Cases Of Diabetes Research Articles

НАСЛЕДСТВЕННАЯ ТУБУЛОПАТИЯ: ФОСФАТ-ДИАБЕТ (Два клинических наблюдения)

Introduction. Phosphate diabetes is a representative of a group of diseases known as tubulopathies. It is more often of a hereditary nature. The disease manifests at an early age with symptoms similar to alimentary rickets, which creates problems for diagnosing and prescribing an adequate therapy. In this case, the current situation leads to the development of bone deformities and disability, delayed physical development, and the need for surgical treatment, which reduces the quality of life of the patients for a long time. Aim: To consider two clinical cases of phosphate diabetes with typical symptoms, demonstrate the diagnosing challenges, and analyze the treatment effects. Materials and Methods. Two clinical cases of phosphate diabetes are presented. The first patient: 16 years old, observed from the age of 2, and takes vitamin D and inorganic phosphates from the diagnosis date. The geneticist found the autosomal dominant of the pathology. The girl underwent two surgeries for her leg deformity. The second patient, 10 years old, was diagnosed at the age of 4 years. DNA diagnostics detected a mutation in the COL9A3 gene. They refused the complete DNA exome sequencing. From the diagnosis date, the patient is treated with the active vitamin D metabolite and inorganic phosphates. Results and Discussion. Clinician-observed: Patient 1 had leg deformities, painful legs, and disharmonious physical development caused by her growth retardation. Blood concentrations of calcium and phosphorus are within normal, there is hypocalciuria typical of phosphate diabetes in the urine, while phosphates are within normal. The patient’s kidney function is not impaired. Clinician-observed: Patient 2 is physically retarded, there are varus foot deformities and pes planovalgus feet. Kidney function is not impaired, the level of alkaline phosphatase is increased, the total blood calcium levels are decreased with phosphorus indicating normal values, and the urine phosphaturia and hypocalciuria are within normal ranges. Due to the COL9A3 mutation detected, Stickler syndrome was excluded. Orthopedic surgeon recommended surgical treatment of her leg deformities. Conclusions. The examination showed that the therapy allows keeping phosphate diabetes under control and avoiding the side effects of taking vitamin D.

IJCM_116A: Risk assessment of type II Diabetes mellitus using Indian Diabetic Risk Score among adults in a tertiary care hospital, Tamil Nadu - A cross sectional study

Background: Non-communicable diseases (NCD) kill 41 million people each year which accounts to 74% of all deaths globally. India ranks second with a diabetes population of 69.2 million and may rise to 123.5 million by 2040. Early detection of diabetes risk through periodic screening could be instrumental in controlling diabetes. Objectives: 1. To estimate the risk of type 2 diabetes mellitus among adults attending tertiary care hospital. 2. To assess correlation between INDIAN DIABETIC RISK SCORE(IDRS) and Random Capillary Blood Sugar (RBS). 1. To assess association between selected risk factors and risk of developing diabetes mellitus. Methodology: This study was done among 270 individuals aged 18 years and above attending NCD OPD in Madurai medical college, Tamil Nadu during November 2023. The sample size was calculated based on 40% global prevalence of moderate to high diabetic risk by Sarah Wild et al. Consecutive sampling was done. After obtaining informed consent, data was collected using semi structured questionnaire containing sociodemographic details, risk factors, and IDRS. Anthropometric measurements and RBS were done. The study excluded all known cases of Diabetes. Results: The mean age of the study participants was 42.25 years (SD 4.70). Majority (83.3%) were females. IDRS categorization showed 18.2%, 56.6% and 25.2% in the low, moderate and high-risk groups respectively. The study indicates moderate correlation (r=0.435) of IDRS and RBS values. Also, significant correlation (r=0.543) of IDRS with RBS in 18-30 age group. Age, waist circumference and body mass index (BMI) were significantly (P < 0.05) higher in the high-risk group. Conclusion: Screening of young adults by simple cost-effective tools like IDRS helps in further evaluation by blood investigations for early detection of diabetes, thereby preventing or delaying complications.

IJCM_279A: Evaluation of diabetes mellitus as a risk factor for urinary tract infection in women: A case control study

Background: Diabetes mellitus (DM) disrupts insulin production and function leads to hyperglycaemia and subsequently exacerbating the risk of complications. Studies highlight hyperglycaemia’s impact on neutrophil function, predisposing diabetic patients to severe infections like pneumonia, urinary tract infections (UTIs), and skin issues. Objectives: To quantify DM’s contribution to UTI development, and to assess the risk of contracting UTI conferred by diabetes mellitus in otherwise healthy women and to characterize the UTI in the cases. Methodology: The case control study was conducted among 200 participants (100 cases with UTI and 100 controls without UTI) from 3 hospitals affiliated to Kasturba Medical College, Mangalore. The data were collected using a structured proforma. Chi – square test and students ‘t’ test was used for comparison of the results across the groups. Results: Patients with urinary tract infections (UTI) showed a higher prevalence of diabetes mellitus (DM) (27.66%) compared to controls (7.45%). The UTI patients were 4.75 times more likely to have DM. Diabetic UTI cases exhibited elevated glycated haemoglobin (HbA1C) and random blood sugar levels than controls. Complicated UTIs were more prevalent in diabetic (77%) than non-diabetic (60%) UTI cases, with E. coli being the most common infecting organism. Conclusion: The uncontrolled diabetes mellitus confers an increased risk of developing UTI and the risk of developing UTI caused by organisms which are not known to cause infections in people with normal immunity (like Candida species). Additionally, diabetics show a higher proportion of complicated UTI cases as compared to non-diabetics.

Epidemiology of type 2 diabetes and prediabetes in the adult population of the Republic of Moldova (preliminary data)

Introduction. Type 2 DM accounts for over 95% of all diabetes cases worldwide and represents an important and independent cardio-metabolic risk factor. This is the first national study (Epidemiological study of widespread endocrine pathologies (diabetes, obesity) in the Republic of Moldova and its management strategy) that analyzes the prevalence of type 2 diabetes mellitus (DM), prediabetes, obesity, and dyslipidemia in the adult population of Moldova. Material and methods. This is an epidemiological cross-sectional study with cluster random sampling. A face-to-face interview was conducted with the participants using a pre-tested semi-structured questionnaire. All biochemical tests were performed in a certified laboratory. Statistical analysis used Spearman’s correlation test, chi-square, and Wilcoxon tests. The Research Ethics Committee of Nicolae Testemițanu State University of Medicine and Pharmacy (Minutes 3 from December 28 2020) approved this study. Results. 728 individuals were enrolled, of which 2.5% had unknown DM. Advanced age, obesity, and dyslipidemia were influencing factors for diabetes. 21.4% of participants had prediabetes, with a higher prevalence in men than in women (28.3 % versus 18.9 %). Only 23.2% of men and 30.4% of women had a BMI within the normal range. Abdominal circumference (AC) values greater than 102 cm and 88 cm in men and women, respectively, were determined in 39.4% of men and 53.8% of women. Conclusions. Our study showed an increased prevalence of carbohydrate metabolism disorders, including prediabetes, as well as a high prevalence of abdominal obesity. Persons with unknown diabetes mellitus have been identified.

Association between Toxoplasma gondii and gestational diabetes with regard to serum leptin and tumor necrosis factor alpha, a preliminary study

Gestational diabetes (GDM), the onset of any degree of glucose intolerance during pregnancy, increases a wide range of adverse health outcomes for both the mother and the fetus. The aim of the present study was to evaluate the association of Toxoplasma gondii infection with GDM in a case-control study with regard to the levels of leptin and tumor necrosis factor alpha (TNF-α) as two inflammatory biomarkers. Fifty-one pregnant diabetic cases and 109 controls were selected from a prenatal care clinic of a general hospital in Shiraz, southern Iran during July–November 2020. Cases and controls were similar in age, gestational age and number of parturitions. The presence of IgG antibodies against T. gondii, and serum concentrations of leptin and TNF-α were determined by ELISA. Anti-Toxoplasma antibodies were detected in 25 subjects (15.6 %, 95 % CI: 9.9–21.3). Nine (18 %) diabetic cases were infected with Toxoplasma compared to 16 (15 %) healthy controls (P = 0.63). Level of leptin was higher (P = 0.07) while TNF-α was lower in diabetic cases compared to healthy controls (P = 0.08). When subjects were classified according to the combination of GDM and T. gondii, leptin was significantly lower in healthy (non-diabetic, non-infected) subjects compared to diabetics (P = 0.026), and TNF-α was higher in healthy subjects compared to Toxoplasma-infected diabetics (P = 0.032). These findings can be interpreted as both comorbidities being individually associated with increasing serum leptin and decreasing TNF-α concentrations, with modifying effects on each other. The present study opens a new perspective on GDM and its complex pathophysiological mechanism. Future research in this area is needed to better understand the underlying pathway for the development of GDM and the role of T. gondii and inflammatory biomarkers.

EVALUATION OF THE EFFICACY OF ‘MADHUMEHARI CHURNA’ WITH ‘TRIPHALADI KWATHA’ IN THE MANAGEMENT OF MADHUMEHA W.S.R. TO DI-ABETES MELLITUS TYPE-2 (NIDDM)

Introduction: Diabetes Mellitus (DM) is commonly known as Madhumeha in Ayurveda. According to report of W.H.O., Diabetes is one of the largest global health emergencies of the 21st century. Incidence of DM is rising more rapidly in India. According to IDF SEA region, there were 69.1million cases of diabetes in India in 2015. So, effective treatment of diabetes is needed. Method: The present research work has been undertaken, to evaluate the efficacy of ‘Madhumehari churna’ with ‘Triphaladi kwatha’ in the management of Madhumeha W.S.R. to D.M. Type-2. The study was conducted on 15 clinically and pathologically diagnosed patients of Madhumeha [DM type 2]. The selection of patients was made from OPD/IPD of Arogyashala, National Institute of Ayurveda and SSBH, Jaipur (Raj.). The selected patients were given 15 registered patients of DM Type-2 (NIDDM) were administered Madhumehari churna and Triphaladi Kwatha for 30 days After evaluating therapy it was observed that the ‘Madhumehari Churna’ with ‘Triphaladi Kwatha’ showed symptomatic relief in the patients of Madhumeha.

Intelligent optimal control of nonlinear diabetic population dynamics system using a genetic algorithm

Diabetes is a chronic disease affecting millions of people worldwide. Several studies have been carried out to control the diabetes problem, involving both linear and non-linear models. However, the complexity of linear models makes it impossible to describe the diabetic population dynamic in depth. To capture more detail about this dynamic, non-linear terms were introduced into the mathematical models, resulting in more complicated models strongly consistent with reality (capable of re-producing observable data). The most commonly used methods for control estimation are Pantryagain’s maximum principle and Gumel’s numerical method. However, these methods lead to a costly strategy regarding material and human resources; in addition, diabetologists cannot use the formulas implemented by the proposed controls. In this paper, the authors propose a straightforward and well-performing strategy based on non-linear models and genetic algorithms (GA) that consists of three steps: 1) discretization of the considered non-linear model using classical numerical methods (trapezoidal rule and Euler–Cauchy algorithm); 2) estimation of the optimal control, in several points, based on GA with appropriate fitness function and suitable genetic operators (mutation, crossover, and selection); 3) construction of the optimal control using an interpolation model (splines). The results show that the use of the GA for non-linear models was successfully solved, resulting in a control approach that shows a significant decrease in the number of diabetes cases and diabetics with complications. Remarkably, this result is achieved using less than 70% of available resources.

Effects of statin therapy on diagnoses of new-onset diabetes and worsening glycaemia in large-scale randomised blinded statin trials: an individual participant data meta-analysis

Previous meta-analyses of summary data from randomised controlled trials have shown that statin therapy increases the risk of diabetes, but less is known about the size or timing of this effect, or who is at greatest risk. We aimed to address these gaps in knowledge through analysis of individual participant data from large, long-term, randomised, double-blind trials of statin therapy. We conducted a meta-analysis of individual participant data from randomised controlled trials of statin therapy that participated in the CTT Collaboration. All double-blind randomised controlled trials of statin therapy of at least 2 years' scheduled duration and with at least 1000 participants were eligible for inclusion in this meta-analysis. All recorded diabetes-related adverse events, treatments, and measures of glycaemia were sought from eligible trials. Meta-analyses assessed the effects of allocation to statin therapy on new-onset diabetes (defined by diabetes-related adverse events, use of new glucose-lowering medications, glucose concentrations, or HbA1c values) and on worsening glycaemia in people with diabetes (defined by complications of glucose control, increased use of glucose-lowering medication, or HbA1c increase of ≥0·5%). Standard inverse-variance-weighted meta-analyses of the effects on these outcomes were conducted according to a prespecified protocol. Of the trials participating in the CTT Collaboration, 19 trials compared statin versus placebo (123 940 participants, 25 701 [21%] with diabetes; median follow-up of 4·3 years), and four trials compared more versus less intensive statin therapy (30 724 participants, 5340 [17%] with diabetes, median follow-up of 4·9 years). Compared with placebo, allocation to low-intensity or moderate-intensity statin therapy resulted in a 10% proportional increase in new-onset diabetes (2420 of 39 179 participants assigned to receive a statin [1·3% per year] vs 2214 of 39 266 participants assigned to receive placebo [1·2% per year]; rate ratio [RR] 1·10, 95% CI 1·04-1·16), and allocation to high-intensity statin therapy resulted in a 36% proportional increase (1221 of 9935 participants assigned to receive a statin [4·8% per year] vs 905 of 9859 participants assigned to receive placebo [3·5% per year]; 1·36, 1·25-1·48). For each trial, the rate of new-onset diabetes among participants allocated to receive placebo depended mostly on the proportion of participants who had at least one follow-up HbA1c measurement; this proportion was much higher in the high-intensity than the low-intensity or moderate-intensity trials. Consequently, the main determinant of the magnitude of the absolute excesses in the two types of trial was the extent of HbA1c measurement rather than the proportional increase in risk associated with statin therapy. In participants without baseline diabetes, mean glucose increased by 0·04 mmol/L with both low-intensity or moderate-intensity (95% CI 0·03-0·05) and high-intensity statins (0·02-0·06), and mean HbA1c increased by 0·06% (0·00-0·12) with low-intensity or moderate-intensity statins and 0·08% (0·07-0·09) with high-intensity statins. Among those with a baseline measure of glycaemia, approximately 62% of new-onset diabetes cases were among participants who were already in the top quarter of the baseline distribution. The relative effects of statin therapy on new-onset diabetes were similar among different types of participants and over time. Among participants with baseline diabetes, the RRs for worsening glycaemia were 1·10 (1·06-1·14) for low-intensity or moderate-intensity statin therapy and 1·24 (1·06-1·44) for high-intensity statin therapy compared with placebo. Statins cause a moderate dose-dependent increase in new diagnoses of diabetes that is consistent with a small upwards shift in glycaemia, with the majority of new diagnoses of diabetes occurring in people with baseline glycaemic markers that are close to the diagnostic threshold for diabetes. Importantly, however, any theoretical adverse effects of statins on cardiovascular risk that might arise from these small increases in glycaemia (or, indeed, from any other mechanism) are already accounted for in the overall reduction in cardiovascular risk that is seen with statin therapy in these trials. These findings should further inform clinical guidelines regarding clinical management of people taking statin therapy. British Heart Foundation, UK Medical Research Council, and Australian National Health and Medical Research Council.

(PM-03) EPIDEMIOLOGICAL PROFILE OF PATIENTS UNDERGOING PENILE DOPPLER ULTRASOUND AT A FEDERAL UNIVERSITY HOSPITAL IN BRAZIL

Abstract Introduction Erectile Dysfunction (ED) refers to the inability to achieve or sustain a satisfactory erection for sexual intercourse. In Brazil, the estimated prevalence of ED among adults aged 40 to 70 years is 42.1%. For the evaluation of primary erectile dysfunction and preoperative assessment of Peyronie's disease, Penile Doppler ultrasound, involving drug-induced is recommended. This study aims to provide insights into the epidemiology of patients undergoing penile Doppler ultrasound at a Federal University Hospital. Methods This retrospective study gathered data from the electronic medical records of 179 patients who underwent the examination between March 2021 and March 2023, using the Phillips Affiniti 50G device. Pharmacological induction with 10 mcg/ml Alprostadil, 30 mg/ml Papaverine, and 1 mg/ml Phentolamine. Initially, 0.1 ml of this mixture was applied to the penile shaft, with subsequent adjustments made to achieve the best maximal erection. Results The participants ages ranged from 20 to 80 years, with an average of 59.8(±11,42) years. Marital status distribution showed 139 married and 40 were single. Ethnically, there were 57 white, 69 individuals of mixed race, and 39 black. The average Body Mass Index was 26.6(±4,13). The majority of patients identified as heterosexual (174 patients), with 51 cases of hypertension and 31 cases of diabetes. Additionally, 62 patients had radical prostatectomy. Out of the 134 patients that performed the exam with the report of erectile dysfunction, 54 were diagnosed with arterial insufficiency and 09 had venous leakage. Among the 42 exlcusive clinical report of Peyronie’s, 76% exhibited a uniplanar curvature located in the dorsal region. The average curvature angle was 47°(±19,5). Conclusion Erectile dysfunction was significantly more prevalent than Peyronie's disease. Among Peyronie's patients, uniplanar curvature, especially in the dorsal region, was the most common deformity type. Financing No conflict.

Immunopathogenesis and detection methods of type 2 diabetes

Diabetes is a disease that is increasingly prevalent on a global scale. Type 2 diabetes (T2D) accounts for 90% of all diabetes cases and is a chronic condition primarily influenced by factors such as obesity and genetics. This condition often leads to the development of various cardiovascular diseases. A diverse of different detection methods for the T2D have been developed and achieved good detection and analysis results. In addition, numerous studies have indicated a close connection between T2D and immune inflammation. This research primarily introduces the current status of diabetes, provides a detailed summary of the connection betweenT2D and the immune system, and presents novel immune biomarkers related to T2D. Some new immunological testing methods will be analyzed in this research. In the future, there is hope that these new biomarkers can be used to design more advantageous therapeutic drugs for diabetes patients and more convenient, sensitive, and low-cost detection methods.

Modelling of Diabetic Cases for Effective Prevalence Classification

INTRODUCTION: This study compares and contrasts various machine learning algorithms for predicting diabetes. The study of current research work is to analyse the effectiveness of various machine learning algorithms for diabetes prediction.
 OBJECTIVES: To compare the efficacy of various machine learning algorithms for diabetic prediction.
 METHODS: For the same, a diabetic dataset was subjected to the application of various well-known machine learning algorithms. Unbalanced data was handled by pre-processing the dataset. The models were subsequently trained and assessed using different performance metrics namely F1-score, accuracy, sensitivity, and specificity.
 RESULTS: The experimental results show that the Decision Tree and ensemble model outperforms all other comparative models in terms of accuracy and other evaluation metrics.
 CONCLUSION: This study can help healthcare practitioners and researchers to choose the best machine learning model for diabetes prediction based on their specific needs and available data.

Abstract P305: Room for Improved Secondary Prevention of Major Cardiovascular Events Among the Population With New Onset Diabetes: A Longitudinal Latent Class Trajectory Analysis

Background: After a diagnosis of diabetes, specialist physicians may play a key role in the secondary prevention of major cardiovascular events (MACE). Yet, trajectories of visits to specialists are heterogenous and their efficacy in the prevention of MACE remains unexplored. Goal: To assess whether trajectories of visits to specialists are associated with MACE among new cases of diabetes. Methods: Using the Quebec Integrated Chronic Disease Surveillance System, we identified new cases of diabetes ≥20 years old during fiscal year 2013, who had no prior history of MACE (ischemic cardiopathy, stroke, myocardial infarction or cardiovascular death). Firstly, individual trajectories according to the presence/absence of ≥1 ambulatory visit to a specialist (cardiologist, internist, endocrinologist) were compiled over consecutive 3-month periods up to 2 years following diagnosis. Patients with no visit were compiled in a “primary care only” group, while others were classified in groups using latent class growth analysis. Patients who had a MACE during this period were excluded. Secondly, the risk of MACE occuring after the 2 years following diagnosis up to December 31 st 2019 was compared between groups using a marginal Cox proportional hazards regression model, adjusted with inverse probability weighting and providing adjusted hazard ratio (aHR) with 95% confidence intervals (CI). Results: Among the 24,782 patients included, 5 groups were identified ( Figure 1 ). A total of 2,837 MACE occurred. Compared with the “primary care only group”, those who consulted a specialist were at higher risk of MACE (Regular/frequent visits: aHR: 1.50 [95% CI: 1.26 to 1.66]; Late visits: aHR: 1.41 [1.13 to 1.73]; Regular/sparce visits: 1.38 [1.27 to 1.51]; Early visits: 1.36 [1.19 to 1.54]), while no difference was observed between these groups. Conclusions: Although confounding by indication cannot be totally ruled out, these results may suggest room for improvement in the secondary prevention of MACE after a diabetes diagnosis.

Abstract P428: Risk-Based Approach to Defining Prediabetes Among Middle-Aged Adults in the Atherosclerosis Risk in Communities (ARIC) Study

Introduction: Current prediabetes definitions, based on fasting blood glucose (FG) or HbA1c, are broad and capture many individuals who will never develop diabetes. Other risk factors including age, sex, body mass index (BMI), systolic blood pressure (SBP), and family history of diabetes, are not part of current definitions but are highly predictive of progression from prediabetes to diabetes. We evaluated whether approaches to defining prediabetes that incorporate standard clinical measures can improve 10-year diabetes risk prediction. Methods: We conducted a prospective analysis of 11,322 participants in the Atherosclerosis Risk in Communities (ARIC) Study aged 46-70 years (55% women, ~20% Black adults) without diabetes at baseline (1990-1992). We used logistic regression to develop risk equations for incident diabetes over ~10-year based on combinations of HbA1c, FG, and/or clinical measures (age, sex, BMI, SBP, family history of diabetes). We calculated area under the curve (AUC) for 10-year diabetes risk, comparing American Diabetes Association (ADA) prediabetes definitions (HbA1c 5.7-6.4%, FG 100-125 mg/dL, either, or both) with our new risk equations. Results: Over ~10 years of follow-up, there were 1230 incident cases of diabetes. The ~10-year absolute diabetes risk for persons with HbA1c 5.7-6.4% was 27% (AUC=0.66) and for persons with an FG of 100-125 mg/dL was 16% (AUC=0.64). Risk equations combining FG and HbA1c yielded an AUC of 0.76. The additional inclusion of all 5 clinical measures increasing the AUC to 0.78 (ΔAUC=0.02; p<0.001). Simple clinical measures, primarily BMI, led to modest improvements in risk discrimination when added to HbA1c alone (ΔAUC=0.03; p<0.001) or FG alone (ΔAUC=0.03; p<0.001). Conclusions: Defining prediabetes based on both an elevated FG and elevated HbA1c (confirmatory definition) or using clinical variables (age, sex, BMI, SBP, family history) added to either FG or HbA1c can substantially improve our ability to identify middle-aged adults who will progress to diabetes.

Diabetes mellitus and associated risk factors among HIV infected patients on HAART

BackgroundUnderstanding the impact of disease associations is becoming a priority in Kenya and other countries bearing the load of infectious diseases. With the increased incidences of non-communicable diseases and the endemicity of infectious diseases in Sub-Saharan Africa, their co-existence poses significant challenges to patients, health workers and an overwhelmed health sector. Classical risk factors for diabetes such as physical inactivity and unhealthy diet may not solely explain the current trends, suggesting the role of novel risk factors including infections/inflammation. HIV and its treatment have been identified as potential contributors especially to patients with family history of confirmed diabetes cases. Co-infections frequently observed during HIV infection also significantly influence both the epidemiological and pathophysiological of the link between HIV and diabetes. Understanding the correlates of HIV and diabetes is crucial to inform management and prevention strategies of the twin infections. We therefore aimed to determine the prevalence of diabetes mellitus and risk factors in a population of HIV infected patients on HAART. This study determined the association of diabetes/impaired glucose regulation in the context of HIV-1. A cross-sectional study was conducted at a comprehensive care clinic in Nairobi (Kenya). Participants were screened for diabetes and impaired glucose regulation using random blood glucose and glycated haemoglobin (HbA1c) This paper describes the prevalence of diabetes mellitus in Human Immunodeficiency Virus positive individuals and the associated risk factors. We have demonstrated that family history is a risk factor for diabetes. While age and BMI are known risk factors, they were not associated with diabetes in this study.

Abstract 31: Energy Intake and Dietary Glycemic Load in Late Morning and Risk of Type 2 Diabetes: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Introduction: Meal timing may affect type 2 diabetes risk due to the circadian regulation of glucose metabolism. However, the optimal meal timing for lowering diabetes risk remains unknown. Objective and Hypothesis: We aimed to identify the optimal meal timing for diabetes prevention. Since glucose tolerance peaks in the morning, we hypothesized that eating more in the morning is associated with a lower risk of diabetes when daily diet quantity and quality are held constant. Methods: We included 7716 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) who were free of diabetes at baseline (2008-2011) and attended clinic visit 2 (2014-2017). Incident diabetes was identified during the annual phone follow-up (through self-reported diabetes) or at visit 2 (through self-reported diabetes or antihyperglycemic medication usage or laboratory tests using the ADA criteria). Dietary intakes at baseline were assessed using two 24-hour dietary recalls, and meal timing was categorized into early morning (6:00-8:59 AM), late morning (9:00-11:59 AM), afternoon (12:00-5:59 PM), evening (6:00-11:59 PM), and night (0:00-5:59 AM). We calculated energy intake (EI) in kilocalories and energy-adjusted glycemic load (GL) in each meal timing. We estimated their associations with incident diabetes using the Cox proportional hazards models, accounted for the HCHS/SOL complex survey design and adjusted for age, sex, field center, Hispanic/Latino background, income, education, smoking, alcohol intake, sleep duration, physical activity, BMI, family history of diabetes, hypertension, dyslipidemia, total energy intake, and diet quality (Health Eating Index for energy intake in each meal timing as the exposure; total GL and fiber intake for GL in each meal timing as the exposure). Results: At baseline, the analytic population had a mean (SE) age of 39.0 (0.3) years, and 50.9% were female. Over a median (range) follow-up of 5.8 (0.8-9.6) years, 1,262 incident diabetes cases were documented. EI and GL exhibited strong positive correlations throughout the day. EI and GL in late morning were inversely associated with diabetes risk, whereas those in other meal timings were not associated with diabetes risk. In fully adjusted models, the hazard ratios (HRs) of diabetes were 0.94 (95% CI: 0.91 to 0.97) for a 100-kcal increase of EI and 0.93 (0.89 to 0.97) for a 10-unit increase of GL in late morning. The associations were stronger and showed a linear dose-response relationship in males and adults with overweight/obesity. Replacing energy intake or GL, from early morning, afternoon, or evening with late morning equivalents was associated with comparable reductions in diabetes risk. Conclusions: This study identifies late morning as a favorable meal timing for lowering diabetes risk in Hispanic/Latino adults, providing a novel perspective on type 2 diabetes prevention that warrants confirmation.

Longitudinal assessment of classic and 11-oxygenated androgen concentrations and their association with type 2 diabetes mellitus development: the Tromsø study

AimWe aimed to investigate changes in pre-diagnostic concentrations of classic and 11-oxygenated androgens in type 2 diabetes (T2DM) cases and healthy controls, associations between androgen concentrations and T2DM, and the potential for androgens to improve the prediction of T2DM when considered in combination with established risk factors.MethodsAndrogen concentrations were analysed in serum samples from 116 T2DM cases and 138 controls at 3, pre-diagnostic time-points: 1986/87 (T1), 1994/95 (T2), and 2001 (T3). Generalised estimating equations were used to longitudinally examine androgen concentrations, and logistic regression models were used to estimate the odds ratios (OR) of T2DM at each time-point. Logistic regression models were also used to calculate area under the receiver operating characteristics curve (AROC) from models including established risk factors alone (ERF model) and established risk factors plus each androgen, respectively, which were compared to identify improvements in predictive ability.ResultsFor women, no significant associations were observed between any of the investigated androgens and T2DM after adjusting for confounders. For men, after adjusting for confounders, concentrations of all investigated 11-oxygenated androgens were higher in cases than controls at one or several time-points. We observed associations between T2DM and concentrations of 11-ketoandrostenedione (OR: 1.59) and 11-ketotestosterone (OR: 1.62) at T1; and 11-hydroxyandrostenedione (OR: 2.00), 11-hydroxytestosterone (OR: 1.76), 11-ketoandrostenedione (OR: 1.84), 11-ketotestosterone (OR: 1.78) and testosterone (OR: 0.45) at T3 in men. The addition of these androgens (including 11-hydroxytestosterone at T2) to the ERF model resulted in an improved ability to predict T2DM in men (AROC: 0.79–0.82). We did not observe significant differences in changes in androgen concentrations over time between cases and controls in either sex.ConclusionOur results demonstrate that testosterone and 11-oxygenated androgens are associated with T2DM in men before diagnosis and may be potential biomarkers in T2DM risk assessment.

Predictive value of insulin resistance surrogates for the development of diabetes in individuals with baseline normoglycemia: findings from two independent cohort studies in China and Japan

BackgroundInsulin resistance (IR) plays a crucial role in the occurrence and progression of diabetes. This study aimed to evaluate and compare the predictive value of four IR surrogates, including the triglycerides glucose (TyG) index, TyG and body mass index (TyG-BMI), triglycerides/high-density lipoprotein cholesterol (TG/HDL-C) ratio, and the metabolic score for IR (MetS-IR) for diabetes in two large cohorts.MethodsA total of 116,661 adult participants from the China Rich Healthcare Group and 15,464 adult participants from the Japanese NAGALA cohort were included in the study. Multivariable Cox proportional hazards models were used to assess the standardized hazard ratio (HR) of the TyG index, TyG-BMI, TG/HDL-C ratio, and MetS-IR directly associated with diabetes. Receiver operating characteristic (ROC) curve and time-dependent ROC curve analysis were performed to evaluate and compare the predictive value of the four IR surrogates for diabetes.ResultsIn the two independent cohorts, the average follow-up time was 3.1 years in the China cohort, with 2681(2.30%) incident cases of diabetes recorded, and 6.13 years in the Japan cohort, with 373 incident cases (2.41%) of diabetes recorded. After adjusting for potential confounding factors, we found that among the four IR surrogates, TyG-BMI and MetS-IR showed stronger associations with diabetes. The stronger associations persisted even after further stratification by age, sex, hypertension, and obese subgroups. In terms of diabetes prediction, based on ROC analysis, TyG-BMI demonstrated the highest predictive accuracy for diabetes in the Chinese population, while both TyG-BMI and MetS-IR showed the highest predictive accuracy in the Japanese population. The results of further subgroup ROC analysis confirmed the robustness of these findings. Furthermore, the time-dependent ROC results indicated that among the four IR surrogates, MetS-IR exhibited the highest accuracy in predicting future diabetes at various time intervals in the Japanese population.ConclusionOur findings suggest that evaluating TyG-BMI and MetS-IR as IR surrogates may be the most useful for predicting diabetes events and assessing the risk of developing diabetes in East Asian populations.

Intensity of statin therapy and primary prevention of cardiovascular in Korean patients with dyslipidemia.

This study aimed to investigate the association between the intensity of statin therapy and the development of cardiovascular disease (CVD) and diabetes in individuals without prior diabetes who were being treated for dyslipidemia with statins for the primary prevention of CVD, using the National Health Insurance Service-Health Screening database. The database is a longitudinal cohort study of Korean men and women 40 years of age or older who underwent comprehensive biannual screening health examinations by Korean National Health Insurance Service from January 1, 2002, to December 31, 2015. We included patients in the health screening checkup cohort who underwent health checkups in 2009 and 2010.The primary outcome was the occurrence of a first major cardiovascular or cerebrovascular event, new-onset diabetes. A total of 20,322 participants without prior diabetes at baseline from 2009 to 2015 were followed up for a mean duration of 81.2 ± 6.6 months. The mean age of all participants at baseline was 59.2 ± 8.4 years and 43.0% of them were male. Their index low lipoprotein cholesterol level was 130.4 ± mg/dL, the mean duration of taking statins was 337.4 ± 52.3 days, and 93.9% of them had been taking moderate-intensity statins. At that time, a total of 641 diabetes cases occurred, 41 from using low-intensity statins, 588 from moderate-intensity statins, and 11 from high-intensity statins. The results indicated no significant differences in the incidence of death, CVD death, or CVD among those in the strong statin group compared with the reference groups. While statin treatment for the primary prevention of CVD in patients with dyslipidemia showed a subtle difference in the incidence of diabetes, there was no difference in the occurrence of CVD or CVD death according to statin intensity.

Analysis of diabetes based on Tree Decision, Logistic Regression and Artificial Neural Network

The alarming rise in diabetes cases globally, particularly amongst the aging population, underscores a pressing need for innovative, accurate, and early diagnostic tools. Amidst this health crisis, the present study delves into the evaluation of three prominent machine learning in predicting diabetes using the Pima Indians Diabetes Database. A comprehensive analysis, considering metrics such as accuracy, precision, recall, F1 score, and ROC curve, revealed Decision Trees as the most efficacious, exhibiting adeptness in balancing precision and recall. Artificial Neural Networks displayed a remarkable ability to identify true positive cases, making it a notable contender in medical diagnostics. In terms of accuracy, Decision Trees led with a rate of 76.19%, followed by Logistic Regression at 74.03%, and Artificial Neural Networks trailing at 72.64%. The findings suggest Decision Trees' potential utility in offering both a nuanced and comprehensive approach to diabetes prediction. However, the constraints imposed by the dataset, and the inherent limitations and sensitivities of the machine learning models, call for a judicious interpretation of the results. This research illuminates the prospective integration of machine learning in healthcare for enhanced, personalized, and timely diabetes management, paving the way for improved patient outcomes and a substantial reduction in global health disparities attributed to diabetes.

Roles of fibroblast growth factors in the treatment of diabetes.

Diabetes affects about 422 million people worldwide, causing 1.5 million deaths each year. However, the incidence of diabetes is increasing, including several types of diabetes. Type 1 diabetes (5%-10% of diabetic cases) and type 2 diabetes (90%-95% of diabetic cases) are the main types of diabetes in the clinic. Accumulating evidence shows that the fibroblast growth factor (FGF) family plays important roles in many metabolic disorders, including type 1 and type 2 diabetes. FGF consists of 23 family members (FGF-1-23) in humans. Here, we review current findings of FGFs in the treatment of diabetes and management of diabetic complications. Some FGFs (e.g., FGF-15, FGF-19, and FGF-21) have been broadly investigated in preclinical studies for the diagnosis and treatment of diabetes, and their therapeutic roles in diabetes are currently under investigation in clinical trials. Overall, the roles of FGFs in diabetes and diabetic complications are involved in numerous processes. First, FGF intervention can prevent high-fat diet-induced obesity and insulin resistance and reduce the levels of fasting blood glucose and triglycerides by regulating lipolysis in adipose tissues and hepatic glucose production. Second, modulation of FGF expression can inhibit renal and cardiac fibrosis by regulating the expression of extracellular matrix components, promote diabetic wound healing process and bone repair, and inhibit cancer cell proliferation and migration. Finally, FGFs can regulate the activation of glucose-excited neurons and the expression of thermogenic genes.