Chronic complications in patients with newly diagnosed type 2 diabetes: prevalence and related metabolic and clinical features: the Verona Newly Diagnosed Type 2 Diabetes Study (VNDS) 9

Optimal Glycated Hemoglobin Cutoff for Diagnosis of Diabetes and Prediabetes in Chinese Breast Cancer Women

Purpose

Glycated hemoglobin (HbA1c) is widely used in diabetes management and now recommended for diagnosis and risk assessment. Our research focused on investigating the optimal cutoff points of HbA1c for diagnosis of diabetes and prediabetes in Chinese breast cancer women, aiming to enhance early detection and tailor treatment strategies.

Patients and Methods

This study involved 309 breast cancer women without diabetes history in China. Patients were categorized into groups of newly diagnosed diabetes, prediabetes, and normal glucose tolerance using oral glucose tolerance test (OGTT) according to the 2010 ADA criteria. HbA1c data were collected from all patients. Receiver operating characteristic (ROC) curve analysis was used to assess the effectiveness of the HbA1c screening.

Results

Among the 309 breast cancer women without diabetes history, 96 (31.0%) were identified with diabetes and 130 (42.1%) had prediabetes according to OGTT, and the incidence of normal glucose tolerance was only 26.9% (83). ROC curve analysis, using OGTT as a reference, revealed that the area under the curve of 0.903 (P<0.001, 95% CI, 0.867-0.938) for HbA1c alone, indicating high accuracy. The optimal HbA1c cutoff for identifying diabetes was determined to be 6.0%, with a sensitivity of 78.1% and specificity of 86.4%. For prediabetes, the ROC curve for HbA1c alone showed that the area under the ROC curve of 0.703 (P<0.001, 95% CI, 0.632-0.774), with an optimal cutoff of 5.5% (sensitivity of 76.9% and specificity of 51.8%).

Conclusion

The prevalence of undiagnosed diabetes is very high in breast cancer women without diabetes history in China. The optimal cutoff points of HbA1c for identifying diabetes and prediabetes are 6.0% and 5.5% in Chinese breast cancer women, respectively.

Predictors of microvascular complications in patients with type 2 diabetes mellitus at regional referral hospitals in the central zone, Tanzania: a cross-sectional study

Microvascular complications encompass a group of diseases which result from long-standing chronic effect of diabetes mellitus (DM). We aimed to determine the prevalence of microvascular complications and associated risk factors among patients with type 2 diabetes mellitus (T2DM). A cross-sectional analytical hospital-based study was conducted at Singida and Dodoma regional referral hospitals in Tanzania from December 2021 to September 2022. A total of 422 patients with T2DM were included in the analysis by determining the prevalence of microvascular complications and their predictors using multivariable logistic regression analysis. A two-tailed p value less than 0.05 was considered statistically significant. The prevalence of microvascular complications was 57.6% (n = 243) and diabetic retinopathy was the most common microvascular complication which accounted for 21.1% (n = 89). Having irregular physical activity (AOR = 7.27, 95% CI = 2.98-17.71, p < 0.001), never having physical activity (AOR = 2.38, 95% CI = 1.4-4.01, p = 0.013), being hypertensive (AOR = 5.0, 95% CI = 2.14-11.68, p = 0.030), having T2DM for more than 5 years (AOR = 2.74, 95% CI = 1.42-5.26, p = 0.025), being obese (AOR = 2.63, 95% CI = 1.22-5.68, p = 0.010), and taking anti-diabetic drugs irregularly (AOR = 1.94, 95% CI = 0.15-0.77, p < 0.001) were the predictors of microvascular complications. This study has revealed a significant proportion of microvascular complications in a cohort of patients with T2DM. Lack of regular physical activity, being obese, taking anti-diabetic drugs irregularly, presence of hypertension, and long-standing duration of the disease, were significantly associated with microvascular complications.

Correlates of Skeletal Muscle Mass and Differences Between Novel Subtypes in Recent-Onset Diabetes

CONTEXT

Low skeletal muscle mass (SMM) is associated with long-standing diabetes but little is known about SMM in newly diagnosed diabetes.

OBJECTIVE

We aimed to identify correlates of SMM in recent-onset diabetes and to compare SMM between novel diabetes subtypes.

METHODS

SMM was normalized to body mass index (SMM/BMI) in 842 participants with known diabetes duration of less than 1 year from the German Diabetes Study (GDS). Cross-sectional associations between clinical variables, 79 biomarkers of inflammation, and SMM/BMI were assessed, and differences in SMM/BMI between novel diabetes subtypes were analyzed with different degrees of adjustment for confounders.

RESULTS

Male sex and physical activity were positively associated with SMM/BMI, whereas associations of age, BMI, glycated hemoglobin A1c, homeostatic model assessment for β-cell function, and estimated glomerular filtration rate with SMM/BMI were inverse (all P < .05; model r2 = 0.82). Twenty-three biomarkers of inflammation showed correlations with SMM/BMI after adjustment for sex and multiple testing (all P < .0006), but BMI largely explained these correlations. In a sex-adjusted analysis, individuals with severe autoimmune diabetes had a higher SMM/BMI whereas individuals with severe insulin-resistant diabetes and mild obesity-related diabetes had a lower SMM/BMI than all other subtypes combined. However, differences were attenuated after adjustment for the clustering variables.

CONCLUSION

SMM/BMI differs between diabetes subtypes and may contribute to subtype differences in disease progression. Of note, clinical variables rather than biomarkers of inflammation explain most of the variation in SMM/BMI.

Estimation of the onset time of diabetic complications in type 2 diabetes patients in Thailand: a survival analysis

BACKGROUND

This study aimed to identify factors associated with the onset time of diabetic complications in patients with type 2 diabetes mellitus (T2DM) and determine the best-fitted survival model.

METHODS

A retrospective cohort study was conducted among T2DM patients enrolled from October 1, 2016 to July 15, 2020 at the National Health Security Office (NHSO). In total, 388 T2DM patients were included. Cox proportional-hazard and parametric models were used to identify factors related to the onset time of diabetic complications. The Akaike information criterion, Bayesian information criterion, and Cox-Snell residual were compared to determine the best-fitted survival model.

RESULTS

Thirty diabetic complication events were detected among the 388 patients (7.7%). A 90% survival rate for the onset time of diabetic complications was found at 33 months after the first T2DM diagnosis. According to multivariate analysis, a duration of T2DM ≥42 months (time ratio [TR], 0.56; 95% confidence interval [CI], 0.33-0.96; p=0.034), comorbid hypertension (TR, 0.30; 95% CI, 0.15-0.60; p=0.001), mildly to moderately reduced levels of the estimated glomerular filtration rate (eGFR) (TR, 0.43; 95% CI, 0.24-0.75; p=0.003) and an eGFR that was severely reduced or indicative of kidney failure (TR, 0.38; 95% CI, 0.16-0.88; p=0.025) were significantly associated with the onset time of diabetic complications (p<0.05).

CONCLUSION

Patients with T2DM durations of more than 42 months, comorbid hypertension, and decreased eGFR were at risk of developing diabetic complications. The NHSO should be aware of these factors to establish a policy to prevent diabetic complications after the diagnosis of T2DM.

Detection of diabetic patients in people with normal fasting glucose using machine learning

BACKGROUND

Diabetes mellitus (DM) is a chronic metabolic disease that could produce severe complications threatening life. Its early detection is thus quite important for the timely prevention and treatment. Normally, fasting blood glucose (FBG) by physical examination is used for large-scale screening of DM; however, some people with normal fasting glucose (NFG) actually have suffered from diabetes but are missed by the examination. This study aimed to investigate whether common physical examination indexes for diabetes can be used to identify the diabetes individuals from the populations with NFG.

METHODS

The physical examination data from over 60,000 individuals with NFG in three Chinese cohorts were used. The diabetes patients were defined by HbA1c ≥ 48 mmol/mol (6.5%). We constructed the models using multiple machine learning methods, including logistic regression, random forest, deep neural network, and support vector machine, and selected the optimal one on the validation set. A framework using permutation feature importance algorithm was devised to discover the personalized risk factors.

RESULTS

The prediction model constructed by logistic regression achieved the best performance with an AUC, sensitivity, and specificity of 0.899, 85.0%, and 81.1% on the validation set and 0.872, 77.9%, and 81.0% on the test set, respectively. Following feature selection, the final classifier only requiring 13 features, named as DRING (diabetes risk of individuals with normal fasting glucose), exhibited reliable performance on two newly recruited independent datasets, with the AUC of 0.964 and 0.899, the balanced accuracy of 84.2% and 81.1%, the sensitivity of 100% and 76.2%, and the specificity of 68.3% and 86.0%, respectively. The feature importance ranking analysis revealed that BMI, age, sex, absolute lymphocyte count, and mean corpuscular volume are important factors for the risk stratification of diabetes. With a case, the framework for identifying personalized risk factors revealed FBG, age, and BMI as significant hazard factors that contribute to an increased incidence of diabetes. DRING webserver is available for ease of application ( http://www.cuilab.cn/dring ).

CONCLUSIONS

DRING was demonstrated to perform well on identifying the diabetes individuals among populations with NFG, which could aid in early diagnosis and interventions for those individuals who are most likely missed.

Pathophysiological Effects of Contemporary Lifestyle on Evolutionary-Conserved Survival Mechanisms in Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is increasingly being characterized as an evolutionary mismatch disorder that presents with a complex mixture of metabolic and endocrine symptoms. The Evolutionary Model proposes that PCOS arises from a collection of inherited polymorphisms that have been consistently demonstrated in a variety of ethnic groups and races. In utero developmental programming of susceptible genomic variants are thought to predispose the offspring to develop PCOS. Postnatal exposure to lifestyle and environmental risk factors results in epigenetic activation of developmentally programmed genes and disturbance of the hallmarks of health. The resulting pathophysiological changes represent the consequences of poor-quality diet, sedentary behaviour, endocrine disrupting chemicals, stress, circadian disruption, and other lifestyle factors. Emerging evidence suggests that lifestyle-induced gastrointestinal dysbiosis plays a central role in the pathogenesis of PCOS. Lifestyle and environmental exposures initiate changes that result in disturbance of the gastrointestinal microbiome (dysbiosis), immune dysregulation (chronic inflammation), altered metabolism (insulin resistance), endocrine and reproductive imbalance (hyperandrogenism), and central nervous system dysfunction (neuroendocrine and autonomic nervous system). PCOS can be a progressive metabolic condition that leads to obesity, gestational diabetes, type two diabetes, metabolic-associated fatty liver disease, metabolic syndrome, cardiovascular disease, and cancer. This review explores the mechanisms that underpin the evolutionary mismatch between ancient survival pathways and contemporary lifestyle factors involved in the pathogenesis and pathophysiology of PCOS.

Insights into Insulin Resistance and Calcification in the Myocardium in Type 2 Diabetes: A Coronary Artery Analysis

Type 2 diabetes (T2D) is responsible for high incidence of cardiovascular (CV) complications leading to heart failure. Coronary artery region-specific metabolic and structural assessment could provide deeper insight into the extent of the disease and help prevent adverse cardiac events. Therefore, in this study, we aimed at investigating such myocardial dynamics for the first time in insulin-sensitive (mIS) and insulin-resistant (mIR) T2D patients. We targeted global and region-specific variations using insulin sensitivity (IS) and coronary artery calcifications (CACs) as CV risk factor in T2D patients. IS was computed using myocardial segmentation approaches at both baseline and after an hyperglycemic-insulinemic clamp (HEC) on [¹⁸F]FDG-PET images using the standardized uptake value (SUV) (ΔSUV = SUV_HEC - SUV_BASELINE) and calcifications using CT Calcium Scoring. Results suggest that some communicating pathways between response to insulin and calcification are present in the myocardium, whilst differences between coronary arteries were only observed in the mIS cohort. Risk indicators were mostly observed for mIR and highly calcified subjects, which supports previously stated findings that exhibit a distinguished exposure depending on the impairment of response to insulin, while projecting added potential complications due to arterial obstruction. Moreover, a pattern relating calcification and T2D phenotypes was observed suggesting the avoidance of insulin treatment in mIS but its endorsement in mIR subjects. The right coronary artery displayed more ΔSUV, whilst plaque was more present in the circumflex. However, differences between phenotypes, and therefore CV risk, were associated to left descending artery (LAD) translating into higher CACs regarding IR, which could explain why insulin treatment was effective for LAD at the expense of higher likelihood of plaque accumulation. Personalized approaches to assess T2D may lead to more efficient treatments and risk-prevention strategies.

Risk Factors for Glycemic Control in Hospitalized Patients with Type 2 Diabetes Receiving Continuous Subcutaneous Insulin Infusion Therapy

INTRODUCTION

Patients with diabetes are confronted with numerous obstacles to achieve adequate glycemic control during hospitalization. The aim of this study was to explore the risk factors associated with glycemic control in hospitalized patients with type 2 diabetes mellitus (T2DM) treated with continuous subcutaneous insulin infusion (CSII).

METHODS

This cross-sectional study included 5223 patients hospitalized with T2DM in a tertiary hospital in Xiamen (China) between January 2017 and December 2019. All patients were managed according to established protocols for glycemic monitoring and insulin pump treatment regimens. Demographic information and clinical profiles were collected from electronic health records. Multiple linear regression analysis was used to identify the risk factors associated with glycemic control.

RESULTS

Among the 5223 hospitalized patients with T2DM receiving CSII therapy, 55.2% achieved their ideal blood glucose level (3.9-10.0 mmol/L), 44.5% experienced hyperglycemia (> 10.0 mmol/L), and 0.3% experienced hypoglycemia (< 3.9 mmol/L) during their hospitalization. Multivariate analyses showed that among inpatients with T2DM, older age, male gender, higher low-density lipoprotein-cholesterol (LDL-C) level, lower C-peptide (C-P) level, lower body mass index (BMI), longer duration of diabetes, previous insulin prescriptions, nephropathy, and retinopathy were factors more likely to be associated with a blood glucose level in the hyperglycemic range (P < 0.05). We also observed that among hospitalized patients with T2DM, those with lower BMI, lower C-P, lower LDL-C, longer disease duration, and previous insulin prescriptions were more likely to correlate with a higher proportion of hypoglycemia range (all P < 0.05).

CONCLUSION

Older age, male gender, lower BMI, lower C-P, higher LDL-C, previous insulin prescriptions, longer duration of diabetes, nephropathy, and retinopathy may be risk factors for a higher proportion of hyperglycemic events in hospitalized patients with T2DM under CSII therapy. Furthermore, lower BMI, lower C-P, lower LDL-C, longer duration of diabetes, and previous insulin prescriptions were found to be important factors for a higher proportion of hypoglycemic events. Evaluating the clinical features, comorbidities, and complications of hospitalized patients is essential to achieve reasonable glycemic control.

Current Therapeutic Modalities for the Management of Chronic Diabetic Wounds of the Foot

Impaired wound healing is common in patients with diabetes mellitus (DM). Different therapeutic modalities including wound debridement and dressing, transcutaneous electrical nerve stimulation (TENS), nanomedicine, shockwave therapy, hyperbaric (HBOT) and topical (TOT) oxygen therapy, and photobiomodulation (PBM) have been used in the management of chronic diabetic foot ulcers (DFUs). The selection of a suitable treatment method for DFUs depends on the hosts' physiological status including the intricacy and wound type. Effective wound care is considered a critical component of chronic diabetic wound management. This review discusses the causes of diabetic wounds and current therapeutic modalities for the management of DFUs, specifically wound debridement and dressing, TENS, nanomedicine, shockwave therapy, HBOT, TOT, and PBM.

A novel diabetes typology: towards precision diabetology from pathogenesis to treatment

The current classification of diabetes, based on hyperglycaemia, islet-directed antibodies and some insufficiently defined clinical features, does not reflect differences in aetiological mechanisms and in the clinical course of people with diabetes. This review discusses evidence from recent studies addressing the complexity of diabetes by proposing novel subgroups (subtypes) of diabetes. The most widely replicated and validated approach identified, in addition to severe autoimmune diabetes, four subgroups designated severe insulin-deficient diabetes, severe insulin-resistant diabetes, mild obesity-related diabetes and mild age-related diabetes subgroups. These subgroups display distinct patterns of clinical features, disease progression and onset of comorbidities and complications, with severe insulin-resistant diabetes showing the highest risk for cardiovascular, kidney and fatty liver diseases. While it has been suggested that people in these subgroups would benefit from stratified treatments, RCTs are required to assess the clinical utility of any reclassification effort. Several methodological and practical issues also need further study: the statistical approach used to define subgroups and derive recommendations for diabetes care; the stability of subgroups over time; the optimal dataset (e.g. phenotypic vs genotypic) for reclassification; the transethnic generalisability of findings; and the applicability in clinical routine care. Despite these open questions, the concept of a new classification of diabetes has already allowed researchers to gain more insight into the colourful picture of diabetes and has stimulated progress in this field so that precision diabetology may become reality in the future.

Sex- and gender-differences in chronic long-term complications of type 1 and type 2 diabetes mellitus in Italy

AIMS

This review summarizes the contribution of Italian diabetologists devoted to a better understanding of the complex relationship linking sex/gender and long-term complications of type 1 (T1DM) and type 2 diabetes (T2DM) over the last fifteen years.

DATA SYNTHESIS

Microvascular and macrovascular complications of diabetes show sex- and gender-related differences, involving pathophysiological mechanisms, epidemiological features and clinical presentation, due to the interaction between biological and psychosocial factors. These differences greatly impact on the progression of diabetes and its long-term complications, especially in the cardiovascular, renal and liver districts.

CONCLUSION

A better knowledge of such sex- and gender-related characteristics is required for a more precise patient phenotypization, and for the choice of a personalized antihyperglycemic treatment. Despite such mounting evidence, current diabetes clinical guidelines do not as yet adequately consider sex/gender differences.

La pandemia diabete in Italia

In Italia vivono circa 4 milioni di persone con il diabete e ogni anno ci sono circa 350 mila nuove diagnosi. Le persone con diabete ricevono prescrizioni di farmaci, esami di laboratorio e strumentali e richiedono ricoveri ospedalieri più spesso delle persone senza il diabete. Il diabete è gravato da aumentata mortalità e accorcia la vita, soprattutto nelle persone di media età. La qualità della cura nelle persone con diabete è subottimale, soprattutto fra chi non è assistito nei centri diabetologici (che, peraltro, rappresentano dei luoghi “salvavita”). Il diabete contribuisce fortemente alla spesa sanitaria e comporta ingenti spese, non tutte specificamente sanitarie. Nonostante tutto questo e nonostante leggi nazionali e regionali, documenti di indirizzo nazionali e regionali, PDTA regionali e locali, promesse e proponimenti di varia provenienza, la pandemia diabete non riceve le attenzioni che merita.

Impaired haematopoietic stem / progenitor cell traffic and multi-organ damage in diabetes

During antenatal development, hematopoietic stem/progenitor cells (HSPCs) arise from a specialized endothelium and migrate from the extraembryonic mesoderm to the fetal liver before establishing hematopoiesis in the bone marrow (BM). It is still debated whether, in adulthood, HSPCs display such ontologic overlap with vascular cells and capacity for endothelial differentiation. Yet, adult HSPCs retain a prominent migratory activity and traffic in the bloodstream to secondary lymphoid organs and all peripheral tissues, before eventually returning to the BM. While patrolling parenchymatous organs, HSPCs locate close to the vasculature, where they establish local hematopoietic islands and contribute to tissue homeostasis by paracrine signals. Solid evidence shows that diabetes mellitus jeopardizes the traffic of HSPCs from BM to the circulation and peripheral tissues, a condition called “mobilopathy.” A reduction in the levels of circulating HSPCs is the most immediate and apparent consequence, which has been consistently observed in human diabetes, and is strongly associated with future risk for multi-organ damage, including micro- and macro-angiopathy. But the shortage of HSPCs in the blood is only the visible tip of the iceberg. Abnormal HSPC traffic results from a complex interplay among metabolism, innate immunity, and hematopoiesis. Notably, mobilopathy is mechanistically connected with diabetes-induced myelopoiesis. Impaired traffic of HSPCs and enhanced generation of pro-inflammatory cells synergize for tissue damage and impair the resolution of inflammation. We herein summarize the current evidence that diabetes affects HSPC traffic, which are the causes and consequences of such alteration, and how it contributes to the overall disease burden.

Assessment of glycaemic status in adult hospital patients for the detection of undiagnosed diabetes mellitus: A systematic review

AIM

In-hospital blood glucose testing is commonplace, particularly in acute care. In-hospital screening for hyperglycaemia may present a valuable opportunity for early diabetes diagnosis by identifying at-risk individuals. This systematic review investigates the extent to which random blood glucose testing in acute and inpatient hospital settings predicts undiagnosed diabetes.

METHODS

Two databases were systematically searched for studies in which adult patients received an in-hospital random blood glucose test, followed by a diagnostic HbA1c test. The primary outcome was the proportion of hyperglycaemic individuals diagnosed with diabetes by HbA1c.

RESULTS

A total of 3245 unique citations were identified, and 12 were eligible for inclusion. Ten different blood glucose thresholds, ranging from 5.5 to 11.1 mmol/L, were used to detect hyperglycaemia, indicating that there is no consistent clinical definition for hyperglycaemia. The proportion of participants with hyperglycaemia in each study ranged from 3.3% to 62.1%, with a median (Q₁ , Q₃ ) of 34.5% (5.95%, 61.1%). The proportion of hyperglycaemic participants found to have a diabetes-range HbA1c varied from 4.1% to 90%, with a median (Q₁ , Q₃ ) of 18.9% (11.5%, 61.1%). Meta-analysis was not possible due to substantial heterogeneity between study protocols.

CONCLUSIONS

All studies consistently identified a proportion of hyperglycaemic hospital patients as having a diabetes-range HbA1c, showing that in-hospital blood glucose screening can facilitate diabetes diagnosis. The proportion of hyperglycaemic participants with undiagnosed diabetes varied substantially, indicating a need for further research and consistency in defining in-hospital hyperglycaemia. This may aid the development of a standardised screening protocol to identify people with possible undiagnosed diabetes.

Diabetes Distal Peripheral Neuropathy: Subtypes and Diagnostic and Screening Technologies

Diabetes distal symmetrical peripheral neuropathy (DSPN) is the most prevalent form of neuropathy in industrialized countries, substantially increasing risk for morbidity and pre-mature mortality. DSPN may manifest with small-fiber disease, large-fiber disease, or a combination of both. This review summarizes: (1) DSPN subtypes (small- and large-fiber disease) with attention to clinical signs and patient symptoms; and (2) technological diagnosis and screening for large- and small-fiber disease with inclusion of a comprehensive literature review of published studies from 2015-present (N = 66). Review findings, informed by the most up-to-date research, advance critical understanding of DSPN large- and small-fiber screening technologies, including those designed for point-of-care use in primary care and endocrinology practices.

Manifestation of Heart Failure and Chronic Kidney Disease are Associated with Increased Mortality Risk in Early Stages of Type 2 Diabetes Mellitus: Analysis of a Japanese Real-World Hospital Claims Database

INTRODUCTION

To assess the initial manifestation of comorbidities and their impact on mortality risk in patients with type 2 diabetes mellitus (T2DM) without a history of cardiovascular or renal complications (i.e., in the early stages of T2DM) compared with patients without T2DM.

METHODS

We performed a retrospective cohort study using a Japanese hospital claims database. The incidence rates of comorbidities (chronic kidney disease [CKD], heart failure [HF], myocardial infarction [MI], peripheral arterial disease [PAD], and stroke) and mortality risk were compared between patients with T2DM and age-/sex-matched patients without T2DM (matched 1:2).

RESULTS

Among the comorbidities assessed in this study, CKD and/or HF was the most frequent initial manifestation in the patients with T2DM (n = 426,186) with an incidence rate 2.02 times greater than that in matched patients without T2DM (n = 1,018,609). The mortality risk was also greater in patients with T2DM than in patients without T2DM with a hazard ratio of 1.73. In both patients with and without T2DM, the presence of CKD or HF was associated with greater mortality risks compared with the presence of MI, PAD, or stroke.

CONCLUSIONS

The high incidence of CKD or HF manifestation can contribute to the augmented mortality risk in patients in the early stages of T2DM compared with patients without T2DM. These findings highlight the importance of early interventions for preventing/treating CKD and HF to improve the prognosis of patients with T2DM.

Prevalence and risk factors of vascular complications in type 2 diabetes mellitus: Results from discover Middle East and Africa cohort

BACKGROUND

We evaluated the prevalence of vascular complications and associated risk factors in individuals with type 2 diabetes mellitus (T2DM) initiating second-line glucose-lowering therapy from the Middle East and Africa (MEA) cohort of the 3-year prospective DISCOVER study involving 15,992 patients in 38 countries.

METHODS

Baseline cross-sectional data collected from healthcare settings were used to assess micro and macrovascular complications prevalence as crude and age- and sex-standardised. The multi-variable analysis assessed factors associated with these complications.

RESULTS

Of 3,525 enrolled patients (mean age: 54.3 ± 10.8 years), >40% had hypertension and hyperlipidaemia. Metformin monotherapy was the first-line therapy in 56.5%, followed by metformin+sulphonylurea (20.3%). Crude and standardised prevalence of microvascular complications were 17.7% and 16.9% (95% confidence interval [CI], 16.77-16.98) and macrovascular complications were 10.7% and 8.7% (95% CI, 8.59-8.76). Factors significantly (p<0.05) associated with micro and macrovascular complications (odds ratios [95% CI]) were age (1.24 [1.12-1.39] and 1.58 [1.35-1.84]), male sex (1.33 [1.04-1.70] and 1.71 [1.22-2.40]), hyperlipidaemia (1.33 [1.07-1.65] and 1.96 [1.46-2.63]) and hypertension (1.75 [1.40-2.19] and 2.84 [2.07-3.92]).

CONCLUSION

A substantial burden of vascular complications with prominent risk factors in the MEA cohort calls for early preventive interventions.

Poor Self-Care Practices and Being Urban Resident Strongly Predict Chronic Complications Among Patients with Type 2 Diabetes in Eastern Ethiopia: A Hospital-Based Cross-Sectional Study

BACKGROUND

Diabetes, together with its complications, has a considerable negative influence on people's quality of life and healthcare delivery and raises diabetic mortality. However, there is limited information about the diabetes-associated chronic complications in the study setting. Therefore, this study aimed to determine the burden and factors related to the chronic complications among patients with type 2 diabetes (T2D) in Eastern Ethiopia.

METHODS

A hospital-based cross-sectional study was conducted among 879 patients with T2D at two public hospitals in Harar. The data were collected through interviews using a structured questionnaire. Data related to the diagnosis of chronic complications and biochemical tests were extracted from medical records. The outcome variable was the number of chronic complications that happened to the patients. A generalized Poisson regression model with robust variance estimation was used to investigate the association of independent variables with chronic complications. An adjusted prevalence ratio with a 95% CI was reported to show an association using a p-value ≤0.05.

RESULTS

One or more chronic complications were presented in 43% of T2D (95% CI: 39.65, 46.19). Macrovascular and microvascular complications were found in 27.6% and 23.5% of patients, respectively. Urban residence (APR = 2.64; 95% CI: 1.54, 4.54), low wealth status (APR = 1.80; 95% CI: 1.17, 2.76), diabetes duration ≥5 years (APR = 1.46; 95% CI: 1.05, 2.01), hypertriglyceridemia (APR = 1.48; 95% CI: 1.07, 2.09) and poor self-care practices (APR = 1.62; 95% CI: 1.18, 2.23) were factors significantly associated with the chronic complications.

CONCLUSION

The burden of chronic complications was high, with nearly half of T2D patients experiencing one or more chronic complications. Almost one in ten patients suffered from multiple chronic complications. The complications were mainly influenced by being urban resident, low wealth status, and poor self-care practices. Therefore, health care providers need to educate patients and promote self-care practices and healthy lifestyles to achieve treatment goals and lower the risk of chronic complications.

Characterization of Symptoms and Symptom Clusters for Type 2 Diabetes Using a Large Nationwide Electronic Health Record Database

OBJECTIVE

A variety of symptoms may be associated with type 2 diabetes and its complications. Symptoms in chronic diseases may be described in terms of prevalence, severity, and trajectory and often co-occur in groups, known as symptom clusters, which may be representative of a common etiology. The purpose of this study was to characterize type 2 diabetes-related symptoms using a large nationwide electronic health record (EHR) database.

METHODS

We acquired the Cerner Health Facts, a nationwide EHR database. The type 2 diabetes cohort (n = 1,136,301 patients) was identified using a rule-based phenotype method. A multistep procedure was then used to identify type 2 diabetes-related symptoms based on International Classification of Diseases, 9th and 10th revisions, diagnosis codes. Type 2 diabetes-related symptoms and co-occurring symptom clusters, including their temporal patterns, were characterized based the longitudinal EHR data.

RESULTS

Patients had a mean age of 61.4 years, 51.2% were female, and 70.0% were White. Among 1,136,301 patients, there were 8,008,276 occurrences of 59 symptoms. The most frequently reported symptoms included pain, heartburn, shortness of breath, fatigue, and swelling, which occurred in 21-60% of the patients. We also observed over-represented type 2 diabetes symptoms, including difficulty speaking, feeling confused, trouble remembering, weakness, and drowsiness/sleepiness. Some of these are rare and difficult to detect by traditional patient-reported outcomes studies.

CONCLUSION

To the best of our knowledge, this is the first study to use a nationwide EHR database to characterize type 2 diabetes-related symptoms and their temporal patterns. Fifty-nine symptoms, including both over-represented and rare diabetes-related symptoms, were identified.

The molecular link between oxidative stress, insulin resistance, and type 2 diabetes: A target for new therapies against cardiovascular diseases

Type 2 Diabetes Mellitus (T2D) is a chronic disease with a pandemic incidence whose pathogenesis has not yet been clarified. Raising evidence highlighted the role of oxidative stress in inducing insulin resistance, pancreatic beta-cell dysfunction, and leading to cardiovascular disease (CVD). Therefore, understanding the link between oxidative stress, T2D and CVD may help to further understand the pathological processes beyond this association, to personalize the algorithm of the cure, and to find new therapeutic targets. Here, we discussed the role of oxidative stress and the decrease of antioxidant defenses in the pathogenesis of T2D. Furthermore, some aspects of hypoglycemic therapies and their potential role as antioxidant agents were examined, which might be pivotal in preventing CVD in T2D patients.

Haplotypes of the genes (GCK and G6PC2) underlying the glucose/glucose-6-phosphate cycle are associated with pancreatic beta cell glucose sensitivity in patients with newly diagnosed type 2 diabetes from the VNDS study (VNDS 11)

BACKGROUND

Elevated fasting plasma glucose has been associated with increased risk for development of type 2 diabetes (T2D). The balance between glucokinase (GCK) and glucose-6-phosphate catalytic subunit 2 (G6PC2) activity are involved in glucose homeostasis through glycolytic flux, and subsequent insulin secretion.

AIM

In this study, we evaluated the association between the genetic variability of G6PC2 and GCK genes and T2D-related quantitative traits.

METHODS

In 794 drug-naïve, GADA-negative, newly diagnosed T2D patients (VNDS; NTC01526720) we performed: genotyping of 6 independent tag-SNPs within GCK gene and 5 tag-SNPs within G6PC2 gene; euglycaemic insulin clamp to assess insulin sensitivity; OGTT to estimate beta-cell function (derivative and proportional control; DC, PC) by mathematical modeling. Genetic association analysis has been conducted using Plink software.

RESULTS

Two SNPs within GCK gene (rs882019 and rs1303722) were associated to DC in opposite way (both p < 0.004). Two G6PC2 variants (rs13387347 and rs560887) were associated to both parameters of insulin secretion (DC and PC) and to fasting C-peptide levels (all p < 0.038). Moreover, subjects carrying the A allele of rs560887 showed higher values of 2h-plasma glucose (2hPG) (p = 0.033). Haplotype analysis revealed that GCK (AACAAA) haplotype was associated to decreased fasting C-peptide levels, whereas, the most frequent haplotype of G6PC2 (GGAAG) was associated with higher fasting C-peptide levels (p = 0.001), higher PC (β = 6.87, p = 0.022) and the lower 2hPG (p = 0.012).

CONCLUSION

Our findings confirmed the role of GCK and G6PC2 in regulating the pulsatility in insulin secretion thereby influencing insulin-signaling and leading to a gradual modulation in glucose levels in Italian patients with newly diagnosed T2D.

Understanding the Connection Between Common Stroke Comorbidities, Their Associated Inflammation, and the Course of the Cerebral Ischemia/Reperfusion Cascade

Despite the enormous progress in the understanding of the course of the ischemic stroke over the last few decades, a therapy that effectively protects neurovascular units (NVUs) and significantly improves neurological functions in stroke patients has still not been achieved. The reasons for this state are unclear, but it is obvious that the cerebral ischemia and reperfusion cascade is a highly complex phenomenon, which includes the intense neuroinflammatory processes, and comorbid stroke risk factors strongly worsen stroke outcomes and likely make a substantial contribution to the pathophysiology of the ischemia/reperfusion, enhancing difficulties in searching of successful treatment. Common concomitant stroke risk factors (arterial hypertension, diabetes mellitus and hyperlipidemia) strongly drive inflammatory processes during cerebral ischemia/reperfusion; because these factors are often present for a long time before a stroke, causing low-grade background inflammation in the brain, and already initially disrupting the proper functions of NVUs. Broad consideration of this situation in basic research may prove to be crucial for the success of future clinical trials of neuroprotection, vasculoprotection and immunomodulation in stroke. This review focuses on the mechanism by which coexisting common risk factors for stroke intertwine in cerebral ischemic/reperfusion cascade and the dysfunction and disintegration of NVUs through inflammatory processes, principally activation of pattern recognition receptors, alterations in the expression of adhesion molecules and the subsequent pathophysiological consequences.

A simple nomogram for identifying individuals at high risk of undiagnosed diabetes in rural population

AIMS

To sought for an easily applicable nomogram for detecting individuals at high risk of undiagnosed type 2 diabetes.

METHODS

The development cohort included 2542 participants recruited randomly from a rural population in 2011.The glycemic status of subjects was determined using the fasting plasma glucose test and the oral glucose tolerance test. The Bayesian Model Average approach was used to search for a parsimonious model with minimum number of predictor and maximum discriminatory power. The corresponding prediction nomograms were constructed and checked for discrimination, calibration, clinical usefulness, and generalizability in nationwide population in 2012.

RESULTS

The non-lab nomogram including waist circumference and systolic blood pressure was the most parsimonious with the area under receiver operating characteristic curve (AUC) of 0.71 (95 %CI = 0.64-0.76). Adding low-density lipoprotein cholesterol in the non-lab nomogram generated the lab-based nomogram with significantly improved AUC of 0.83 (0.78-0.87, P < 0.001). The nomograms had a positive net benefit at threshold probability between 0.01 and 0.15. Applying the non-lab nomogram to the national population yielded the AUC of 0.66 (0.63-0.70) and 0.68 (0.65-0.71) in the cohorts aged 40-64 and 30-69 years, respectively.

CONCLUSIONS

The novel nomograms could help promote the early detection of undiagnosed diabetes in rural Vietnamese population.

Progression and regression of nerve fibre pathology and dysfunction early in diabetes over 5 years

It has been traditionally suggested that the early development of diabetic sensorimotor polyneuropathy (DSPN) is characterized by a predominant and progressive injury to small nerve fibres followed by large fibre impairment. We alternatively hypothesized that small and large fibre damage due to DSPN in type 1 and type 2 diabetes could develop in parallel and may not only be progressive but also reversible. Participants from the German Diabetes Study baseline cohort with recent-onset type 1/type 2 diabetes (n = 350/570) and age-matched glucose-tolerant control individuals (Control 1/Control 2: n = 114/190) were assessed by nerve conduction studies (NCS), thermal detection thresholds (TDT), vibration perception threshold (VPT), Neuropathy Symptom Score (NSS), Neuropathy Disability Score (NDS), and intraepidermal nerve fibre density (IENFD) in skin biopsies (type 1/type 2 diabetes: n = 102/226; Control 1/Control 2: n = 109/208). Subsets of participants with type 1/type 2 diabetes were followed for 5 years (n = 184/307; IENFD subset: n = 18/69). DSPN was defined by the Toronto Consensus criteria. At baseline, DSPN was present in 8.1 and 13.3% of the type 1 and type 2 diabetes groups, respectively. The most frequently abnormal tests in the lower limbs below or above the 2.5th and 97.5th centile of the controls were IENFD (13.7%) and individual NCS (up to 9.4%) in type 1 diabetes participants and IENFD (21.8%), malleolar VPT (17.5%), and individual NCS (up to 11.8%) in those with type 2 diabetes, whereas TDT abnormalities did not differ between the control and diabetes groups. After 5 years in type 2 diabetes participants, the highest progression rates from the normal to the abnormal range were found for IENFD (18.8%) by -4.1 ± 2.8 fibres/mm, malleolar VPT (18.6%) by 9.1 ± 20.2 µm, and NDS (15.0%) by 3.7 ± 1.5 points, while vice versa the highest regression rates were observed for NDS (11.2%) by -3.1 ± 1.3 points, sural nerve amplitude (9.1%) by 4.7 ± 3.0 µV, IENFD (8.7%) by 1.4 ± 1.3 fibres/mm, and NSS (8.2%) by -5.8 ± 1.6 points. In type 1 diabetes participants, no major progression was seen after 5 years, but subclinical DSPN regressed in 10.3%. These findings point to an early parallel damage to both small and large nerve fibres in well-controlled recent-onset type 2 and, to a lesser extent, type 1 diabetes. After 5 years peripheral nerve morphology and function and clinical measures progress to the abnormal range in type 2 diabetes, but initial nerve alterations are also reversible to a meaningful degree.

Initial treatment of diabetes in Italy. A nationwide population-based study from of the ARNO Diabetes Observatory

BACKGROUND AND AIMS

To investigate diabetes treatment initiation and continuation in the next sixth months in newly diagnosed Italian subjects.

METHODS AND RESULTS

We analyzed administrative claims of 11,300,750 Italian residents. Subjects with incident diabetes were identified by glucose lowering drug prescriptions, disease-specific co-payment exemptions and hospital discharge codes occurring in 2018 but not in 2017. Incident cases were 65,932 of whom 91.4% received the prescription of a glucose lowering drug. Among the latter, those receiving a prescription of a noninsulin medication but no insulin were 84.8%, those receiving a prescription of insulin only were 9.4%, and those receiving prescriptions of both insulin and noninsulin drugs were 5.8%. Metformin was the most frequently drug initially prescribed in noninsulin treated subjects (~85%) and sulphonylurea receptor (SUR) agonists collectively ranked as second (~13%). Lispro (35%) and glargine (34%) were the most frequently prescribed molecules in subjects who were insulin treated. Differences in prescriptions were found in age categories, with increased use of SUR agonists across decades. In the first six months, as many as 50% of noninsulin treated patients continued with the initial drug, ~15% added a second agent, ~5% switched to another medication, and ~30% discontinued any glucose lowering treatment.

CONCLUSIONS

These data document that current guidelines are often neglected because prescriptions of SUR agonists as first agent are still quite common and insulin is prescribed more than expected. They point out the urgent need to improve the dissemination and implementations of guidelines in diabetes care.

Glomerular filtration rate decline in T2DM following diagnosis. The Verona newly diagnosed diabetes study-12

AIMS

Nephropathy is a complication of type 2 diabetes, with increased albuminuria and reduced glomerular filtration rate (GFR) as biomarkers. Rates of progression to end-stage-renal disease are variable among patients. In this study we have examined the GFR decline in newly diagnosed T2DM.

METHODS

A cohort of 410 patients with newly diagnosed T2DM and with at least four serum creatinine during the follow-up period were recruited. A linear model was used to calculate the decline in eGFR. A multivariable logistic model was used to identify independent predictors of rapid eGFR decline.

RESULTS

Average follow-up was 12.4 years. The eGFR change was -0.80 ± 2.23 ml/min/1.73 m² per year. Patients were arbitrarily stratified into rapid decliners (≤-3.0 ml/min/1.73 m² per year), moderate decliners (-2.9/-1 ml/min/1.73 m² per year) and slow/no decliners (>-1.0 ml/min/1.73 m² per year). Subjects in the 3 categories were 11.4%, 27.3%, and 61.3%, respectively. Albuminuria was the stronger predictor of rapid eGFR decline.

CONCLUSIONS

A rapid decline in eGFR occurs in approximately 1 out of 10 newly diagnosed subjects. This rapid decline can be predicted by widely accessible clinical features, such as albuminuria. Identification of rapid decliners may help to reduce progression toward advanced stages of nephropathy.