Screening for Diabetes and Prediabetes

Association between uric acid to high-density lipoprotein cholesterol ratio and chronic kidney disease among Chinese middle-aged and older adults with abnormal glucose metabolism: a nationwide cohort study

BACKGROUND

Previous research has demonstrated a correlation between uric acid to high-density lipoprotein cholesterol ratio (UHR) and chronic kidney disease (CKD), yet the evidence remains unclear in individuals with abnormal glucose metabolism. The objective of this research was to investigate the correlation between UHR and the occurrence of CKD, as well as the rapid kidney function decline among individuals aged over 45 years with abnormal glucose metabolism, using data from the China Health and Retirement Longitudinal Study (CHARLS).

METHODS

This study employed K-means clustering to categorize individuals based on UHR control levels into four classes. Subsequently, multivariate logistic regression analyses were utilized to explore the relationships between UHR and the occurrence of CKD as well as rapid kidney function decline. To examine the potential nonlinear relationship, restricted cubic spline (RCS) analyses were employed. Subgroup analyses and various sensitivity analyses were applied to validate the reliability of the results.

RESULTS

This study encompassed 3902 participants, all of whom had prediabetes or diabetes. In the fully adjusted logistic regression model assessing the risk of CKD development, the odds ratios (ORs) for Class 2, Class 3, and Class 4, versus Class 1, were 1.08 (0.71 to 1.67), 1.71 (1.06 to 2.77), and 2.13 (1.02 to 4.35), respectively. For every 1 standard deviation (SD) increase in cumulative UHR exposure, there was a 32% elevation in the risk of CKD incidence (OR: 1.32, 95% CI 1.12 to 1.56). RCS curves suggested a linear association between cumulative UHR (CumUHR) and CKD occurrence, but a nonlinear association with rapid renal function progression. Subgroup analysis indicated an interaction between age and UHR on the development of CKD. The application of multiple sensitivity analyses yielded consistent outcomes, suggesting the robustness of the findings.

CONCLUSION

In individuals with abnormal glucose metabolism, suboptimal control of UHR signifies an elevated risk of rapid kidney function decline and the incidence of CKD in the future. Therefore, close monitoring of long-term variations in UHR can facilitate early identification of the risk for CKD development.

Prognostic impact of prediabetes on long-term cardiovascular outcomes in patients under 35 with premature acute myocardial infarction

BACKGROUND

Prediabetes (pre-DM) is recognized as an intermediate state of glucose metabolism with a high potential to progress to diabetes mellitus (DM). However, its prognostic value in patients with premature acute myocardial infarction (PAMI) under the age of 35 remains unclear. This study aimed to investigate the relationship between pre-DM and long-term cardiovascular outcomes in this unique population.

METHODS

This retrospective cohort study included 796 PAMI patients under 35 years of age who were categorized into three groups based to glycated hemoglobin levels or previous history: normal glucose regulation (NGR), pre-DM, and DM. The primary endpoint was the occurrence of major adverse cardiovascular and cerebrovascular events (MACCE) including all-cause death, non-fatal myocardial infarction, non-fatal stroke, or revascularization. Multivariable Cox regression, Kaplan-Meier and Subgroup analyses were performed.

RESULTS

Pre-DM was observed in 22.1% of the PAMI cohort. During the median follow-up of 81 months, the incidence of MACCE was 23.5%, with significantly higher rates in the pre-DM and DM group compared to the NGR group (18.4%, 27.3%, 34.2%; p < 0.001). After adjusting for confounding variables, pre-DM remained independently associated with an increased risk of MACCE (HR 1.51, 95%CI 1.05-2.18, p = 0.027). Subgroup analysis demonstrated that pre-DM status was a robust risk factor compared to NGR. Moreover, pre-DM had a similar impact on MACCE events as DM in patients with PAMI.

CONCLUSIONS

Pre-DM is associated with a poor prognosis in young AMI patients under 35 years old, suggesting that it may be an independent predictor of adverse events in this population.

Association between endogenous estradiol, testosterone, and long-term mortality in adults with prediabetes and diabetes: Evidence from NHANES database

AIM AND INTRODUCTION

Diabetes and prediabetes pose significant global public health challenges. Sex steroids, particularly testosterone and estradiol, play crucial roles in various metabolic processes. This study investigates the relationship between sex hormone levels and long-term mortality in adults with prediabetes and diabetes, as well as those without glucose intolerance.

MATERIAL AND METHODS

This retrospective cohort study utilized data from the NHANES 2013-2016, including adults aged 50-79 across prediabetic, diabetic, and non-diabetic groups. Serum testosterone, estradiol, and their ratios (T/E) were analyzed. The primary outcomes were all-cause mortality and CVD mortality tracked until December 2019. Cox regression models estimated the associations between hormone levels and mortality risks.

RESULTS

The study included 3,665 participants (male: 2,140; female: 1,775). In males with prediabetes, higher estradiol (adjusted hazard ratio [aHR] = 0.17, 95% confidence interval [CI]: 0.07-0.43) or testosterone (aHR = 0.39, 95% CI: 0.31-0.50) was significantly associated with lower risk of all-cause mortality. Higher estradiol (aHR = 0.12, 95% CI: 0.04-0.32) or testosterone (aHR = 0.36, 95% CI: 0.27-0.48) was significantly associated with lower CVD mortality risk. In females with diabetes, there was a significant association between higher estradiol levels (aHR = 0.22, 95% CI: 0.06-0.83) or T/E ratio (aHR = 0.18, 95% CI: 0.04-0.73) with a reduced all-cause mortality risk.

CONCLUSIONS

This study identifies some novel associations between estradiol, testosterone, and their ratios with long-term mortality in men and women across different glycemic statuses. These findings suggest a potential protective role of sex hormones in individuals with altered glucose metabolism, with gender difference, warranting further investigation.

Machine Learning-Driven D-Glucose Prediction Using a Novel Biosensor for Non-Invasive Diabetes Management

Developing reliable noninvasive diagnostic and monitoring systems for diabetes remains a significant challenge, especially in the e-healthcare domain, due to computational inefficiencies and limited predictive accuracy in current approaches. The current study integrates machine learning with a molecularly imprinted polymer biosensor for detecting D-glucose in the exhaled breath condensate or aerosol. Advanced models, such as Convolutional Neural Networks and Recurrent Neural Networks, were used to analyze resistance signals, while classical algorithms served as benchmarks. To address challenges like data imbalance, limited samples, and inter-sensor variability, synthetic data generation methods like Synthetic Minority Oversampling Technique and Generative Adversarial Networks were employed. This framework aims to classify clinically relevant glucose levels accurately, enabling non-invasive diabetes monitoring.

Community-based HbA1c testing programme for early detection of undiagnosed diabetes in community pharmacy

OBJECTIVE

Testing with fingertip blood sampling, including HbA1c testing, has been available in community pharmacies in Japan since 2014. In 2016, the Mihara Pharmacy Association in Hiroshima Prefecture, in collaboration with the Mihara municipal government, developed a community programme that utilized the walk-in HbA1c test that could be offered by participating community pharmacies. The aim of this study was to assess whether the new programme could detect undiagnosed DM in the community and to compare groups who had and had not accessed the SHCG programme among SHCG eligible participants.

METHOD

The programme includes pharmacist advice following participants conducted Hba1c testing in the pharmacy, and completing a questionnaire to collect self-reported personal data including lifestyle, demography, height, weight, and blood pressure. All those accessing the programme were included. We analysed data from fiscal years 2016 to 2018, obtained retrospectively from the questionnaires.

KEY FINDINGS

The participants aged 40-74 years who were the target of a national health check programme represented 73.7% of the 1933 total unique participants. Approximately 40% of these participants did not undergo routine checkups, 23.8% had HbA1c scores ≥5.6%, and 2.7% had HbA1c scores ≥6.5%.

CONCLUSIONS

The walk-in HbA1c community testing programme provided an opportunity to test the diabetes mellitus risk of residents, especially those who have missed their routine checkups. If the community programme were adopted widely, more undiagnosed populations at risk for diabetes mellitus could be detected in the early stages and the use of community resources such as pharmacists and pharmacies would be utilized.

Comparison Between the Impact of Diabetes Mellitus on Liver Diseases and Vice Versa Among Saudi and Egyptian Patients

Background: The risk of dying from chronic liver diseases (CLDs) is two to three times higher for patients with diabetes (DM). Nonalcoholic fatty liver disease (NAFLD) is the primary cause of this increased risk, which has an etiology unrelated to alcohol or viruses. Previous research reported that diabetes and CLD are related, since they influence each other. Aim: Estimation of the impact of diabetes (DM) on liver diseases (LD), and of the impact of liver diseases on DM among Egyptian and Saudi patients. It is a descriptive and prospective analytical study design. The investigation was carried out in Saudi Arabia and Egypt at gastroenterology outpatient clinics. Methods: Prospective data were collected through face-to-face patient interviews during clinic visits between June 2021 and June 2023. The interviews covered the patients' basic characteristics and information on DM and LD. Certain laboratory tests were conducted on these patients, such as liver function, glucose level, lipid profile, INR, and prothrombin time. Results: The total of 2748 participants in this study included 1242 diabetic patients of both genders from Saudi Arabia and 1506 from Egypt. Most Saudis had between 10 and 20 years' duration of DM (35.5%), with HbA1c (7-10%) values of 47.8%, while the Egyptian patients had >20 years' duration of DM (39.8%), with HbA1c (7-10%) values of 49.8%. Regarding the impact of DM on the development of liver diseases, about 35.5% (Saudis) vs. 23.5% (Egyptians) had liver diseases due to DM, a significant difference (p-value = 0.011). Liver enzymes were increased in many of the Egyptian and Saudi patients (41.4% vs. 33%), while the presence of fatty liver (28.2% vs. 35.7%) and hepatocellular carcinoma (13.7% vs. 6.1%) were also significantly different (p-value = 0.047). While the impact of liver diseases on DM was observed more among Egyptian (59%) than among Saudi (46.4%) patients because of liver cirrhosis (HCV or HBV), known to be a reason for diabetes in Egyptians (27.9%) vs. Saudis (8.0%), a higher incidence of fatty liver leading to DM was observed in Saudis than in Egyptians (15.9% vs. 11.6%) (p-value = 0.000. Obesity was more prevalent among Saudi patients (63.8%) than among Egyptian patients (48.6%) (p-value = 0.019). Fewer Egyptians (about 65%) suffered from dyslipidemia than Saudis (about 80%). Higher INR and longer prothrombin times were observed in Egyptians (29.9% and 29.1%, respectively) than in Saudis (20.3% and 18.8%, respectively), with a significant difference between the two nations (p-value < 0.050). Conclusions: We may conclude that diabetes in most patients has a negative impact on the development of liver diseases (particularly fatty liver in Saudi patients). In addition, most liver diseases (liver cirrhosis) have a negative influence on the development of DM (more so in Egyptian patients). There is a link between DM and liver disease. In particular, liver cirrhosis and diabetes were found to influence each other. Therefore, correct medication, adherence to treatment, lifestyle modifications, successful cirrhosis control (in patients with liver diseases), and diabetic control (in diabetic patients) could lead to effective management of both diseases. The negative fallouts in the two cases were prompted by obesity, morbid eating, and poor quality of life.

Serum uric acid to creatinine ratio as a predictor of insulin resistance, β cell function, and metabolic syndrome in normal Korean adults: a cross-sectional study

BACKGROUND

This study aimed to determine the relations between serum uric acid to creatinine ratio(SUA/Cr) and insulin resistance, pancreatic β cell function, and outbreak of metabolic syndrome (MetS) in normal Korean participants.

MATERIALS AND METHODS

This study included 14,984 participants without diabetes mellitus or gout who participated in the 2019-2021 Korea National Health and Nutrition Examination Survey. To evaluate insulin resistance and β cell function, the homeostasis model assessment (HOMA) was used. Insulin resistance was suggested by HOMA-IR, and β cell function was presented as HOMA-β. Multivariate logistic linear regression analysis was used to identify the factors affecting HOMA-IR, HOMA-β, and MetS. Cut-off values of SUA/Cr to predict insulin resistance, β cell dysfunction, and MetS risk were also been suggested.

RESULTS

Consequent to dividing SUA/Cr into tertiles, the higher the SUA/Cr, the higher the HOMA-IR and dysfunction of β cell, and the rate of MetS increased (p < 0.05). SUA/Cr was associated with insulin resistance, β cell function, and existence of MetS (adjusted odds ratio [OR]; 1.231 [95% confidence interval [CI]; 1.204-1.259], 1.033 [1.011-1.057], and 1.065 [1.026-1.106], respectively). In addition, the group with the clinical significance was the 3rd tertile. In this group, insulin resistance, β cell dysfunction, and MetS risk could be predicted when SUA/Cr value was 8.2716, 8.8710, and 7.9762, respectively. Based on the total number of people, meaningful SUA/Cr values were 7.0175, 6.7925, and 6.9369.

CONCLUSIONS

The SUA/Cr may be a useful marker for predicting the insulin resistance, β cell function and incidence of MetS in normal Korean participants.

Starting the Conversation: Patient Perceptions of Self-Assessed Type-2 Diabetes Risk

Introduction

Little is known about patients' perceptions of their risk for type-2 diabetes (T2D), or if knowledge of risk could facilitate weight and diabetes prevention discussions with health care professionals.

Methods

In our academic family medicine practice, 25 patients completed a previsit T2D risk assessment on their phone and answered interview and survey questions to assess their understanding of their risk for developing T2D.

Results

Interest in their T2D risk was high, but self-estimation of risk before obtaining their score was low (21/25 reported ≤30% chance of developing diabetes). All patients perceived T2D to be very serious, most remembered their risk score (18/23 correct) when interviewed 3-5 days later, and many reported that the score increased their motivation to prevent T2D development. Despite this, the calculated risk result was not considered accurate by 8/23 patients and only 4/23 patients shared their score during their appointment visit.

Conclusion

T2D risk evaluation can facilitate patient awareness of their risk and lifestyle improvement, but clinician engagement and communication are needed for interpretation, treatment, and linkage to prediabetes care.

Molecular mechanism of Wilms tumour 1-associated protein in diabetes-related dry eye disease by mediating m6A methylation modification of lncRNA NEAT1

Background: Dry eye disease (DED) is often secondary to diabetes mellitus (DM).Purpose: This study is to explore the action of Wilms tumor 1-associated protein (WTAP) in DM-DED via lncRNA NEAT1 m6A methylation.Methods: DM-DED mouse models were treated with sh-WTAP/sh-NEAT1, followed by assessment of corneal epithelial damage/histopathological changes. HCE-2 cells were exposed to hyperosmotic conditions to establish in vitro DED models and treated with oe-NEAT1/sh-NEAT1/sh-WTAP/nigericin (an NLRP3 inflammasome inducer). Cell viability/apoptosis were evaluated by CCK-8/TUNEL. Levels of WTAP/NEAT1/inflammatory factors/NLRP3 inflammasome- and apoptosis-related markers were determined. m6A modification was examined by MeRIP-qPCR and NEAT1 stability was also detected.Results: DM-DED mice exhibited up-regulated WTAP/NEAT1 expression and severe corneal damage, whereas WTAP/NEAT1 knockdown alleviated inflammation/corneal damage. In hyperosmolarity-induced HCE-2 cells, NEAT1 aggravated inflammation and apoptosis, while NEAT1 knockdown suppressed NLRP3 inflammasome activation and ameliorated cell injury. Hyperosmolarity-induced WTAP expression increased m6A modification and NEAT1 mRNA stability. WTAP mediated m6A methylation of NEAT1 and NLRP3 inflammasome activation in DM-DED mice.

A multiorgan map of metabolic, signaling, and inflammatory pathways that coordinately control fasting glycemia in mice

To identify the pathways that are coordinately regulated in pancreatic β cells, muscle, liver, and fat to control fasting glycemia we fed C57Bl/6, DBA/2, and Balb/c mice a regular chow or a high fat diet for 5, 13, and 33 days. Physiological, transcriptomic and lipidomic data were used in a data fusion approach to identify organ-specific pathways linked to fasting glycemia across all conditions investigated. In pancreatic islets, constant insulinemia despite higher glycemic levels was associated with reduced expression of hormone and neurotransmitter receptors, OXPHOS, cadherins, integrins, and gap junction mRNAs. Higher glycemia and insulin resistance were associated, in muscle, with decreased insulin signaling, glycolytic, Krebs' cycle, OXPHOS, and endo/exocytosis mRNAs; in hepatocytes, with reduced insulin signaling, branched chain amino acid catabolism and OXPHOS mRNAs; in adipose tissue, with increased innate immunity and lipid catabolism mRNAs. These data provide a resource for further studies of interorgan communication in glucose homeostasis.

Lipid Accumulation Product as a Predictor of Prediabetes and Diabetes: Insights From NHANES Data (1999-2018)

Background: The study investigates the association between lipid accumulation product (LAP) and the risk of prediabetes and diabetes. LAP, a measure indicating lipid overaccumulation, is hypothesized to be a significant predictor for these conditions. This research utilizes data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2018. Methods: The study followed a structured methodology, starting with data extraction from the NHANES database. Participants' eligibility was determined based on specific inclusion and exclusion criteria, resulting in a final sample size of 24,121 individuals. LAP was calculated using established formulas for men and women. The diagnosis of prediabetes and diabetes was based on standard medical criteria, including HbA1c levels, fasting plasma glucose, and oral glucose tolerance test (OGTT) results. Covariates like demographic variables, lifestyle factors, and other health indicators were also considered. Statistical analysis involved categorizing LAP into quartiles and employing logistic regression models to examine the relationship between LAP and the risk of prediabetes and diabetes. Results: Participants in the highest LAP quartile exhibited distinct characteristics: older age, lower education levels, more former smokers and drinkers, higher blood pressure and cholesterol levels, and greater use of medications. A positive association was observed between LAP and the incidence of prediabetes and diabetes across all models. Specifically, each 10-unit increase in LAP was linked to a 22% increase in risk. Nonlinear relationships were also explored, revealing an inflection point in the risk correlation at an LAP value of 68.1. Conclusion: The study concludes that LAP is a significant predictor of prediabetes and diabetes risk, with higher LAP levels correlating with increased risk. This finding underscores the potential of LAP as a useful marker in identifying individuals at higher risk for these conditions. It also highlights the importance of considering LAP in preventive health strategies.

A machine learning tool for identifying patients with newly diagnosed diabetes in primary care

BACKGROUND AND AIM

It is crucial to identify a diabetes diagnosis early. Create a predictive model utilizing machine learning (ML) to identify new cases of diabetes in primary health care (PHC).

METHODS

A case-control study utilizing data on PHC visits for sex-, age, and PHC-matched controls. Stochastic gradient boosting was used to construct a model for predicting cases of diabetes based on diagnostic codes from PHC consultations during the year before index (diagnosis) date and number of consultations. Variable importance was estimated using the normalized relative influence (NRI) score. Risks of having diabetes were calculated using odds ratios of marginal effects (ORME). Four groups by age and sex were studied, age-groups 35-64 years and ≥ 65 years in men and women, respectively.

RESULTS

The most important predictive factors were hypertension with NRI 21.4-29.7 %, and obesity 4.8-15.2 %. The NRI for other top ten diagnoses and administrative codes generally ranged 1.0-4.2 %.

CONCLUSIONS

Our data confirm the known risk patterns for predicting a new diagnosis of diabetes, and the need to test blood glucose frequently. To assess the full potential of ML for risk prediction purposes in clinical practice, future studies could include clinical data on life-style patterns, laboratory tests and prescribed medication.

Understanding the struggle: Unique challenges of adherence in male diabetic patients in Tshwane

BACKGROUND

Type 2 diabetes prevalence is steadily increasing worldwide, and South Africa is one of the countries in Africa with the highest prevalence of this disease, along with other non-communicable diseases. The adherence to treatment in male patients with type 2 diabetes is influenced by their attitudes towards medication and how they perceive their condition. To some extent, these factors impact the treatment outcomes for patients undergoing type 2 diabetes treatment. The purpose of this study was to investigate the perceptions of male patients with type 2 diabetes on their adherence to diabetic therapy. The study was conducted in the clinics of the City of Tshwane Metropolitan municipality in Gauteng.

METHODS

This study followed a qualitative, exploratory design. Data were gathered from 15 male patients who were purposefully sampled through in-person, one-on-one interviews with the principal investigator. The eight steps outlined by Tesch were used to analyse the participant data.

RESULTS

Emergent themes indicated that there were barriers to adherence to diabetic treatment and also factors that promoted adherence to diabetic treatment among the participants. Several factors were found to affect treatment uptake among the participants.

CONCLUSION

Patients demonstrated various reactions to diabetic treatment, highlighting the need for reinforcing education at the time of diagnosis and treatment initiation. Additionally, regular patient follow-up may be essential to improve adherence among patients.Contribution: The study highlights the importance of health promotion and the need to develop materials for medication-specific counselling for patients receiving diabetic treatment, in order to promote adherence.

Nonlinear relationship between triglyceride-glucose index and the risk of prediabetes and diabetes: a secondary retrospective cohort study

Background

The triglyceride-glucose (TyG) index, recognized for its cost-efficiency and simplicity, serves as an accessible indicator of insulin resistance. Yet, its correlation with the risk of prediabetes and diabetes (Pre-DM/DM) in the Chinese demographic remains uncertain. Consequently, our study explored the association between the TyG index and the development of Pre-DM/DM within the Chinese population.

Methods

The retrospective cohort study was carried out utilizing data from a health screening initiative. The study included 179541 adults over 20 who underwent medical examinations at the Rich Healthcare Group over a period spanning from 2010 to 2016. The correlation between the TyG index and Pre-DM/DM risk was investigated using Cox regression analysis. Furthermore, Cox proportional hazards regression with cubic spline functions and smooth curve fitting was incorporated to explore their non-linear connection.

Results

The mean age of study participants was 41.18 ± 12.20 years old, and 95255 (53.05%) were male. During a median follow-up of 3.01 years, 21281 (11.85%) participants were diagnosed with Pre-DM/DM. After adjusting the potential confounding factors, the results showed that the TyG index was positively correlated with incident Pre-DM/DM (HR: 1.67, 95%CI: 1.62-1.71, P< 0.001). Additionally, a non-linear association was observed between the TyG index and the onset of Pre-DM/DM, with an inflection point identified at 8.73. Hazard ratios (HR) to the left and right of this inflection point were 1.95 (95%CI: 1.86-2.04) and 1.34 (95%CI: 1.27-1.42), respectively. Furthermore, sensitivity analyses confirmed the stability of these findings.

Conclusion

The TyG index exhibited a non-linear positive relationship with the risk of Pre-DM/DM. These findings imply that maintaining the TyG index at a lower, specified threshold may be beneficial in mitigating the onset of Pre-DM/DM.

The interplay between vitamin D status, subclinical inflammation, and prediabetes

Vitamin D's role extends beyond classical calcium and phosphate homeostasis to encompass a pivotal influence on immune modulation and metabolic health. The mechanisms by which vitamin D exerts these effects involve its conversion to hormonally active calcitriol, which binds intracellular vitamin D receptors, initiating various downstream cascades. In this review, we tease out the evidence showing the relationship between vitamin D deficiency and prediabetes within the context of subclinical inflammation, with a special focus on the novel monocyte-to-HDL ratio (MHR), a novel inflammatory marker reflecting subclinical inflammation. This was based on a thorough literature review using reputable databases covering the period from 1980 to 2024. In light of this, we discuss calcitriol's anti-inflammatory effects and consequently link vitamin D deficiency to both overt and subclinical inflammation. Additionally, the utility of several biomarkers, notably MHR, in investigating this association is also discussed. We further reviewed the role of vitamin D deficiency in precipitating prediabetes and type 2 diabetes mellitus (T2DM) via insulin resistance, decreased insulin synthesis and secretion, and subclinical inflammation. Taken together, this mini review highlights that vitamin D deficiency is significantly associated with subclinical inflammation, playing a critical role in the development of prediabetes and the progression to T2DM. Addressing vitamin D deficiency through appropriate interventions may serve as a preventative measure against the development of prediabetes and T2DM.

Association of caffeine intake with all-cause and cardiovascular mortality in diabetes and prediabetes

BACKGROUD

The association between caffeine intake and mortality in prediabetes and diabetes is not well defined. This study was designed to investigate the association between caffeine intake and all-cause mortality and cardiovascular disease (CVD) mortality in adults with prediabetes and diabetes in the United States.

METHODS

This analysis included 18,914 adult patients with diabetes and prediabetes from the National Health and Nutrition Examination Survey (NHANES) 2003-2018. Follow-up extended to December 31, 2019. Weighted Cox proportional hazards regression models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CI) for all-cause mortality and CVD mortality.

RESULTS

During 142,460 person-years of follow-up, there were 3,166 cases of all-cause mortality and 1,031 cases of CVD mortality recorded. In the fully adjusted models, caffeine intake showed a significant dose-response association with the risk of all-cause mortality and CVD mortality in individuals with diabetes and prediabetes. When comparing extreme quartiles of caffeine intake, the multivariable-adjusted hazard ratio for all-cause mortality was 0.78 (0.67-0.91) (P for trend = 0.007); however, there was no significant association with the risk of CVD mortality. Results remained consistent in stratified analyses by sex, age, race/ethnicity, education level, family income-poverty ratio, BMI, hypertension, smoking status, alcohol intake, and HEI-2015.

CONCLUSIONS

This study suggests that caffeine intake is significantly inversely associated with the risk of all-cause mortality in individuals with diabetes and prediabetes. In individuals with prediabetes, there is also a significant inverse association between caffeine intake and CVD events, but this association is not present in those with diabetes.

Development and validation of a machine learning-based model to predict isolated post-challenge hyperglycemia in middle-aged and elder adults: Analysis from a multicentric study

INTRODUCTION

Due to the high cost and complexity, the oral glucose tolerance test is not adopted as the screening method for identifying diabetes patients, which leads to the misdiagnosis of patients with isolated post-challenge hyperglycemia (IPH), that is., patients with normal fasting plasma glucose (<7.0 mmoL/L) and abnormal 2-h postprandial blood glucose (≥11.1 mmoL/L). We aimed to develop a model to differentiate individuals with IPH from the normal population.

METHODS

Data from 54301 eligible participants were obtained from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a longitudinal (REACTION) study in China. Data from 37740 participants were used to develop the diagnostic system. External validation was performed among 16561 participants. Three machine learning algorithms were used to create the predictive models, which were further evaluated by various classification algorithms to establish the best predictive model.

RESULTS

Ten features were selected to develop an IPH diagnosis system (IPHDS) based on an artificial neural network. In external validation, the AUC of the IPHDS was 0.823 (95% CI 0.811-0.836), which was significantly higher than the AUC of the Taiwan model [0.799 (0.786-0.813)] and that of the Chinese Diabetes Risk Score model [0.648 (0.635-0.662)]. The IPHDS model had a sensitivity of 75.6% and a specificity of 74.6%. This model outperformed the Taiwan and CDRS models in subgroup analyses. An online site with instant predictions was deployed at https://app-iphds-e1fc405c8a69.herokuapp.com/.

CONCLUSIONS

The proposed IPHDS could be a convenient and user-friendly screening tool for diabetes during health examinations in a large general population.

Through the Looking Glass Darkly: How May AI Models Influence Future Underwriting?

Applications of Artificial Intelligence (AI) deep-learning models to screening for clinical conditions continue to evolve. Instances provided in this treatise include using a simple one-view PA chest radiograph to screen for Type 2 Diabetes Mellitus (T2DM), congestive heart failure, valvular heart disease, and to assess mortality in asymptomatic persons with respiratory diseases. This technology incorporates hundreds of thousands of CXRs into a convoluted neural network and is generally named AI CXR. As an example, the AUROC (Area Under Receiving Operator Characteristic) of screening for T2DM was 0.84, with sensitivity and specificities that exceed those of the United States Preventative Services Task Force (USPSTF) guidelines for screening with HBA1c or blood glucose studies. The AUROC's for diagnosing ejection fractions less than 40% was 0.92, and for detecting valvular heart diseases was 0.87. The potential implications for underwriting life and disability policies may be significant. A companion article in the Journal of Insurance Medicine addresses this same technology using a simple 12-lead ECG, generally named AI ECGs.

Scoping review: Exploring the relationship between chrononutrition and glycemic responses in the adult population

Chrononutrition, an emerging body of evidence on the relationship between biological rhythms and metabolism, has been established to be associated with glycemic responses. However, the available evidence is inconsistent, due to protocol variations. Therefore, this review aims to summarize the findings on chrononutrition characteristics and their association with glycemic responses among adults. Systematic searches were conducted across six databases (PubMed, EBSCO Host, ProQuest Central, MEDLINE & Ovid, Scopus and Web of Science) to identify all relevant studies published from January 2012. Two reviewers independently screened the abstracts and full-text articles based on the inclusion and exclusion criteria. Details about population characteristics, study methods and key findings were extracted following the PRISMA-ScR guideline. The quality of selected studies was evaluated using the mixed methods appraisal tool. The searchers identified 49 studies eligible for analysis. The results showed that meal timing, particularly night-time eating and snacking were associated with glycemic responses. Regarding meal regularity, skipping breakfast may affect glycemic responses, but no clear conclusion was drawn about its effect on insulin. The association between meal frequency and glycemic responses was inconclusive. Night fasting duration and restricted eating window are potentially associated with glycemic responses. The current review extensively investigates the association between chrononutrition factors and glycemic responses in adults. However, more prospective cohort and interventional studies are needed to better understand this causal-effect relationship.

Feasibility of prevention of type 2 diabetes in low- and middle-income countries

Type 2 diabetes is a leading cause of global mortality and morbidity. Nearly 80% of individuals with diabetes live in low- and middle-income countries (LMICs), where nearly half of those with the condition remain undiagnosed. The majority of known cases have sub-optimal clinical outcomes. Moreover, large populations with impaired glucose tolerance and/or impaired fasting glucose contribute to the rapid increase in type 2 diabetes. Globally, priority should be given to limit the population with diabetes, especially in LMICs, alongside actions to optimise the care of people diagnosed with diabetes. Primary prevention studies in LMICs have generated evidence to show the efficacy and scalability of strategies to fully prevent or delay the development of diabetes in high-risk groups. However, these are mainly limited to certain countries in Asia, particularly China and India. The studies have indicated that prevention policies are effective in populations with a high risk of type 2 diabetes, and they also have long-term benefits, not only for the risk of type 2 diabetes but also for the risk of associated metabolic disorders, such as CVDs. For the effective conduct of national programmes, innovative mechanisms must be implemented, such as the use of information technology, joint efforts of multiple teams implementing similar programmes, and involvement of governmental and non-governmental partnerships. Continuous monitoring and long-term studies are required to assess the utility of these programmes. The effectiveness of such programmes in LMICs has not been proven over the longer term, except in China. Despite the available evidence, the feasibility of prevention strategies for type 2 diabetes in LMICs at population level remains an enigma. There remain challenges in the form of cultural, societal and economic constraints; insufficient infrastructure and healthcare capacity; and the non-fully elucidated natural history and determinants of type 2 diabetes in LMICs.

Metabolic health tracking using Ultrahuman M1 continuous glucose monitoring platform in non- and pre-diabetic Indians: a multi-armed observational study

Continuous glucose monitoring (CGM) device adoption in non- and pre-diabetics for preventive healthcare has uncovered a paucity of benchmarking data on glycemic control and insulin resistance for the high-risk Indian/South Asian demographic. Furthermore, the correlational efficacy between digital applications-derived health scores and glycemic indices lacks clear supportive evidence. In this study, we acquired glycemic variability (GV) using the Ultrahuman (UH) M1 CGM, and activity metrics via the Fitbit wearable for Indians/South Asians with normal glucose control (non-diabetics) and those with pre-diabetes (N = 53 non-diabetics, 52 pre-diabetics) for 14 days. We examined whether CGM metrics could differentiate between the two groups, assessed the relationship of the UH metabolic score (MetSc) with clinical biomarkers of dysglycemia (OGTT, HbA1c) and insulin resistance (HOMA-IR); and tested which GV metrics maximally correlated with inflammation (Hs-CRP), stress (cortisol), sleep, step count and heart rate. We found significant inter-group differences for mean glucose levels, restricted time in range (70-110 mg/dL), and GV-by-SD, all of which improved across days. Inflammation was strongly linked with specific GV metrics in pre-diabetics, while sleep and activity correlated modestly in non-diabetics. Finally, MetSc displayed strong inverse relationships with insulin resistance and dysglycemia markers. These findings present initial guidance GV data of non- and pre-diabetic Indians and indicate that digitally-derived metabolic scores can positively influence glucose management.

Lipidomics based on UHPLC/Q-TOF-MS to characterize lipid metabolic profiling in patients with newly diagnosed type 2 diabetes mellitus with dyslipidemia

Dyslipidemia often accompanies type 2 diabetes mellitus (T2DM). Elevated blood glucose in patients commonly leads to high levels of lipids. Lipid molecules can play a crucial role in early detection, treatment, and prognosis of T2DM with dyslipidemia. Previous lipid studies on T2DM mainly focused on Western diabetic populations with elevated blood glucose. In this research, we investigate both high blood sugar and high lipid levels to better understand changes in plasma lipid metabolism in newly diagnosed Chinese T2DM patients with dyslipidemia (NDDD). We used a plasma lipid analysis method based on ultra-high performance liquid chromatography coupled with mass spectrometry technology (UHPLC-MS) and statistical analysis to characterize lipid profiles and identify potential biomarkers in NDDD patients compared to healthy control (HC) subjects. Additionally, we examined the differences in lipid profiles between hyperlipidemia (HL) patients and HC subjects. We found significant changes in 15 and 23 lipid molecules, including lysophosphatidylcholine (LysoPC), phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), and ceramide (Cer), in the NDDD and HL groups compared to the HC group. These altered lipid molecules are associated with five metabolic pathways, with sphingolipid metabolism and glycerophospholipid metabolism being the most relevant to glucose and lipid metabolism changes. These lipid biomarkers are strongly correlated with traditional markers of glucose and lipid metabolism. Notably, Cer(d18:1/24:0), SM(d18:1/24:0), SM(d18:1/16:1), SM(d18:1/24:1), and SM(d18:2/24:1) were identified as essential potential biomarkers closely linked to clinical parameters through synthetic analysis of receiver operating characteristic curves, random forest analysis, and Pearson matrix correlation. These lipid biomarkers can enhance the risk prediction for the development of T2DM in individuals with dyslipidemia but no clinical signs of high blood sugar. Furthermore, they offer insights into the pathological mechanisms of T2DM with dyslipidemia.

Exercise training modalities in prediabetes: a systematic review and network meta-analysis

Background

Lifestyle modification based on exercise intervention is still the primary way to delay or reverse the development of diabetes in patients with prediabetes. However, there are still challenges in setting up a detailed exercise prescription for people with prediabetes. This study mainly ranks exercise prescriptions by comparing the improvement of glucose and lipid metabolism and the level of weight loss in patients.

Method

All studies on exercise intervention in prediabetes were identified by searching five electronic databases. Risk assessment and meta-analysis were performed on eligible studies.

Results

Twenty-four studies involving 1946 patients with prediabetes and seven exercise intervention models were included in the final analysis. The meta-analysis showed that exercise of any type was more effective for glycemic control in prediabetes than no exercise. However, the changes in blood glucose were moderate. In prediabetes, combining moderate-intensity aerobic exercise with low-to moderate-load resistance training showed the most significant improvements in glycosylated hemoglobin (HbA1c), body mass index (BMI), body weight (BW), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL) (P-score=0.82; 0.70; 0.87; 1; 0.99), low-to moderate-load resistance training showed the most significant improvements in fasting blood glucose (FBG) (P-score=0.98), the vigorous-intensity aerobic exercise showed the most significant improvements in 2-hour post-meal blood glucose (2hPG) and systolic blood pressure (SBP) (P-score=0.79; 0.78), and moderate-intensity aerobic exercise showed the most significant improvements in diastolic blood pressure (DBP) (P-score=0.78).

Conclusion

In summary, moderate-intensity aerobic exercise, low-to moderate-load resistance training and the combination of both have beneficial effects on glycemic control, weight loss, and cardiovascular health in patients with prediabetes. These findings provide valuable guidance for rehabilitation clinicians and patients alike to follow.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD 42021284922.

Association of T-wave electrocardiogram changes and type 2 diabetes: a cross-sectional sub-analysis of the MASHAD cohort population using the Minnesota coding system

BACKGROUND

Type 2 Diabetes Mellitus (T2DM) has become a major health concern with an increasing prevalence and is now one of the leading attributable causes of death globally. T2DM and cardiovascular disease are strongly associated and T2DM is an important independent risk factor for ischemic heart disease. T-wave abnormalities (TWA) on electrocardiogram (ECG) can indicate several pathologies including ischemia. In this study, we aimed to investigate the association between T2DM and T-wave changes using the Minnesota coding system.

METHODS

A cross-sectional study was conducted on the MASHAD cohort study population. All participants of the cohort population were enrolled in the study. 12-lead ECG and Minnesota coding system (codes 5-1 to 5-4) were utilized for T-wave observation and interpretation. Regression models were used for the final evaluation with a level of significance being considered at p < 0.05.

RESULTS

A total of 9035 participants aged 35-65 years old were included in the study, of whom 1273 were diabetic. The prevalence of code 5-2, 5-3, major and minor TWA were significantly higher in diabetics (p < 0.05). However, following adjustment for age, gender, and hypertension, the presence of TWAs was not significantly associated with T2DM (p > 0.05). Hypertension, age, and body mass index were significantly associated with T2DM (p < 0.05).

CONCLUSIONS

Although some T-wave abnormalities were more frequent in diabetics, they were not statistically associated with the presence of T2DM in our study.

A Comprehensive Review on Prospects of Polymeric Nanoparticles for Treatment of Diabetes Mellitus: Receptors-Ligands, In vitro & In vivo Studies

As per International Diabetes Federation Report 2022, worldwide diabetes mellitus (DM) caused 6.7M moralities and ~537M adults suffering from diabetes mellitus. It is a chronic condition due to β-cell destruction or insulin resistance that leads to insulin deficiency. This review discusses Type-1 DM and Type-2 DM pathophysiology in detail, with challenges in management and treatment. The toxicity issues of conventional drugs and insulin injections are complex to manage. Thus, there is a need for technological intervention. In recent years, nanotechnology has found a fruitful advancement of novel drug delivery systems that might potentially increase the efficacy of anti-diabetic drugs. Amongst nano-formulations, polymeric nanoparticles have been studied to enhance the bioavailability and efficacy of anti-diabetic drugs and insulin. In the present review, we summarized polymeric nanoparticles with different polymers utilized to deliver anti-diabetic drugs with in vitro and in vivo studies. Furthermore, this review also includes the role of receptors and ligands in diabetes mellitus and the utilization of receptor-ligand interaction to develop targeted nanoparticles. Additionally, we discussed the utility of nanoparticles for the delivery of phytoconstituents which aids in protecting the oxidative stress generated during diabetes mellitus. Atlast, this article also comprises of numerous patents that have been filed or granted for the delivery of antidiabetic and anticancer molecules for the treatment of diabetes mellitus and pancreatic cancer.

Non-linear association of triglyceride-glucose index with prevalence of prediabetes and diabetes: a cross-sectional study

Background

The Triglyceride-glucose (TyG) index has been acknowledged as a convenient, cost-effective, and relatively simple marker for insulin resistance (IR). Meanwhile, prediabetes, described as an asymptomatic, moderately hyperglycemic state, tends to be more prevalent than diabetes. Thus, the objective of this study was to explore the relationship between the TyG index and the prevalence of both prediabetes and diabetes within the U.S. population.

Methods

This study utilized a cross-sectional dataset derived from the National Health and Nutrition Survey (NHANES) spanning 1999 to 2018. The subjects were individuals aged 18 years and above, who had available fasting glucose and fasting triglyceride information, permitting a diagnosis of prediabetes or diabetes. The TyG index was computed using laboratory data, and participants were subsequently categorized into quartiles based on this information. The relationship between the TyG index and the prevalence of prediabetes and diabetes was investigated using logistic regression analysis.

Results

Out of the 25,159 participants, 23.88% were found to have prediabetes, while 16.22% were diagnosed with diabetes. After adjusting for confounding factors, a linear increase in relative odds was observed in Q2 (OR: 1.69; 95% CI: 1.52, 1.89), Q3 (OR: 2.57; 95% CI: 2.30, 2.88), and Q4 (OR: 4.88; 95% CI: 4.33, 5.49) groups in comparison to the reference group, Q1. In addition, a non-linear relationship was observed between the TyG index and the prevalence of prediabetes and diabetes. Specifically, patients with a TyG index greater than 8.00 overall exhibited a significantly higher risk of prediabetes and diabetes, confirming that an increase in the TyG index is associated with a corresponding increase in risk. However, this shift showed gender-specific variations; the threshold was observed at 8.00 in males but shifted to 9.00 in females.

Conclusion

The TyG index demonstrated a non-linear positive correlation with both prediabetes and diabetes. This suggests that maintaining the TyG index at a certain, reduced level could potentially aid in preventing the onset of prediabetes and diabetes.

Improving Diabetes Screening in the Primary Care Clinic

BACKGROUND

In our suburban primary care clinic, the average rate of screening for diabetes among eligible patients was only 51%, similar to national screening data. We conducted a quality improvement project to increase this rate.

METHODS

During the 6-month preintervention phase, we collected baseline data on the percentage of eligible patients screened per week (percentage of patients with hemoglobin A1c checked in the prior 3 years out of patients eligible for screening who completed a visit during the week). We then implemented a two-phase intervention. In phase 1 (approximately 8 months), we generated an electronic health record (EHR) report to identify eligible patients and pended laboratory orders for physicians to sign. In phase 2 (approximately 3 months), we replaced the phase 1 intervention with an EHR clinical decision support tool that automatically identifies eligible patients. We compared screening rates in the preintervention vs. intervention period. For phase 1, we also assessed laboratory completion rates and the laboratory results. We surveyed physicians regarding intervention acceptability and satisfaction at 3, 6, 9, and 12 months during the intervention period.

RESULTS

The weekly percentage of patients screened increased from an average of 51% in the preintervention phase to 65% in the intervention phase (p < 0.001). During phase 1, most patients underwent laboratory blood testing as recommended (83% within 3 months), and results were consistent with prediabetes in 23% and with diabetes in 4%. Overall, most physicians believed that the intervention appropriately identified patients due for screening and was helpful (100% of respondents agreed at 9 months vs. 71% at 3 months).

CONCLUSION

We successfully implemented a systematic screening intervention involving a manual workflow and EHR tool and improved diabetes screening rates in our clinic.

The leading global health challenges in the artificial intelligence era

Millions of people's health is at risk because of several factors and multiple overlapping crises, all of which hit the vulnerable the most. These challenges are dynamic and evolve in response to emerging health challenges and concerns, which need effective collaboration among countries working toward achieving Sustainable Development Goals (SDGs) and securing global health. Mental Health, the Impact of climate change, cardiovascular diseases (CVDs), diabetes, Infectious diseases, health system, and population aging are examples of challenges known to pose a vast burden worldwide. We are at a point known as the "digital revolution," characterized by the expansion of artificial intelligence (AI) and a fusion of technology types. AI has emerged as a powerful tool for addressing various health challenges, and the last ten years have been influential due to the rapid expansion in the production and accessibility of health-related data. The computational models and algorithms can understand complicated health and medical data to perform various functions and deep-learning strategies. This narrative mini-review summarizes the most current AI applications to address the leading global health challenges. Harnessing its capabilities can ultimately mitigate the Impact of these challenges and revolutionize the field. It has the ability to strengthen global health through personalized health care and improved preparedness and response to future challenges. However, ethical and legal concerns about individual or community privacy and autonomy must be addressed for effective implementation.

Glycated Hemoglobin Is Suboptimal for the Screening of Prediabetes and Type 2 Diabetes in Adults With Nonalcoholic Fatty Liver Disease

OBJECTIVES

Nonalcoholic fatty liver disease (NAFLD) is a risk factor for type 2 diabetes (T2D), but T2D screening tests are not well validated in this population. In this study, we assessed performance of glycated hemoglobin (A1C) and fasting plasma glucose (FPG) in glucose dysmetabolism screening and aimed to optimize detection thresholds for individuals with NAFLD.

METHODS

We retrospectively included oral glucose tolerance tests (OGTTs) from consecutive patients undergoing a specialized clinic for NAFLD, if A1C and/or fasting glucose was available within 3 months of OGTT. We compared performances of A1C and fasting glucose with the "gold standard" of OGTT using thresholds from the 2018 Diabetes Canada guidelines. A1C and FPG thresholds were optimized for detection of glucose dysmetabolism using receiver operating characteristic curves.

RESULTS

We included 63 OGTTs from individuals with NAFLD (52% female, age 48 [interquartile range 35 to 63] years, body mass index 34 [interquartile range 29 to 40] kg/m2). A1C had 16% (95% confidence interval [CI] 6% to 38%) sensitivity (Se) and 97% (95% CI 85% to 100%) specificity (Sp) for T2D detection, and 45% (95% CI 30% to 62%) Se and 100% (95% CI 83% to 100%) Sp for abnormal blood glucose detection. FPG had 67% (95% CI 45% to 83%) Se and 100% (95% CI 92% to 100%) Sp for T2D detection, and 74% (95% CI 59% to 85%) Se and 92% (95% CI 74% to 99%) Sp for abnormal blood glucose detection. Optimal A1C and FPG thresholds were 5.6% and 6.3 mmol/L for T2D detection, which are lower than current recommendations.

CONCLUSIONS

A1C is less sensitive than FPG and is suboptimal for T2D detection, suggesting that OGTT may be obtained if A1C is ≥5.6% or FPG is ≥6.3 mmol/L in individuals with NAFLD, to avoid underdiagnosis and treatment inertia.

Lifestyle Can Exert a Significant Impact on the Development of Metabolic Complications and Quality Life in Patients with Inflammatory Bowel Disease

Inflammatory bowel diseases (IBDs) are associated with an increased risk of metabolic comorbidities. There is a lack of data regarding the relationship between lifestyle and metabolic diseases in IBD patients. A cross-sectional study on consecutive IBD outpatients was conducted. Adherence to the Mediterranean diet (MD) was assessed using a 14-item questionnaire from the PREDIMED study, and physical activity was evaluated using the GODIN-Leisure score. Body composition was studied based on body mass index and waist-hip ratio (WHR), while quality of life was assessed using a nine-item short questionnaire. Among the 688 evaluated IBD patients, 66% were overweight or obese, 72.7% did not lead an active lifestyle and 70.1% did not adhere to the MD. Metabolic syndrome was associated with age (OR = 1.07, p = 0.019), overweight/obesity (OR = 12.987, p < 0.001) and the inflammatory behavior of Crohn's disease (OR = 6.172, p = 0.001). Type 2 diabetes mellitus or prediabetes was associated with age (OR = 1.063 p = 0.016), overweight/obesity (OR = 3.861, p < 0.001) and the inflammatory behavior of Crohn's disease (OR = 4.716, p = 0.001). Overweight /obesity (OR = 5.494, p < 0.001), a high WHR (OR = 2.564, p = 0.005) and a non-active lifestyle (OR = 2.202, p = 0.0003) were associated with metabolic dysfunction-associated steatotic liver disease. Lifestyle, body composition and not solely systemic inflammation might exert a significant influence on the emergence of metabolic comorbidities such as MASLD, type 2 diabetes mellitus and metabolic syndrome in patients with IBD.

Acute Glycemic Control in Prediabetes Individuals Favorably Alters Serum NLRP3 Inflammasome and Related Interleukins

Hyperglycemia associated with prediabetes (PD) alters NLRP3 inflammasome activity and related interleukins, yet no study has evaluated the expression of the NLRP3 inflammasome complex and related interleukins in individuals with a PD condition that did or did not develop type 2 diabetes mellitus (T2DM). This study investigated the effect of 6 months of lifestyle modification on the expression of the NLRP3 inflammasome and related interleukins (1α, 1β, 18, 33 and 37) in the sera of individuals with a PD condition that did or did not develop T2DM. This interventional study included 67 Saudi adults (mean age = 41.9 ± 8.0 years, mean BMI = 33.2 ± 5.5 kg/m2). Overnight-fasting serum samples were collected at baseline and at the 6-month follow-up. Serum levels of NLRP3, capsase-1 and related ILs were analyzed at both visits using commercially available immunoassay kits. Results showed that IL-1α increased in the PD group that developed T2DM (p = 0.046), IL-33 decreased in the PD group that reverted to normal (p < 0.001) and NLRP3 decreased in the PD group that remained PD (p = 0.01). Results also showed a positive over-time correlation between NLRP3 and both IL-1α and IL-33 (p < 0.001 and p = 0.028, respectively). In conclusion, glycemic control favorably altered NLRP3 inflammasome complex activity, and lifestyle modification in PD individuals is crucial in reversing harmful metabolic and inflammatory phenotypes.

Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs

Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulatory chest radiographs (CXRs) frequently ordered, we investigated detecting type 2 diabetes (T2D) by combining radiographic and EHR data using a DL model. Our model, developed from 271,065 CXRs and 160,244 patients, was tested on a prospective dataset of 9,943 CXRs. Here we show the model effectively detected T2D with a ROC AUC of 0.84 and a 16% prevalence. The algorithm flagged 1,381 cases (14%) as suspicious for T2D. External validation at a distinct institution yielded a ROC AUC of 0.77, with 5% of patients subsequently diagnosed with T2D. Explainable AI techniques revealed correlations between specific adiposity measures and high predictivity, suggesting CXRs' potential for enhanced T2D screening.

Self-Management of Diabetes and Associated Factors among Patients Seeking Chronic Care in Tshwane, South Africa: A Facility-Based Study

The burden of diabetes continues to increase in South Africa and a significant number of diabetes patients present at public primary healthcare facilities with uncontrolled glucose. We conducted a facility-based cross-sectional study to determine the diabetes self-management practices and associated factors among out-patients in Tshwane, South Africa. An adapted validated questionnaire was used to collect data on sociodemography, diabetes knowledge, and summaries of diabetes self-management activities measured in the previous seven days, and over the last eight weeks. Data were analysed using STATA 17. A final sample of 402 diabetes out-patients was obtained (mean age: 43 ± 12 years) and over half of them were living in poor households. The mean total diabetes self-management of score was 41.5 ± 8.2, with a range of 21 to 71. Almost two thirds of patients had average self-management of diabetes, and 55% had average diabetes knowledge. Twenty-two percent of patients had uncontrolled glucose, hypertension (24%) was the common comorbidity, and diabetic neuropathy (22%) was the most common complication. Sex [male: AOR = 0.55, 95% CI: 0.34-0.90], race [Coloured: AOR = 2.84, 95% CI: 1.69-4.77 and White: AOR = 3.84, 95% CI: 1.46-10.1], marital status [divorced: AOR = 3.41, 95% CI: 1.13-10.29], social support [average: AOR = 2.51, 95% CI: 1.05-6.00 and good: AOR = 4.49, 95% CI: 1.61-7.57], body mass index [obesity: AOR = 0.31, 95% CI: 0.10-0.95], diabetes knowledge [average: AOR = 0.58, 95% CI: 0.33-0.10 and good: AOR = 1.86, 95% CI: 0.71-4.91], and uncontrolled glucose [AOR = 2.97, 95% CI: 1.47-5.98] were factors independently predictive of diabetes self-management. This study emphasizes that the self-management of diabetes was mostly on average among patients and was associated with the aforementioned factors. Innovative approaches are perhaps needed to make diabetes education more effective. Face-to-face sessions delivered generally during clinic visits should be better tailored to the individual circumstances of diabetes patients. Considerations should be given to the options of leveraging information technology to ensure the continuity of diabetes education beyond clinic visits. Additional effort is also needed to meet the self-care needs of all patients.

The Importance of Prediabetes Screening in the Prevention of Cardiovascular Disease

Background

Prediabetes is a disordered state of glucose metabolism defined by an elevated blood glucose level that is below the level required for the diagnosis of diabetes. Prediabetes is associated with an increased risk of cardiovascular disease. The onset and progression of macrovascular disease occur during the prediabetes phase. Early diagnosis and screening of prediabetes are essential steps to prevent diabetes and its associated complications.

Objective

To assess the prevalence of prediabetes and undiagnosed diabetes in patients with cardiovascular disease according to the ADA criteria.

Methods

This cross-sectional study included 2968 a high cardiovascular risk patients aged 40 to 75 years admitted to the Department of Internal Medicine. Sociodemographic variables and other relevant medical history information were collected by the researchers during the clinical interview. A fasting blood sample was obtained to determine HbA1c levels and other relevant laboratory findings.

Results

Of the total number of participants, 1496 participants were not diagnosed with diabetes, 485 (32.4%) of them had HbA1c values indicating prediabetes and 158 (10.6%) of them had HbA1c values indicating new diagnosed diabetes. Up to one-third of those with undiagnosed prediabetes had already been diagnosed with cardiovascular complications.

Conclusion

Routine screening of glycemic metabolism could be valuable in identifying high-risk individuals before a cardiovascular event occurs.

Association of triglycerides to high-density lipoprotein cholesterol ratio to identify future prediabetes and type 2 diabetes mellitus: over one-decade follow-up in the Iranian population

BACKGROUND

To determine the association between triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) for identifying subjects at risk of incident prediabetes and type 2 diabetes mellitus (T2DM).

METHODS

In 5064 subjects (men = 2247) aged ≥ 20 years, using Cox proportional hazards regression analyses, the associations of TG/HDL-C with incident prediabetes and T2DM were examined among normoglycemic men and women. Furthermore, the association of this lipid ratio with incident T2DM was also assessed among prediabetic subjects (n = 1414). The multivariable analyses were adjusted for age, body mass index, waist-to-height ratio, wrist circumference, systolic blood pressure, family history of T2DM, education level, history of cardiovascular diseases, and fasting plasma glucose (FPG).

RESULTS

During a median follow-up of 11.2 years, 2140 new cases of prediabetes (men = 1070) and 360 incident T2DM (men = 152) were identified among normoglycemic individuals. In the prediabetic population, 574 new cases of T2DM (men = 252) were developed. Among the whole population, compared to the first quartile (reference), higher quartiles of TG/HDL-C were significantly associated with higher risks of incident prediabetes and T2DM among normoglycemic individuals and incident T2DM in the prediabetic population (all P for trend < 0.001). The corresponding hazard ratios (HRs) and 95% confidence intervals (CIs) for the fourth quartiles were 1.37(1.20-1.58), 1.92(1.34-2.75), and 1.57(1.22-2.01), respectively. The sex-stratified analyses demonstrated similar significant associations in both sexes; however, TG/HDL-C lost its association with incident T2DM among prediabetic men. Among the normoglycemic population, 1 unit increase in TG/HDL-C was significantly associated with incident prediabetes and T2DM [1.02(1.00-1.03) and 1.06(1.03-1.08), respectively]. The corresponding value for incident T2DM in prediabetic individuals was 1.01(1.00-1.03). In a subgroup population having insulin data (n = 2897), the associations between TG/HDL-C and incident prediabetes and T2DM among normoglycemic individuals generally persisted even after replacing FPG with an index of insulin resistance (IR), i.e., homeostasis model assessment of IR (HOMA-IR) in the adjusted model.

CONCLUSIONS

In conclusion, in the normoglycemic population, the increasing value of TG/HDL-C was unfavorably associated with incident prediabetes and T2DM, especially among women. Similarly, TG/HDL-C was associated with incident T2DM in prediabetic individuals. Generally, we found that the correlation between TG/HDL-C and different states of dysglycemia is independent of HOMA-IR.

False hemoglobin A1c value as a result of compound heterozygotes of hemoglobin E and hemoglobin New York

The presence of hemoglobin (Hb) variants might interfere with some glycated hemoglobin (HbA_1c ) measurements. There have been a few reports of compound Hb variants affecting HbA_1c testing. Here, we report a case of the coinheritance of two Hb variants in the β-globin gene. High-performance liquid chromatography with the Hb program showed a high HbA₂ level. Similarly, an E-window peak was separated on the high-performance liquid chromatography with a glycated Hb program. However, capillary electrophoresis showed two abnormal peaks and no HbA peak. Sanger sequencing confirmed the presence of Hb New York and HbE. This is the first report of a compound heterozygote for HbE and Hb New York. The double heterozygote caused erroneous results for HbA_1c on high-performance liquid chromatography and enzyme assay.

Disparities in adherence to diabetes screening guidelines among males and females in a universal care setting: A population-based study of 1,380,697 adults

Background

National guidelines recommend that all adults over the age of 40 years undergo screening for diabetes at least once every 3-years. We examined the adherence to these guidelines among males and females after accounting for age, urban/rural residence, and material deprivation. We also examined the incidence of prediabetes and diabetes in adherent and non-adherent individuals.

Methods

Our study is based on a retrospective population-level inception cohort of adults aged 40-79 years without pre-existing diabetes or cardiovascular disease on April 1, 2013. Adherence during a 3-year screening period (2013-2016) and prediabetes and diabetes during a 4-year follow-up period were examined. Multivariate logistic regression was used to examine the adjusted association between sex and adherence.

Findings

Among 1,380,697 individuals (49·2% male, 50·8% female) adherence rates were 69·9% in males and 79·8% in females. Sex-differences in adherence were largest in younger individuals (58·0% and 72·6% and in males and females aged 40-44 years, respectively) and consistent across rural/urban residence and material deprivation. Females were more adherent (adjusted odds ratio 1·92; 95% confidence interval 1·89 to 1·95) than males. Prediabetes and diabetes rates among individuals who adhered to screening guidelines were 15·7% and 2·6% among males and 13·4% and 1·5% among females. During the follow-up period, an additional 3·2% and 1·9% of adherent males and females had diabetes. Incidence rates of prediabetes and diabetes during the follow-up period among individuals who did not adhere to screening guidelines were 8·8% and 2·1% among males and 7·3% and 1·3% among females.

Interpretation

Adherence to diabetes screening guidelines is sub-optimal, especially among young males. Despite lower rates of adherence to screening, males have higher rates of prediabetes and diabetes compared to females. There is a need for education campaigns to improve diabetes screening rates in young adults, especially males.

Funding

This study was funded by the Canadian Institutes of Health Research Sex and Gender Science Chair (Recipient: Kaul).

Use of the new guidelines on an earlier age threshold of 35 years for diabetes screening can identify an additional 6.3 million undiagnosed individuals with diabetes and 72.3 million individuals with prediabetes among Chinese adults: An analysis of a nationally representative survey

BACKGROUND

Young-onset diabetes has been increasingly prevalent in China and most of the young patients with diabetes remain undiagnosed. Recently, the American Diabetes Association (ADA) updated their screening criteria and turned down the age threshold of diabetes screening from 45 years to 35 years, which highlighted the importance of identifying young individuals with diabetes. Herein, we aimed to evaluate the clinical relevance of updated ADA screening recommendations in Chinese adults and the metabolic features and risk factor profiles of these newly diagnosed individuals.

STUDY DESIGN AND METHODS

Using a complex, multistage, probability sampling design, we analyzed data from a nationally representative sample of 98,658 Chinese adults in 2010. Participants without previously diagnosed diabetes were included into the present study. We calculated the proportion of individuals with diabetes eligible for screening and the number needed to screen (NNS) to identify one patient with diabetes by age groups.

RESULTS

Setting an earlier age threshold of diabetes screening can identify additional 6.3 million patients with diabetes and 72.3 million individuals with prediabetes, and the proportion of identified individuals increased more in rural, underdeveloped, and central areas. The NNS in Chinese adults dropped significantly from 28 in 30-34 age group to 15 in 35-45 years of age and remained low afterwards. The undiagnosed patients with diabetes who met the new screening age threshold of ADA recommendation were characterized by younger age, lower blood pressure and blood lipids, but higher proportion of overweight and higher level of insulin resistance, and tended to have an unhealthy diet habit, including low intake of fruits and vegetables and high intake of sugar-sweetened beverages, compared to those aged over 45 years.

CONCLUSIONS

The new age threshold of 35 years for diabetes screening would reduce the proportion of undiagnosed diabetes with high cost-effectiveness, given the NNS for a positive test result was much lower in 35-45 age group comparing to the lower age group in Chinese adults.

Relationship between pre‑operative glycated haemoglobin and surgical site infection in patients undergoing elective colon cancer surgery

Surgical site infections remain a significant cause of morbidity following colon cancer surgery. Although diabetes has been recognised as a risk factor, patients with asymptomatic diabetes are likely underdiagnosed. The aim of the present study was to determine the relationship between preoperative glycated haemoglobin (HbA1C), clinicopathological characteristics and the influence on surgical site infection in a cohort of patients undergoing potentially curative colon cancer surgery. Patients who underwent elective, potentially curative colon cancer surgery between January 2011 and December 2014 were assessed for HbA1C levels (mmol/mol) measured within 3 months preoperatively. Clinicopathological data were recorded in a maintained database. A multivariate binary logistic regression model was used to assess the relationship between HbA1C, clinicopathological characteristics and surgical site infections. A total of 362 patients had HbA1C levels preoperatively recorded. HbA1C was significantly associated with body mass index (BMI), diabetes, smoking status, visceral fat area and skeletal muscle index. As determined by multivariate analysis, preoperative HbA1C levels remained independently associated with an increased risk of surgical site infections (OR 1.69, 95% CI 1.05-2.7; P=0.031) together with BMI (OR 1.91, 95% CI 1.36-2.67; P<0.001). Notably, in the present study, tumour-based factors, such as tumour location and TNM status, were not associated with infective complications. By contrast, host factors, such as BMI and pre-operative HbA1C were associated with surgical site infections suggesting that these factors were of more importance in determining short-term outcomes. In conclusion, objective measurements of BMI and HbA1C effectively stratified the risk of developing surgical site infection from 8 to 59%; therefore, HbA1C levels should be determined to allow for preoperative optimisation.

Combining HbA1c and glycated albumin improves detection of dysglycaemia in mixed-ancestry South Africans

BACKGROUND

Combining HbA_1c with glycated albumin (GA) may improve detection of dysglycaemia. As BMI correlates positively with HbA_1c and negatively with GA, HbA_1c may be more effective in obese and GA in nonobese individuals.

METHODS

To relate these findings to Africans, we assessed in 1274 South Africans living in CapeTown (male 26%; age 48±16y; BMI 28.7 kg/m² (range 15.6-73.8); obesity 39.9% and no prior diabetes history) the: (1) correlation of BMI with HbA_1c and GA, (2) ability of HbA_1c and GA separately and jointly, to detect OGTT-diagnosed dysglycaemia (diabetes plus prediabetes). Data collection took place between 2014 and 2016 in the City of Cape Town. Dysglycaemia was diagnosed by glucose criteria for the OGTT. Youden index was used to optimize diagnostic thresholds for HbA_1c and GA.

FINDINGS

Normal glucose tolerance, prediabetes and diabetes occurred in 76%, 17% and 7%, respectively. BMI positively correlated with HbA_1c [r = 0·34 [95%CI: 0·29,0·39)] and negatively with GA [-0·08 (0·13,0·03)]. For HbA_1c the optimal threshold by Youden-index for dysglycaemia diagnosis was: 6·0% (95%CI: 5·8,6·2) and for GA: 13·44% (12·72,14·71). In the nonobese, obese and total cohort, HbA_1c-alone detected: 51% (42-60), 72% (65,78), 63% (57,68), respectively; GA-alone detected 55% (52% (46,63), 52% (44, 59) and 53% (47,53), respectively; whereas: HbA_1c+GA detected: 69% (60,76), 82% (75,87) and 76% (71, 81). Therefore, for the total cohort detection of dysglycaemia HbA_1c-alone vs HbA_1c+GA detected 63% (57,68) vs 76% (71,81).

INTERPRETATION

The opposite correlations of HbA_1c and GA with BMI have now been demonstrated in an African-based population. Improving detection of dysglycaemia by combining HbA_1c and GA has important implications for diabetes risk screening.

FUNDING

AES is supported by the intramural programs of the National Institute of Diabetes and Digestive and Kidney Diseases and the National Institute of Minority Health and Health Disparities of the National Institutes of Health (NIH, Bethesda, Maryland, USA). DBS is supported by the intramural program of the Clinical Center of NIH. The South African Medical Research Council (SAMRC) funded the VMH study with funds from the National Treasury under its Economic Competitiveness and Support Package (MRC-RFA-UFSP-01-2013/VMH Study).

ASK1-Interacting Protein 1 Acts as a Novel Predictor of Type 2 Diabetes

Type 2 diabetes (T2D) mellitus is a chronic inflammatory disease characterized with high secretion of tumor necrosis factor (TNF)-α, but the regulatory pathway of TNF-α production in T2D has not been fully elucidated. ASK1-interacting protein 1 (AIP1) is a signaling scaffold protein that modulates several pathways associated with inflammation. In this study, we aimed to investigate the role of AIP1 in T2D development. Our results revealed that AIP1 was downregulated in omental adipose tissue (OAT) of obese patients with T2D compared with that in obese patients. In addition, Pearson's correlation test showed that AIP1 was negatively correlated with the homeostatic model assessment for insulin resistance (HOMA-IR, r = -0.4829) and waist-to-hip ratio (r = -0.2614), which are major clinical indexes of T2D. As revealed by the proteomic analysis, immunohistochemistry, and ELISA, the OAT and the serum of obese patients with T2D presented high inflammatory status. And the increased inflammatory factors TNF-α and C-reactive protein C (CRP) in the serum of obese patients with T2D showed a positive correlation with HOMA-IR (TNF-α, r = 0.4728; CRP, r = 0.5522). Interestingly, AIP1 deficiency in adipocytes facilitated TNF-α secretion and retarded glucose uptake. Mechanistically, AIP1 deletion in human adipocytes activated JNK, p38 MAPK, and ERK1/2 signaling. Furthermore, inhibition of these signaling pathways using specific inhibitors could suppress these signal activation and insulin resistance caused by AIP1 deficiency. In addition, AIP1 and TNF-α expression in the OAT of patients with T2D recovered to normal levels after laparoscopic Roux-en-Y gastric bypass (RYGB) surgery. These findings indicate that AIP1 is negatively correlated with the clinical indexes of T2D. It modulates TNF-α expression in OAT via JNK, p38 MAPK, and ERK1/2 signaling.

Population-Level Approaches to Preventing Type 2 Diabetes Globally

Type 2 diabetes (T2DM) is increasingly considered an epidemic rooted in modern society as much as in individual behavior. Addressing the T2DM burden thus involves a dual approach, simultaneously addressing high-risk individuals and whole populations. Within this context, this article summarizes the evidence base, in terms of effectiveness and cost-effectiveness, for population-level approaches to prevent T2DM: (1) modifications to the food environment; (2) modifications to the built environment and physical activity; and (3) programs and policies to address social and economic factors. Existing knowledge gaps are also discussed.