals with prediabetes. We searched four databases from inception until March 20, 2024. Our primary outcomes included the incidence of type 2 diabetes, hemoglobin A1c (HbA1c), and fasting plasma glucose (FPG). Secondary outcomes included blood pressure, plasma lipids, and weight measurements. Dichotomous outcomes were pooled as the risk ratio (RR) and its 95% confidence interval (CI), while continuous outcomes were pooled as the standardized mean difference (SMD) and its 95% CI in the random effect model. All statistical analyses were conducted using the "meta" package of RStudio software. We included 12 RCTs, comprising 2720 patients. Adding metformin to lifestyle interventions significantly reduced HbA1c levels (SMD = -0.10, 95% CI [-0.19, -0.01], P = 0.03) and the incidence of type 2 diabetes (RR = 0.85, 95% CI [0.75, 0.97], P = 0.01). Interestingly, adding metformin to lifestyle interventions was comparable to lifestyle interventions alone in terms of FPG at both 3 and 6 months; however, it significantly reduced FPG at 12 months (SMD = -0.34, 95% CI [-0.59, -0.08], P = 0.01). There were no significant differences between the two groups in terms of all secondary outcomes. Our findings suggest that adding metformin to lifestyle interventions may improve glycemic control in individuals with prediabetes and reduce their risk of progression to diabetes, compared to lifestyle interventions alone. A longer duration of this combined approach may be required to observe the desired effects.

Short-Term Impact of Digital Mental Health Interventions on Psychological Well-Being and Blood Sugar Control in Type 2 Diabetes Patients in Riyadh

Background: Type 2 diabetes (T2D) management is complicated by psychological factors, yet mental health interventions are not routinely integrated into diabetes care. This study investigated the impact of a digital mental health intervention on psychological well-being and glycemic control in T2D patients. Methods: A quasi-experimental study was conducted with 120 T2D patients divided into intervention (n = 60) and control (n = 60) groups. The intervention group received a one-month digital mental health intervention alongside standard care. Psychological well-being (PHQ-9, GAD-7, and DDS) and glycemic control (HbA1c) were assessed at baseline and post-intervention. Results: The intervention group showed significant improvements in HbA1c levels (−0.5%, p = 0.032), PHQ-9 (−3.1, p = 0.001), GAD-7 (−2.8, p = 0.006), and DDS (−7.7, p = 0.012) scores compared to the control group. Strong correlations were observed between psychological improvements and HbA1c reductions. Higher engagement with the digital platform was associated with greater improvements in both psychological and glycemic outcomes. Conclusions: Integrating digital mental health interventions into T2D care can significantly improve both psychological well-being and glycemic control. These findings support a more holistic approach to diabetes management that addresses both mental and physical health aspects.

The effect of diabetes education on maternal and neonatal outcomes in pregnant women diagnosed with gestational diabetes.

Education during pregnancy is important for the development of the pregnant woman's ability to adapt to change and for a healthy birth. In this study, we aimed to examine the effects of education through a diabetes education program on maternal and newborn health in women diagnosed with gestational diabetes. In our study, we compared the maternal and neonatal health outcomes of pregnant women who participated in the diabetes education program and were diagnosed with gestational diabetes with the outcomes of pregnant women who did not participate in the diabetes education program and were diagnosed with gestational diabetes. The study included patients who were diagnosed with diabetes between 24and 26 weeks gestation at a tertiary education and research hospital and who underwent a 75-gram OGTT test. Age, BMI, parity, method of delivery, weight gain during pregnancy, newborn birth weight, gestational age and Apgar scores were compared. The study included 119 patients and analyzed maternal-neonatal outcomes. There were no statistically significant differences in age (33 ± 5.7 versus 31 ± 5.2), body mass index (BMI) (32.2 vs. 31.2), gravidity, parity, number of miscarriages, mode of delivery, family history of diabetes, smoking, prenatal corticosteroid use, and gestational age at delivery. The HbA1c value (p: 0.013), the total weight gain during pregnancy (p: 0.015), the need for insulin treatment (p: 0.002), and the birth weight (0.005) were significantly higher in the group without diabetes education. In our study, diabetic school education was associated with lower HbA1c levels, less weight gain and less need for insulin therapy. When the results were categorized by insulin use, it was found that in patients using insulin, those who received diabetic school education had fewer macrosomic fetuses, whereas in patients not using insulin, those who received diabetic school education had lower maternal weight gain during pregnancy.

HPB SO15 - Developing protocol for managing diabetes after Distal pancreatectomy

Abstract Background The incidence of new-onset diabetes mellitus (NODM) has been reported to be 18% to 39% after pancreaticoduodenectomy and 5% to 42% after distal pancreatectomy. Postoperative NODM is historically referred to as type 3c diabetes mellitus (DM). Postoperative HbA1c levels over 7% or 52 mmol have been identified as one of the independent risk factors for tumor recurrence and overall poor survival after cancer-related resections. This study aimed to evaluate the current practice in glycemic monitoring of patients who had distal pancreatectomy and to develop a departmental protocol for Glycemic monitoring in the perioperative period. Method Electronic medical records of 74 patients were reviewed, of these, 61 patients who underwent distal pancreatectomy from Jan 2019 to Dec 2023 was included in the study. All patients with distal pancreatectomy were included irrespective of their pathological diagnosis. age or gender. Patients who died in the perioperative period or the ones who did not have distal pancreatectomy were excluded. (necrosectomy, drainage procedures, GIST, central pancreatectomy. Data analysis performed using Microsoft Excel Results The Age ranged from 24-86. 61 patients were included in the study where whereas male-to-female ratio is shown in the Pie Chart. 80% of the patients had investigations for glycemic status, Only 59% (36/61) had HBA1C done, additional 21% others had only glucose levels measured. 19.7% had no investigations to date. This graph shows the current diabetic status of patient The graph shows the variability in practice with no consistency. Overall 36% of our patients have become diabetic or Pre-diabetic post distal pancreatectomy. Conclusion There is a lack of consistency in the follow-up of our patients regarding glycemic control. This calls for the development of a defined departmental protocol for the follow-up of our patients. Every patient with pancreatectomy should have a glucose tolerance test/HBA1C pre-op in close liaison with the diabetic team. We made the following suggestions. HBA1C at 1 month post surgery in 1st clinic follow up. HBA1C every 6 months thereafter or advice GP if they were to be discharged after benign disease surgery. Information charts are to be made available to the ward base and added to the induction pack.

Postnatal levels of glycated albumin and glycated hemoglobin A1c in mothers of large-for-gestational-age newborns

BackgroundGestational diabetes mellitus (GDM) is an important cause of macrosomia. The value of glycated albumin (GlyA) has been demonstrated to be a useful marker of glycemic control in pregnancy and a predictor of adverse perinatal outcomes. The aim of this study was to investigate the relationship between the postnatal levels of GlyA and glycated hemoglobin A1c (HbA1c) regarding the prenatal diagnosis of GDM in mothers of large-for-gestational-age (LGA) newborns.MethodsThe study included mothers and their LGA newborns born between July 2017 and September 2019. The mothers were grouped according to the prenatal diagnosis of GDM, and measurements of GlyA and HbA1c levels in their serum were performed on the first day after delivery of a LGA newborn.ResultsA total of 61 LGA newborns and their mothers were enrolled in the study. The median GlyA level was higher, at 16.4% (81.0 µmol/L), whereas the HbA1c level was lower in the group without a prenatal diagnosis of GDM; the differences between groups regarding the GlyA and HbA1c levels were not significant (p &amp;gt; 0.05). The postnatal level of maternal GlyA was positively correlated with birth weight (β = 0.022, p = 0.007), but no correlation with the presence of other adverse perinatal outcomes was found.ConclusionMothers of LGA newborns who were not diagnosed with GDM during pregnancy had higher median levels of GlyA and lower HbA1c levels than mothers with prenatal diagnosis of GDM. Values of GlyA in mothers were positively correlated with the birth weight of their newborns but no correlation with other adverse perinatal outcomes was found. Our results indicate the potential value of GlyA for screening of GDM in the last trimester of pregnancy.

Association between depression and diabetes among American adults using NHANES data from 2005 to 2020.

Depression impairs self-management in diabetic patients, exacerbates insulin resistance, and elevates glycated hemoglobin (HbA1c) levels, thereby increasing diabetes risk. This study analyzed data from 30,386 participants in the National Health and Nutrition Examination Survey (NHANES), assessing depression severity using the 9-item Patient Health Questionnaire (PHQ-9) and evaluating diabetes status through clinical markers such as HbA1c, random blood glucose, and fasting blood glucose. Participants were stratified by depression severity and diabetes status to examine the relationship between depression and diabetes risk. We applied descriptive statistics, logistic regression models, subgroup analyses, and restricted cubic spline (RCS) modeling to explore this association. The results revealed that greater depression severity was significantly associated with increased diabetes incidence, elevated HbA1c, fasting glucose, and insulin levels. Multivariate regression analysis confirmed a consistent positive correlation between depression severity and diabetes risk. Subgroup analyses further identified significant relationships between depression and various demographic and behavioral factors, including gender, race, BMI, smoking status, and prediabetic conditions. Additionally, the RCS model demonstrated a clear increase in diabetes risk with rising PHQ-9 scores. In conclusion, our study demonstrates that the severity of depression is positively correlated with the risk of diabetes, and this association may be closely linked to various glycemic and lipid metabolic parameters.

Abstract 4138477: Small Vessels, Big Challenges: Clinical and Demographic Correlates of Failure to Respond to Optimal Medical Therapy in Patients with Microvascular Angina

Background: Microvascular angina (MVA), resulting from coronary microvascular dysfunction, affects 40-50% of patients with exertional chest pain or dyspnea and a normal coronary angiogram. This condition significantly impairs quality of life and elevates the risk of major cardiac events, including myocardial infarction, stroke and death. MVA is classified as 'structural' (coronary flow reserve [CFR] &lt;2.5&amp;index of microcirculatory resistance [IMR] &gt;25) or 'functional' (CFR &lt;2.5&amp;IMR &lt;25). Current treatments are empirical, necessitating further investigation. Methods: This single-centre, retrospective study conducted in South Wales from 2019-24 examined MVA cases confirmed via national electronic health records. The Canadian Cardiovascular Society (CCS) angina grade was assessed at diagnosis and post optimal medical therapy (OMT) during clinic visits. Ordinal logistic regression was used to identify independent correlates of higher CCS grade, considering baseline LDL, age, diffuse epicardial disease, sex, hypertension, kidney function, smoking status and HbA1c levels as covariates. Results: Among 64 identified MVA cases (median age 69 yrs, IQR 61.3-77.8; 68.8% male), 81.3% had structural MVA, 6.3% functional MVA and 12.5% mixed disease. Coronary vessel testing was performed on 1, 2 or 3 vessels in 29.7% (n=19), 53.1% (n=34; 21 positive [+ve] in 2 vessels, 13 +ve in 1 vessel) and 17.2% (n=11; 5 +ve in 3 vessels, 5 +ve in 2 vessels, 1 +ve in 1 vessel) of cases, respectively. The LAD was most commonly affected vessel (82.8%). At diagnosis, 79.7% had CCS grade III or higher (Fig 1). Post OMT, 45.3% achieved CCS grade 0-I, 31.8% CCS grade II and 15.6% remained at CCS grade III (refractory angina). Medications included ranolazine (84.4%), beta-blockers (70.3%) and calcium channel blockers (28.1%). Ordinal logistic regression analysis (X 2 =0.27, p=0.033) identified baseline LDL (95% CI [0.16, 1.26]; p=0.011), age (95% CI [-0.12, -0.001]; p=0.045), diffuse epicardial disease (95% CI [0.016, 2.13]; p=0.047) and male sex (95% CI [0.066, 2.36]; p=0.038) as independent correlates of higher CCS grade, signifying poor response to OMT. Conclusion: MVA manifests regionally, underscoring the need for multi-territory testing. Although tailored OMT proved effective for many, 15.6% of patients continued to experience refractory symptoms (CCS grade III). This highlights the necessity for alternative therapeutic strategies to improve patient outcomes in this challenging condition.

Abstract 4131796: Non-Contact Biometric System for Early Detection of Hypertension and Diabetes Using AI and RGB Imaging

Introduction: In recent years, the development of wearable devices and bioinformation analysis applications utilizing smartphone sensors has seen significant advancements. Despite these technological strides, their adoption and sustained use remain limited to health-conscious individuals. The general populace, particularly those indifferent to health management, stands to miss out on the potential benefits of wearable technologies due to a lack of engagement. This disconnect underscores the necessity for more accessible health monitoring solutions. Research Questions and Goals: This study aims to bridge the gap in health monitoring accessibility by introducing a system capable of non-invasive, non-contact acquisition of biometric information. Such a system seeks to democratize the early detection and prevention of diseases across various demographics. Methods and Results: A prospective cohort clinical study was conducted in a hospital setting with approximately 200 consenting patients and healthy controls. Images of the subjects' faces and hands were captured with a high-speed camera, and blood pressure measurements were taken simultaneously for correlation. A machine learning algorithm was developed to analyze skin blood flow and spectral features from these images to identify potential diseases. The study specifically focused on early detection of hypertension and diabetes. Hypertension was categorized for individuals with systolic blood pressure ≥115 mmHg or diastolic blood pressure ≥75 mmHg. Diabetes was identified in subjects with HbA1c levels ≥6.5 or those previously diagnosed. The algorithm's performance in detecting hypertension showed a 94.2% in alignment with the AHA guidelines for stage1 hypertension, based on pulse wave features. For a subset including 40% early hypertension cases, accuracy rates were 86.2% for 30-second data segments and 80.9% for 5-second segments. For diabetes detection, the application of the algorithm to video data achieved a 75.3%, utilizing blood flow patterns as markers. Hypertension and diabetes were analyzed using different features. Conclusions: The integration of AI algorithms with video data analysis of skin and blood vessels demonstrates a promising avenue for the non-contact, early detection of hypertension and diabetes. This approach not only offers a viable non-contact monitoring technology, but also represents a significant leap towards inclusive, accessible health care prevention and management strategies.

Abstract 4138815: Prognostic Implications of Glycemic Variability Assessed by Continuous Glucose Monitoring-derived Coefficient of Variation among Patients Hospitalized for Acute Heart Failure

Background: Recent findings indicate that high glycemic variability (GV) could increase the risk of adverse outcomes in patients with cardiovascular disease. With the advances in technology, the utility of continuous glucose monitoring (CGM) has grown during recent years, which can provide valuable information that is not captured by HbA1c. We used the glucose coefficient of variation (CV, calculated as the ratio of standard deviation divided by the mean glucose level) of the obtained CGM data to analyze GV. Aims: We aimed to analyze CGM-derived CV as an indicator of GV and to evaluate prognostic implications of CGM-derived CV in patients hospitalized for acute heart failure (HF). Methods: Patients hospitalized for HF who had not been diagnosed diabetes were performed 75g-oral glucose tolerance test (OGTT). CV was evaluated using CGM system for at least 72 consecutive hours after being able to have meals stably during hospitalization. The primary outcome was a composite of cardiovascular death or re-hospitalization for HF. Patients were divided into two groups based on the median value of CV. Results: We prospectively analyzed 130 patients (mean age: 76±10 years, male 56%) admitted for acute HF. Following the 75g-OGTT, only 21% of the entire cohort exhibited normal glucose tolerance. During the median follow up period of 905 days, Kaplan–Meier curve analysis revealed that the cumulative incidence of the primary outcome event was significantly higher in patients with CV above median than in those with CV less than median (51.7% versus 24.4%, Log-rank P=0.01)(Figure). Multivariate Cox proportional analysis demonstrated that the risk of CV per 1% increment for the primary outcome was significant adjusted for history of diabetes, CGM-derived mean glucose level, and HbA1c level (hazard ratio: 1.06, 95% confidence interval 1.03–1.09). Conclusions: CGM-derived CV was associated with long term prognosis of patients hospitalized for HF with or without diabetes.

Abstract 4119052: Redefining the phenotypic continuum of cardiovascular disease using machine learning

Background: Current approaches that define cardiovascular disease rely on assignment of traditional diagnostic labels which may not reflect the natural continuum of phenotypic expression, influenced by genetic and environmental modifiers, or adequately identify groups with shared molecular mechanisms. Machine learning can leverage advances in genetic and imaging characterisation to reclassify phenotypic diversity along a continuum, from health to disease. Research Aims: Our study aims to build a tree-like classification of cardiovascular phenotypes in the community where branches represent subjects with shared features, ordered by their severity. Using dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) as exemplar conditions with opposing phenotypes, we aim to demonstrate the interaction between genetic and environmental modifiers of disease expression. Methods: We analysed cardiovascular magnetic resonance (CMR) imaging, electrocardiogram (ECG), biomarkers and clinical data from participants in the UK Biobank. Using unsupervised learning of multiparametric data, we built a tree of phenotypic expression. We projected the risk of DCM and HCM cases, and associated rare and common variant risk, onto the tree structure. Results: Ten main branches were discovered, using data from 41,525 participants (51.7 % female, median age 65 yrs [IQR: 58, 70]). The extremities of branches 1 and 6 were enriched for DCM cases (p &lt;0.05) and participants with reduced ejection fraction and high left ventricular volumes (p &lt;0.05). Compared with subjects at the tree centre, distal participants in branch 1 had increased blood pressure (BP) and body mass index (BMI), whilst those in branch 6 were more likely to have high HbA1c levels and carry a pathogenic DCM variant (p &lt;0.05). The extremity of branch 5 was enriched for HCM cases, rare sarcomeric variants (p = 0.004) and high polygenic risk (p &lt;0.001). Whilst the ends of branches 3 and 9 had high polygenic risk for HCM, they were less likely to have elevated BP and BMI, and had reduced likelihood of HCM expression, compared with branch 5. A phenomapping model was trained to accurately project unseen subjects onto the tree (R 2 0.98). Conclusions: We present a tree-like continuum of cardiovascular phenotypes, providing a novel framework for mechanistic discovery and exploration of genotype-phenotype associations. Phenomapping of unseen subjects enables personalised estimation of genetic and cardiovascular risk.