An explainable stacking-based approach for accelerating the prediction of antidiabetic peptides

Diabetes is a chronic disease that is characterized by high blood sugar levels and can have several harmful outcomes. Hyperglycemia, which is defined by persistently elevated blood sugar, is one of the primary concerns. People can improve their overall well-being and get optimal health outcomes by prioritizing diabetes control. Although the use of experimental approaches in diabetes treatment is cost-effective, it necessitates the development of many strategies for evaluating the efficacy of therapies. Researchers can quickly create new strategies for managing diabetes and get vital insights by enabling virtual screening with computational tools and procedures. In this study, we suggest a predictor named STADIP (STacking-based predictor for AntiDiabetic Peptides), a new method to predict antidiabetic peptides (ADPs) utilizing a stacked-based ensemble approach. It uses 12 different feature encodings and seven machine-learning techniques to construct 84 baseline models. The impacts of various baseline models on ADP prediction were then thoroughly examined. A two-step feature selection method, eXtreme Gradient Boosting with Sequential Forward Selection (XGB-SFS), was employed to determine the optimal number, out of 84 PFs to enhance predictive performance. Subsequently, utilizing the meta-predictor approach, 45 selected PFs were integrated into an XGB classifier to formulate the final hybrid model. The proposed method demonstrated superior predictive capabilities compared to constituent baseline models, as evidenced by evaluations on both cross-validation and independent tests. During extensive independent testing, STADIP achieved promising performance with accuracy and mathew's correlation coefficient of 0.954 and 0.877, respectively. It is anticipated that it will be useful tool in helping the scientific community to identify new antidiabetic proteins.

Could poor glycaemic control be a predictor of walking speed decline in older adults? Evidence from the English Longitudinal Study of Ageing

AIM

Although diabetes is a risk factor for walking speed decline in older adults, it remains unclear how glycaemic control [assessed by glycated haemoglobin (HbA1c)] might affect the long-term trajectories of walking speed. We investigated whether the glycaemic control status accelerates the walking speed decline and whether this decline differs depending on previous mobility conditions.

MATERIALS AND METHODS

In total, 3202 individuals aged ≥60 years from the English Longitudinal Study of Ageing (ELSA) were classified at baseline and after 4 and 8 years of follow-up according to glycaemic control status as 'without diabetes' (no self-reported diabetes and HbA1c <6.5%), 'good glycaemic control' (self-reported diabetes and HbA1c ≥6.5% and <7.0%) and 'poor glycaemic control' (PGC) (self-reported diabetes and HbA1c ≥7.0%). The generalized linear mixed models verified the walking speed trajectories in m/s. A second analysis was performed, including only participants without slowness at baseline (>0.8 m/s).

RESULTS

Compared with the status 'without diabetes', the annual walking speed decline was -0.015 m/s for PGC and -0.011 m/s for good glycaemic control, totalling -0.160 and -0.130 m/s, respectively, over 8 years. Among those without slowness at baseline, only PGC had a significant walking speed decline, corresponding to -0.014 m/s per year and -0.222 m/s over 8 years.

CONCLUSIONS

Poor glycaemic control is a discriminator of walking speed decline in older adults, regardless of previous mobility conditions. It may serve as an early screening tool for those at risk of decreased functional performance later in life.

Sex-specific associations between haemoglobin glycation index and the risk of cardiovascular and all-cause mortality in individuals with pre-diabetes and diabetes: A large prospective cohort study

AIM

The aim of this study was to investigate the relationship between the haemoglobin glycation index (HGI), and cardiovascular disease (CVD) and all-cause mortality in adults with pre-diabetes and diabetes.

METHODS

This study included 10 267 adults with pre-diabetes and diabetes from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. Sex-differentiated relationships between HGI and mortality were elucidated using multivariate Cox proportional hazards models, restricted cubic splines and a two-piecewise Cox proportional hazards model.

RESULTS

During the median follow-up time of 103.5 months, a total of 535 CVD deaths and 1918 all-cause deaths were recorded. After multivariate adjustment, in males with pre-diabetes and diabetes, there was a U-shaped relationship between HGI and CVD mortality and all-cause mortality, with threshold points of -0.68 and -0.63, respectively. Before the threshold point, HGI was negatively associated with CVD mortality [hazard ratio (HR) 0.60; 95% confidence interval (CI) 0.41, 0.89] and all-cause mortality (HR 0.56; 95% CI 0.43, 0.74), and after the threshold point, HGI was positively associated with CVD mortality (HR 1.46; 95% CI 1.23, 1.73) and all-cause mortality (HR 1.40; 95% CI 1.23, 1.59). In contrast, HGI had an L-shaped relationship with all-cause mortality and no significant association with CVD mortality in females. To the left of the threshold points, the risk of all-cause mortality decreased (HR 0.50; 95% CI 0.35, 0.71) progressively with increasing HGI.

CONCLUSIONS

In the cohort study, HGI in pre-diabetic and diabetic populations was found to have a U-shaped association with CVD mortality and all-cause mortality in males and an L-shaped association with all-cause mortality only in females. Further prospective and mechanistic studies are warranted.

The association between the triglyceride-glucose index and the risk of cardiovascular disease in US population aged ≤ 65 years with prediabetes or diabetes: a population-based study

BACKGROUND

The relationship between the triglyceride-glucose (TyG) index and the risk of cardiovascular disease (CVD) in the U.S. population under 65 years of age with diabetes or prediabetes is unknown. The purpose of this study was to investigate the relationship between baseline TyG index and CVD risk in U.S. patients under 65 years of age with diabetes or prediabetes.

METHODS

We used data from the 2003-2018 National Health and Nutrition Examination Survey (NHANES). Multivariate regression analysis models were constructed to explore the relationship between baseline TyG index and CVD risk. Nonlinear correlations were explored using restricted cubic splines. Subgroup analysis and interaction tests were also conducted.

RESULTS

The study enrolled a total of 4340 participants with diabetes or pre-diabetes, with a mean TyG index of 9.02 ± 0.02. The overall average prevalence of CVD was 10.38%. Participants in the higher TyG quartiles showed high rates of CVD (Quartile 1: 7.35%; Quartile 2: 10.04%; Quartile 3: 10.71%; Quartile 4: 13.65%). For CVD, a possible association between the TyG index and the risk of CVD was observed. Our findings suggested a linear association between the TyG index and the risk of CVD. The results revealed a U-shaped relationship between the TyG index and both the risk of CVD (P nonlinear = 0.02583) and CHF (P nonlinear = 0.0208) in individuals with diabetes. Subgroup analysis and the interaction term indicated that there was no significant difference among different stratifications. Our study also revealed a positive association between the TyG index and comorbid MetS in the U.S. population under 65 years of age with prediabetes or diabetes.

CONCLUSIONS

A higher TyG index was linked to an increased likelihood of CVD in the U.S. population aged ≤ 65 years with prediabetes and diabetes. Besides, TyG index assessment will contribute to more convenient and effective screening of high-risk individuals in patients with MetS. Future studies should explore whether interventions targeting the TyG index may improve clinical outcomes in these patients.

Association of neutrophil-lymphocyte ratio with all-cause and cardiovascular mortality in US adults with diabetes and prediabetes: a prospective cohort study

BACKGROUND

The neutrophil-lymphocyte ratio (NLR) is a novel hematological parameter to assess systemic inflammation. Prior investigations have indicated that an increased NLR may serve as a potential marker for pathological states such as cancer and atherosclerosis. However, there exists a dearth of research investigating the correlation between NLR levels and mortality in individuals with diabetes and prediabetes. Consequently, this study aims to examine the connection between NLR and all-cause as well as cardiovascular mortality in the population of the United States (US) with hyperglycemia status.

METHODS

Data were collected from a total of 20,270 eligible individuals enrolled for analysis, spanning ten cycles of the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. The subjects were categorized into three groups based on tertiles of NLR levels. The association of NLR with both all-cause and cardiovascular mortality was evaluated using Kaplan-Meier curves and Cox proportional hazards regression models. Restricted cubic splines were used to visualize the nonlinear relationship between NLR levels and all-cause and cardiovascular mortality in subjects with diabetes after accounting for all relevant factors.

RESULTS

Over a median follow-up period of 8.6 years, a total of 1909 subjects with diabetes died, with 671 deaths attributed to cardiovascular disease (CVD). And over a period of 8.46 years, 1974 subjects with prediabetes died, with 616 cases due to CVD. The multivariable-adjusted hazard ratios (HRs) comparing high to low tertile of NLR in diabetes subjects were found to be 1.37 (95% CI, 1.19-1.58) for all-cause mortality and 1.63 (95% CI, 1.29-2.05) for CVD mortality. And the correlation between high to low NLR tertile and heightened susceptibility to mortality from any cause (HR, 1.21; 95% CI, 1.03-1.43) and CVD mortality (HR, 1.49; 95% CI, 1.08-2.04) remained statistically significant (both p-values for trend < 0.05) in prediabetes subjects. The 10-year cumulative survival probability was determined to be 70.34%, 84.65% for all-cause events, and 86.21%, 94.54% for cardiovascular events in top NLR tertile of diabetes and prediabetes individuals, respectively. Furthermore, each incremental unit in the absolute value of NLR was associated with a 16%, 12% increase in all-cause mortality and a 25%, 24% increase in cardiovascular mortality among diabetes and prediabetes individuals, respectively.

CONCLUSIONS

The findings of this prospective cohort study conducted in the US indicate a positive association of elevated NLR levels with heightened risks of overall and cardiovascular mortality among adults with diabetes and prediabetes. However, potential confounding factors for NLR and the challenge of monitoring NLR's fluctuations over time should be further focused.

Lipids as potential mediators linking body mass index to diabetes: evidence from a mediation analysis based on the NAGALA cohort

BACKGROUND

Body mass index (BMI) and lipid disorders are both known to be strongly associated with the development of diabetes, however, the indirect effect of lipid parameters in the BMI-related diabetes risk is currently unknown. This study aimed to investigate the mediating role of lipid parameters in the association of BMI with diabetes risk.

METHODS

We assessed the association of diabetes risk with BMI, as well as lipid parameters including high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-CF and LDL-CS), triglycerides(TG), total cholesterol(TC), remnant cholesterol(RC), non-HDL-C, and combined indices of lipid parameters with HDL-C (RC/HDL-C ratio, TG/HDL-C ratio, TC/HDL-C ratio, non-HDL/HDL-C ratio, LDL/HDL-C ratio) using data from 15,453 subjects in the NAGALA project. Mediation models were used to explore the mediating role of lipid parameters in the association of BMI with diabetes risk, and mediation percentages were calculated for quantifying the strength of the indirect effects. Finally, receiver operating characteristic curve (ROC) analysis was used to compare the accuracy of BMI and BMI combined with lipid parameters in predicting incident diabetes.

RESULTS

Multivariate regression models, adjusted for confounding factors, demonstrated robust associations of lipid parameters, BMI, with diabetes risk, with the exception of TC, LDL-CF, LDL-CS, and non-HDL-C. Mediation analysis showed that lipid parameters except TC, LDL-CF, LDL-CS, and Non-HDL-C were involved in and mediated the association of BMI with diabetes risk, with the largest mediation percentage being the RC/HDL-C ratio, which was as high as 40%; it is worth mentioning that HDL-C and HDL-C-related lipid ratio parameters also play an important mediating role in the association between BMI and diabetes, with the mediator proportion being greater than 30%. Finally, based on the ROC results, we found that the prediction performance of all lipid parameters in the current study except TC was significantly improved when combined with BMI.

CONCLUSION

Our fresh findings suggested that lipid parameters partially mediated the association of BMI with diabetes risk; this result indicated that in the context of diabetes risk screening and disease management, it is important to not only monitor BMI but also pay attention to lipid parameters, particularly HDL-C and HDL-C-related lipid ratio parameters.

Nonenzymatic dual glucose sensing on boronic acid modified zeolitic imidazolate framework-67 nanoparticles for diabetes management

For early diabetes identification and management, the progression of an uncomplicated and exceedingly responsive glucose testing technology is crucial. In this study, we present a new sensor incorporating a composite of metal organic framework (MOF) based on cobalt, coated with boronic acid to facilitate selective glucose binding. Additionally, we successfully employed a highly sensitive electro-optical immunosensor for the detection of subtle changes in concentration of the diabetes biomarker glycated haemoglobin (HbA1c), using zeolitic imidazolate framework-67 (ZIF-67) coated with polydopamine which further modified with boronic acid. Utilizing the polymerization characteristics of dopamine and the NH2 groups, a bonding structure is formed between ZIF-67 and 4-carboxyphenylboronic acid. ZIF-67 composite served as an effective substrate for immobilising 4-carboxyphenylboronic acid binding agent, ensuring precise and highly selective glucose identification. The sensing response was evaluated through both electrochemical and optical methods, confirming its efficacy. Under optimized experimental condition, the ZIF-67 based sensor demonstrated a broad detection range of 50-500 mg dL-1, a low limit of detection (LOD) of 9.87 mg dL-1 and a high correlation coefficient of 0.98. Furthermore, the 4-carboxyphenylboronic acid-conjugated ZIF-67-based sensor platform exhibited remarkable sensitivity and selectivity in optical-based detection for glycated haemoglobin within the clinical range of 4.7-11.3%, achieving a LOD of 3.7%. These findings highlight the potential of the 4-carboxyphenylboronic acid-conjugated ZIF-67-based electro-optical sensor as a highly sensitive platform for diabetes detection.

Glycated Hemoglobin Variability Is Associated With Adverse Outcomes in Patients With Heart Failure Irrespective of Diabetic Status

BACKGROUND

The effect of glycated hemoglobin (HbA1c) variability on adverse outcomes in patients with heart failure (HF) is unclear. We aim to investigate the predictive value of HbA1c variability on the risks of all-cause death and HF rehospitalization in patients with HF irrespective of their diabetic status.

METHODS AND RESULTS

Using a previously validated territory-wide clinical data registry, HbA1c variability was assessed by average successive variability (ASV) or SD of all HbA1c measurements after HF diagnosis. Multivariable Cox proportional hazards models were used to estimate the adjusted hazard ratio (HR) and its corresponding 95% CI. A total of 65 950 patients with HF were included in the study. Over a median follow-up of 6.7 (interquartile range, 4.0-10.6) years, 34 508 patients died and 52 446 required HF rehospitalization. Every unit increment of variability in HbA1c was significantly associated with higher HF rehospitalization (HR ASV, 1.20 [95% CI, 1.18-1.23]) and all-cause death (HR ASV, 1.50 [95% CI, 1.47-1.53]). Diabetes significantly modified the association between HbA1c variability and outcomes (Pinteraction<0.001). HbA1c variability in patients with HF without diabetes conferred a higher risk of rehospitalization (HR ASV, 1.92 [95% CI, 1.70-2.17] versus HR ASV, 1.19 [95% CI, 1.17-1.21]), and all-cause death (HR ASV, 3.90 [95% CI, 3.31-4.61] versus HR ASV, 1.47 [95% CI, 1.43-1.50] compared with patients with diabetes).

CONCLUSIONS

HbA1c variability is significantly associated with greater risk of rehospitalization and all-cause death in patients with HF, irrespective of their diabetic status. These observations were more pronounced in patients with HF without diabetes.

Unveiling potential therapeutic targets for diabetes-induced frozen shoulder through Mendelian randomization analysis of the human plasma proteome

INTRODUCTION

This study aimed to assess the causal relationship between diabetes and frozen shoulder by investigating the target proteins associated with diabetes and frozen shoulder in the human plasma proteome through Mendelian randomization (MR) and to reveal the corresponding pathological mechanisms.

RESEARCH DESIGN AND METHODS

We employed the MR approach for the purposes of establishing: (1) the causal link between diabetes and frozen shoulder; (2) the plasma causal proteins associated with frozen shoulder; (3) the plasma target proteins associated with diabetes; and (4) the causal relationship between diabetes target proteins and frozen shoulder causal proteins. The MR results were validated and consolidated through colocalization analysis and protein-protein interaction network.

RESULTS

Our MR analysis demonstrated a significant causal relationship between diabetes and frozen shoulder. We found that the plasma levels of four proteins were correlated with frozen shoulder at the Bonferroni significance level (p<3.03E-5). According to colocalization analysis, parathyroid hormone-related protein (PTHLH) was moderately correlated with the genetic variance of frozen shoulder (posterior probability=0.68), while secreted frizzled-related protein 4 was highly correlated with the genetic variance of frozen shoulder (posterior probability=0.97). Additionally, nine plasma proteins were activated during diabetes-associated pathologies. Subsequent MR analysis of nine diabetic target proteins with four frozen shoulder causal proteins indicated that insulin receptor subunit alpha, interleukin-6 receptor subunit alpha, interleukin-1 receptor accessory protein, glutathione peroxidase 7, and PTHLH might contribute to the onset and progression of frozen shoulder induced by diabetes.

CONCLUSIONS

Our study identified a causal relationship between diabetes and frozen shoulder, highlighting the pathological pathways through which diabetes influences frozen shoulder.

Emerging biosensor probes for glycated hemoglobin (HbA1c) detection

Glycated hemoglobin (HbA1c), originating from the non-enzymatic glycosylation of βVal1 residues in hemoglobin (Hb), is an essential biomarker indicating average blood glucose levels over a period of 2 to 3 months without external environmental disturbances, thereby serving as the gold standard in the management of diabetes instead of blood glucose testing. The emergence of HbA1c biosensors presents affordable, readily available options for glycemic monitoring, offering significant benefits to small-scale laboratories and clinics. Utilizing nanomaterials coupled with high-specificity probes as integral components for recognition, labeling, and signal transduction, these sensors demonstrate exceptional sensitivity and selectivity in HbA1c detection. This review mainly focuses on the emerging probes and strategies integral to HbA1c sensor development. We discussed the advantages and limitations of various probes in sensor construction as well as recent advances in diverse sensing strategies for HbA1c measurement and their potential clinical applications, highlighting the critical gaps in current technologies and future needs in this evolving field.

The reliability of using gingival crevicular blood to measure blood glucose and hba1c levels in the dental setting: a systematic review and meta-analysis

OBJECTIVE

There are 500 million patients living with diabetes mellitus worldwide and 50% of them remain undiagnosed. Routine periodontal probing provides gingival crevicular blood in patients with gingivitis. Gingival blood may be useful for diabetes screening without the need for any expensive, painful or time-consuming method by using convenient glucometers. Therefore, the objective of this systematic review and meta-analysis is to answer the question to "is there a difference in glucose or HbA1c levels (O) in patients with positive gingival bleeding (P) measured on gingival crevicular blood (GCB) (I) compared to finger prick capillary blood (CB) (C).

MATERIALS AND METHODS

The authors performed an electronic search of six databases using identical MeSH phrases. Only human clinical studies without limitations on the year of publication were considered. Data extraction was done by using standardized data collection sheets. Risk of bias assessment were conducted using QUADAS-2 and QUADAS-C. Meta-analyses were carried out with the random effects model to aggregate the correlation coefficients and the difference between the means between gingival and capillary blood reading, using 95% confidence intervals.

RESULTS

The database and manual search yielded 268 articles, from which the selection procedure provided 36 articles for full-text screening, and the final pool of eligible articles composed of 23 studies with 1680 patients. Meta-analysis results on glycemic levels showed differences between the GCB and CB procedures in patients with and without diabetes with values of -6.80 [-17.35; 3.76] and - 4.36 [-9.89; 1.18], respectively. Statistically significant correlations were found (p = 0.001) between GCB and CB measurements in patients with (0.97 [0.927; 0.987]) and without diabetes (0.927 [0.873; 0.958]).

CONCLUSION

Gingival blood could prove to be useful to identify patients with undiagnosed diabetes when the necessary amount of uncontaminated blood is present. However, this technique is limited by the possibility of contamination, prandial status and inaccuracies, so it is unsuited to address the patient's glycemic control accurately.

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

BACKGROUND

Previous meta-analyses of summary data from randomised controlled trials have shown that statin therapy increases the risk of diabetes, but less is known about the size or timing of this effect, or who is at greatest risk. We aimed to address these gaps in knowledge through analysis of individual participant data from large, long-term, randomised, double-blind trials of statin therapy.

METHODS

We conducted a meta-analysis of individual participant data from randomised controlled trials of statin therapy that participated in the CTT Collaboration. All double-blind randomised controlled trials of statin therapy of at least 2 years' scheduled duration and with at least 1000 participants were eligible for inclusion in this meta-analysis. All recorded diabetes-related adverse events, treatments, and measures of glycaemia were sought from eligible trials. Meta-analyses assessed the effects of allocation to statin therapy on new-onset diabetes (defined by diabetes-related adverse events, use of new glucose-lowering medications, glucose concentrations, or HbA1c values) and on worsening glycaemia in people with diabetes (defined by complications of glucose control, increased use of glucose-lowering medication, or HbA1c increase of ≥0·5%). Standard inverse-variance-weighted meta-analyses of the effects on these outcomes were conducted according to a prespecified protocol.

FINDINGS

Of the trials participating in the CTT Collaboration, 19 trials compared statin versus placebo (123 940 participants, 25 701 [21%] with diabetes; median follow-up of 4·3 years), and four trials compared more versus less intensive statin therapy (30 724 participants, 5340 [17%] with diabetes, median follow-up of 4·9 years). Compared with placebo, allocation to low-intensity or moderate-intensity statin therapy resulted in a 10% proportional increase in new-onset diabetes (2420 of 39 179 participants assigned to receive a statin [1·3% per year] vs 2214 of 39 266 participants assigned to receive placebo [1·2% per year]; rate ratio [RR] 1·10, 95% CI 1·04-1·16), and allocation to high-intensity statin therapy resulted in a 36% proportional increase (1221 of 9935 participants assigned to receive a statin [4·8% per year] vs 905 of 9859 participants assigned to receive placebo [3·5% per year]; 1·36, 1·25-1·48). For each trial, the rate of new-onset diabetes among participants allocated to receive placebo depended mostly on the proportion of participants who had at least one follow-up HbA1c measurement; this proportion was much higher in the high-intensity than the low-intensity or moderate-intensity trials. Consequently, the main determinant of the magnitude of the absolute excesses in the two types of trial was the extent of HbA1c measurement rather than the proportional increase in risk associated with statin therapy. In participants without baseline diabetes, mean glucose increased by 0·04 mmol/L with both low-intensity or moderate-intensity (95% CI 0·03-0·05) and high-intensity statins (0·02-0·06), and mean HbA1c increased by 0·06% (0·00-0·12) with low-intensity or moderate-intensity statins and 0·08% (0·07-0·09) with high-intensity statins. Among those with a baseline measure of glycaemia, approximately 62% of new-onset diabetes cases were among participants who were already in the top quarter of the baseline distribution. The relative effects of statin therapy on new-onset diabetes were similar among different types of participants and over time. Among participants with baseline diabetes, the RRs for worsening glycaemia were 1·10 (1·06-1·14) for low-intensity or moderate-intensity statin therapy and 1·24 (1·06-1·44) for high-intensity statin therapy compared with placebo.

INTERPRETATION

Statins cause a moderate dose-dependent increase in new diagnoses of diabetes that is consistent with a small upwards shift in glycaemia, with the majority of new diagnoses of diabetes occurring in people with baseline glycaemic markers that are close to the diagnostic threshold for diabetes. Importantly, however, any theoretical adverse effects of statins on cardiovascular risk that might arise from these small increases in glycaemia (or, indeed, from any other mechanism) are already accounted for in the overall reduction in cardiovascular risk that is seen with statin therapy in these trials. These findings should further inform clinical guidelines regarding clinical management of people taking statin therapy.

FUNDING

British Heart Foundation, UK Medical Research Council, and Australian National Health and Medical Research Council.

User Performance Evaluation and System Accuracy Assessment of Four Blood Glucose Monitoring Systems With Color Coding of Measurement Results

BACKGROUND

Blood glucose monitoring systems (BGMSs) are a cornerstone in diabetes management. They have to provide sufficiently accurate results in the hands of lay users, particularly in insulin-treated patients. The aim of this study was user performance evaluation and system accuracy assessment of four BGMSs with color coding of results.

METHODS

Study procedures were based on ISO 15197:2013. User performance evaluation included data from 100 participants, each of whom used every system with one reagent lot. Study personnel observed user techniques. For the system accuracy assessment, 100 capillary samples were obtained for measurement in duplicate with each of three reagent system lots per system, resulting in 600 results per system.

RESULTS

All assessed BGMSs exhibited a sufficient level of accuracy, with small differences between them. In the user performance evaluation, study personnel observed the smallest total number of user errors with Contour Next (Ascensia), followed by Accu-Chek Instant (Roche), Medisafe Fit Smile (Terumo), and OneTouch Ultra Plus Reflect (LifeScan). Approximately 90% of participants stated that a consistent color scheme, eg, for low blood glucose (BG) values, should be used across all BGMSs. There was no clear preference among the four tested BGMSs regarding the specific way of displaying color coding.

CONCLUSIONS

The four BGMSs assessed in this study showed only small differences in an overall sufficient level of accuracy. User handling errors, as observed by study personnel, differed between the systems.

Drug Interference in Self-Monitoring of Blood Glucose and the Impact on Patient Safety: We Can Only Guard Against What We Are Looking for

Self-monitoring of blood glucose is a key aspect of diabetes management. Depending on the technology used, however, various substances can jeopardize the reliability of the measurements and precipitate complications with potentially life-threatening consequences when blood glucose was deemed well-controlled. As such, it is important for all involved to be aware of those factors. Officially suggested procedures for testing and alternatives have each their own advantages and limitations, and interferences may be found beyond the substances to be tested provided by the various pertinent institutions. This article reviews these pros and cons and illustrates how interference testing beyond established standards contributes to patient safety. Once identified, interfering substances are included in product labeling and healthcare professionals and users need to be trained to be aware of these risks.

Urinary and circulatory netrin-1 as biomarker in diabetes and its related complications: a systematic review and meta-analysis

BACKGROUND

Novel biomarkers have been suggested for the diagnosis and prognosis of diabetes mellitus. The biomarker utility of netrin-1 in diabetes as an extracellular protein has been investigated. In this systematic review and meta-analysis, we reviewed the role of netrin-1 as a biomarker in prediabetes, diabetes, and complications of diabetes.

METHODS

PubMed, Embase, Scopus, and Web of Science were systematically searched for studies that measured circulatory and/or urinary netrin-1 levels in diabetes and compared them with non-diabetic patients or evaluated the prognostic role of this marker. Standardized mean difference (SMD) and 95% confidence interval (CI) were calculated using random-effect meta-analysis to compare netrin-1 levels between groups. The impact of mean age, male sex percentage, sample size, mean body mass index, and publication year on the overall heterogeneity was assessed using meta-regression.

RESULTS

Among 413 records from international databases, 19 original studies were included with 2061 cases (1137 diabetics, 196 prediabetics, and 728 healthy controls). Meta-analysis of eight studies measuring netrin-1 in patients with diabetes and comparing it with healthy controls showed no significant difference between the two groups (SMD 0.69, 95% CI -0.78 to 2.16, I2 = 98%, p-value = 0.36). On the other hand, a meta-analysis of netrin-1 levels in patients with prediabetes in comparison with healthy controls revealed that they had lower levels (SMD -0.51, 95% CI -0.81 to -0.21, p-value < 0.01). Diabetic patients with microalbuminuria and macroalbuminuria had significantly higher circulatory netrin-1 levels compared to normoalbuminuric group SMD 1.18, 95% CI 0.83 to 1.53, p-value < 0.01 and SMD 1.67, 95% CI 0.76 to 2.58, p-value < 0.01, respectively). Moreover, no difference in urinary netrin-1 levels was found between micro-, macro-, and normoalbuminuric groups (p-value > 0.05).

CONCLUSION

Netrin-1 showed promising results as a biomarker in diabetes prognosis. However, more studies are required to confirm our findings, and higher sample size studies are needed to evaluate the diagnostic utility of this marker.

Metabolomics Signature in Prediabetes and Diabetes: Insights From Tandem Mass Spectrometry Analysis

OBJECTIVE

This study investigates the metabolic differences between normal, prediabetic and diabetic patients with good and poor glycaemic control (GGC and PGC).

DESIGN

In this study, 1102 individuals were included, and 50 metabolites were analysed using tandem mass spectrometry. The diabetes diagnosis and treatment standards of the American Diabetes Association (ADA) were used to classify patients.

METHODS

The nearest neighbour method was used to match controls and cases in each group on the basis of age, sex and BMI. Factor analysis was used to reduce the number of variables and find influential underlying factors. Finally, Pearson's correlation coefficient was used to check the correlation between both glucose and HbAc1 as independent factors with binary classes.

RESULTS

Amino acids such as glycine, serine and proline, and acylcarnitines (AcylCs) such as C16 and C18 showed significant differences between the prediabetes and normal groups. Additionally, several metabolites, including C0, C5, C8 and C16, showed significant differences between the diabetes and normal groups. Moreover, the study found that several metabolites significantly differed between the GGC and PGC diabetes groups, such as C2, C6, C10, C16 and C18. The correlation analysis revealed that glucose and HbA1c levels significantly correlated with several metabolites, including glycine, serine and C16, in both the prediabetes and diabetes groups. Additionally, the correlation analysis showed that HbA1c significantly correlated with several metabolites, such as C2, C5 and C18, in the controlled and uncontrolled diabetes groups.

CONCLUSIONS

These findings could help identify new biomarkers or underlying markers for the early detection and management of diabetes.

Elevated glycosylated hemoglobin levels are associated with severe acute kidney injury following coronary artery bypass surgery

BACKGROUND

Diabetic patients are at increased risk of acute kidney injury (AKI) following surgery. The significance of uncontrolled diabetes on kidney function after coronary artery bypass grafting (CABG) remains controversial. Our aim was to study the association between pre-operative hemoglobin A1c (HbA1c) and severe cardiac surgery-associated AKI (CSA-AKI) following CABG.

METHODS

A single-center, retrospective cohort study including patients who underwent isolated CABG from 2010 to 2018 was performed. Patients were grouped into pre-operative HbA1c of <6.5 %, 6.5-8.5 %, and ≥8.5 %. Postoperative serum creatinine levels were queried for up to 30 days, and the 30-day risk of severe AKI was compared among groups. Multivariable logistic regression was used to study factors associated with severe CSA-AKI and the association of severe CSA-AKI with postoperative outcomes. Cox regression was used to study the association between severe CSA-AKI and all-cause mortality from the time of surgery to the last follow-up or death.

RESULTS

A total of 2424 patients met the inclusion criteria. Patients were primarily male (70.5 %), with a median age of 64 years (IQR 57-71). Median bypass and cross-clamp times were 95 (IQR 78-116) and 78 min (IQR 63-95). Severe CSA-AKI occurred within 30 days in 5.7 %, 6.7 %, and 9.1 % of patients with pre-op HbA1c of <6.5 %, 6.5-8.5 %, and ≥8.5 %, respectively. After adjusting for covariates, HbA1c >8.5 %, was independently associated with severe CSA-AKI 30 days after CABG (aOR 1.59, 95%CI 1.06-2.40). In addition, severe CSA-AKI was associated with increased 30- (aOR 15.83,95%CI 7.94-31.56) and 90- day mortality (aOR 9.54, 95%CI 5.46-16.67), prolonged length of stay (aOR 3.46,95%CI 2.41-4.96) and unplanned 30-day readmission (aOR 2.64, 95%CI 1.77-3.94). Lastly, severe CSA-AKI was associated with increased all-cause mortality (aHR 3.19, 95%CI 2.43-4.17).

CONCLUSION

Elevated preoperative HbA1c (≥8.5 %) was independently associated with an increased 30-day risk of severe CSA-AKI, which is a consistent predictor of adverse outcomes after CABG. Delaying surgery to achieve optimal glycemic control in an elective setting may be reasonable.

Learning Difference Equations With Structured Grammatical Evolution for Postprandial Glycaemia Prediction

People with diabetes must carefully monitor their blood glucose levels, especially after eating. Blood glucose management requires a proper combination of food intake and insulin boluses. Glucose prediction is vital to avoid dangerous post-meal complications in treating individuals with diabetes. Although traditional methods, and also artificial neural networks, have shown high accuracy rates, sometimes they are not suitable for developing personalised treatments by physicians due to their lack of interpretability. This study proposes a novel glucose prediction method emphasising interpretability: Interpretable Sparse Identification by Grammatical Evolution. Combined with a previous clustering stage, our approach provides finite difference equations to predict postprandial glucose levels up to two hours after meals. We divide the dataset into four-hour segments and perform clustering based on blood glucose values for the two-hour window before the meal. Prediction models are trained for each cluster for the two-hour windows after meals, allowing predictions in 15-minute steps, yielding up to eight predictions at different time horizons. Prediction safety was evaluated based on Parkes Error Grid regions. Our technique produces safe predictions through explainable expressions, avoiding zones D (0.2% average) and E (0%) and reducing predictions on zone C (6.2%). In addition, our proposal has slightly better accuracy than other techniques, including sparse identification of non-linear dynamics and artificial neural networks. The results demonstrate that our proposal provides interpretable solutions without sacrificing prediction accuracy, offering a promising approach to glucose prediction in diabetes management that balances accuracy, interpretability, and computational efficiency.

Postoperative Length of Stay in Patients With Stress Hyperglycemia Compared to Patients With Diabetic Hyperglycemia: A Retrospective Cohort Study

BACKGROUND

Postoperative hospital length of stay (LOS) is longer in patients with diabetes than in patients without diabetes. Stress hyperglycemia (SH) in patients without a history of diabetes has been associated with adverse postoperative outcomes. The effect of SH on postoperative LOS is uncertain. The aim of this study is to compare postoperative LOS in patients with SH to patients with diabetic hyperglycemia (DH) following noncardiac surgery.

METHODS

We carried out a retrospective cohort study of inpatients with at least two glucose measurements ≥180 mg/dL. Two groups were compared. Patients with SH had no preoperative history of diabetes. Patients were considered to have DH if they had an established preoperative diagnosis of diabetes mellitus or a preoperative hemoglobin A1c (HbA1c) ≥6.5%. The primary outcome measure was hospital LOS.

RESULTS

We included 270 patients with postoperative hyperglycemia-82 in the SH group and 188 in the DH group. In a linear regression analysis, hospital LOS was longer in the SH group than in the DH group (10.4 vs 7.3 days; P = .03). Within the SH group, we found no association between LOS and prompt treatment of hyperglycemia within 12 hours (P = .43), insulin dose per day (P = .89), or overall mean glucose (P = .13).

CONCLUSIONS

Postoperative LOS was even longer in patients with SH than in patients with DH, representing a potential target for quality improvement efforts. We did not, however, find evidence that improved treatment of SH was associated with reduction in LOS.

Digital technology and healthcare delivery in insulin-treated adults with diabetes: a proposal for analysis of self-monitoring blood glucose patterns using a dedicated platform

PURPOSE

A remote platform for diabetes care (Roche Diabetes® Care Platform, RDCP) has been developed that allows combined face-to-face consultations and remote patient monitoring (RPM).

METHODS

A dedicated flowchart is proposed as a clinical approach to help healthcare professionals in the appropriate interpretation of structured self-monitoring blood glucose data, as visualized on the RDCP during the visits, and in the optimal management of patients using the integrated RDCP-RPM tools.

RESULTS

The platform organizes patterns in different blocks: (i) hypoglycemia; (ii) hyperglycemia; (iii) blood glucose variability; (iv) treatment adherence, which identifies a possible individual pattern according to glycemic control challenges, potential causal factors, and behavioral type patterns. The flowchart proposed for use of the RDCP-RPM is self-explanatory and entails 3 steps: (1) evaluation of quality and quantity of self-monitoring blood glucose data; (2) pattern analysis; (3) personalized suggestions and therapy changes.

CONCLUSION

The main aim of the remote treatment flowchart proposed is to support healthcare professionals in the identification of hypoglycemic and hyperglycemic patterns using the RDCP regardless of the HbA1c value and ongoing treatment, which however, become crucial in combination with pattern analysis in the therapeutical choice.

Changes in glucometric parameters in people living with diabetes users of the free-style libre 2 system before and after the update possibility to real-time glucose readings in real world practice

In Spain, from October 10th, 2023, the FreeStyle Libre 2 system offers the possibility to automatically changed from isCGM to rtCGM with a system update. Our study aimed to evaluate the glucometric before and after that date. We didn't find significant changes in TIR, however time of use increased and TBR decreased.

Plasma Glucose Concentrations in Different Sampling Tubes Measured on Different Glucose Analysers

INTRODUCTION

The German Diabetes Association recommends using sampling tubes with citrate and fluoride additives to diagnose diabetes by oral glucose tolerance test to inhibit glycolysis. The effect of different tubes on measurement results was assessed.

MATERIALS AND METHODS

In a first study, an oral glucose tolerance test was performed on 41 participants without anamnestically known diabetes. Venous blood was sampled in two different tubes with citrate/fluoride additives from different manufacturers and one with only lithium-heparin additive. A second study with 42 participants was performed to verify the initial results with an adapted design, in which a third tube with citrate buffer was used, and glucose measurements were performed on two additional devices of another analyser model. Samples were centrifuged either immediately (<5 min incubation time) or after 20 min or 4 h. All glucose measurements were performed in plasma. Glucose concentrations in lithium-heparin tubes with<5 min incubation time served as baseline concentrations.

RESULTS

In the first study, glucose concentrations in one of the citrate/fluoride tubes were similar to the baseline. In the other citrate/fluoride tube, markedly lower concentrations (approximately - 5 mg/dL (- 0.28 mmol/L)) were measured. This was reproduced in the verification study for the same analyser, but not with the other analyser model. Lithium-heparin tubes centrifuged after 20 and 240 min showed systematically lower glucose concentrations.

CONCLUSIONS

The results confirm that glycolysis can be effectively inhibited in citrate/fluoride-containing sampling tubes. However, glucose measurement results of one analyser showed a relevant negative bias in tubes containing liquid citrate buffer.

Feasibility and Performance of Continuous Glucose Monitoring to Guide Computerized Insulin Infusion Therapy in Cardiovascular Intensive Care Unit

BACKGROUND

We evaluated the feasibility of real-time continuous glucose monitoring (CGM) for titrating continuous intravenous insulin infusion (CII) to manage hyperglycemia in postoperative individuals in the cardiovascular intensive care unit and assessed their accuracy, nursing acceptance, and postoperative individual satisfaction.

METHODS

Dexcom G6 CGM devices were applied to 59 postsurgical patients with hyperglycemia receiving CII. A hybrid approach combining CGM with periodic point-of-care blood glucose (POC-BG) tests with two phases (initial-ongoing) of validation was used to determine CGM accuracy. Mean and median absolute relative differences and Clarke Error Grid were plotted to evaluate the CGM accuracy. Surveys of nurses and patients on the use of CGMs experience were conducted and results were analyzed.

RESULTS

In this cohort (mean age 64, 32% female, 32% with diabetes) with 864 paired POC-BG and CGM values analyzed, mean and median absolute relative difference between POC-BG and CGM values were 13.2% and 9.8%, respectively. 99.7% of paired CGM and POC-BG were in Zones A and B of the Clarke Error Grid. Responses from nurses reported CGMs being very or quite convenient (n = 28; 93%) and it was favored over POC-BG testing (n = 28; 93%). Majority of patients (n = 42; 93%) reported their care process using CGM as being good or very good.

CONCLUSION

This pilot study demonstrates the feasibility, accuracy, and nursing convenience of adopting CGM via a hybrid approach for insulin titration in postoperative settings. These findings provide robust rationale for larger confirmatory studies to evaluate the benefit of CGM in postoperative care to improve workflow, enhance health outcomes, and cost-effectiveness.

Longitudinal Digital Glucometric Benchmarking to Evaluate the Impact of Institutional Diabetes Care Initiatives in Adults With Diabetes Mellitus Over the 2016-2020 Period

BACKGROUND

While glucometric benchmarking has been used to compare glucose management between institutions, the value of longitudinal intra-institution benchmarking to assess quality improvement changes is not established.

METHODS

A prospective six-month observational study (October 2019-March 2020 inclusive) of inpatients with diabetes or newly detected hyperglycemia admitted to eight medical and surgical wards at the Royal Melbourne Hospital. Networked blood glucose (BG) meters were used to collect capillary BG levels. Outcomes were measures of glycemic control assessed by mean and threshold glucometric measures and comparison with published glucometric benchmarks. Intra-institution comparison was over the 2016-2020 period.

RESULTS

In all, 620 admissions (588 unique individuals) met the inclusion criteria, contributing 15 164 BG results over 4023 admission-days. Compared with the 2016 cohort from the same institution, there was increased BG testing (3.8 [SD = 2.2) vs 3.3 [SD = 1.7] BG measurements per patient-day, P < .001), lower mean patient-day mean glucose (PDMG; 8.9 mmol/L [SD = 3.2] vs 9.5 mmol/L [SD = 3.3], P < .001), and reduced mean and threshold measures of hyperglycemia (P < .001 for all). Comparison with institutions across the United States revealed lower incidence of mean PDMG >13.9 or >16.7 mmol/L, and reduced hypoglycemia (<3.9, <2.8, and <2.2 mmol/L), when compared with published benchmarks from an earlier period (2009-2014).

CONCLUSIONS

Comprehensive digital-based glucometric benchmarking confirmed institutional quality improvement changes were followed by reduced hyperglycemia and hypoglycemia in a five-year comparison. Longitudinal glucometric benchmarking enables evaluation and validation of changes to institutional diabetes care management practices.

JMJD6 Autoantibodies as a Potential Biomarker for Inflammation-Related Diseases

Inflammation is closely associated with cerebrovascular diseases, cardiovascular diseases, diabetes, and cancers, and it is accompanied by the development of autoantibodies in the early stage of inflammation-related diseases. Hence, it is meaningful to discover novel antibody biomarkers targeting inflammation-related diseases. In this study, Jumonji C-domain-containing 6 (JMJD6) was identified by the serological identification of antigens through recombinant cDNA expression cloning. In particular, JMJD6 is an antigen recognized in serum IgG from patients with unstable angina pectoris (a cardiovascular disease). Then, the serum antibody levels were examined using an amplified luminescent proximity homogeneous assay-linked immunosorbent assay and a purified recombinant JMJD6 protein as an antigen. We observed elevated levels of serum anti-JMJD6 antibodies (s-JMJD6-Abs) in patients with inflammation-related diseases such as ischemic stroke, acute myocardial infarction (AMI), diabetes mellitus (DM), and cancers (including esophageal cancer, EC; gastric cancer; lung cancer; and mammary cancer), compared with the levels in healthy donors. The s-JMJD6-Ab levels were closely associated with some inflammation indicators, such as C-reactive protein and intima-media thickness (an atherosclerosis index). A better postoperative survival status of patients with EC was observed in the JMJD6-Ab-positive group than in the negative group. An immunohistochemical analysis showed that JMJD6 was highly expressed in the inflamed mucosa of esophageal tissues, esophageal carcinoma tissues, and atherosclerotic plaques. Hence, JMJD6 autoantibodies may reflect inflammation, thereby serving as a potential biomarker for diagnosing specific inflammation-related diseases, including stroke, AMI, DM, and cancers, and for prediction of the prognosis in patients with EC.

Diabetes mellitus, systemic inflammation and overactive bladder

Background

Increasing evidence emphasizes the potential relationship between diabetes and OAB (overactive bladder). However, large population epidemiology is still lacking.

Methods

This cross-sectional study included six cycle NHANES surveys, with a total of 23863 participants. Logistic regression models were constructed to analyze the association between diabetes mellitus, diabetes-related markers, and inflammatory biomarkers with OAB. Restricted cubic splines were used to analyze the non-linear associations. Mediating analysis was performed to test the effect of inflammatory biomarkers on the relationship between diabetes-related markers and OAB. Finally, machine learning models were applied to predict the relative importance and construct the best-fit model.

Results

Diabetes mellitus participants' OAB prevalence increased by 77% compared with non-diabetes. As the quartiles of diabetes-related markers increased, the odds of OAB monotonically increased in three models (all p for trend < 0.001). Glycohemoglobin exhibited a linear association with OAB (p for nonlinearity > 0.05). White blood cells significantly mediated the associations between diabetes-related markers (glycohemoglobin, fasting glucose, and insulin) with OAB, and the proportions were 7.23%, 8.08%, and 17.74%, respectively (all p < 0.0001). Neutrophils partly mediated the correlation between (glycohemoglobin, fasting glucose, and insulin) and OAB at 6.58%, 9.64%, and 17.93%, respectively (all p < 0.0001). Machine learning of the XGBoost model constructs the best fit model, and XGBoost predicts glycohemoglobin is the most important indicator on OAB.

Conclusion

Our research revealed diabetes mellitus and diabetes-related markers were remarkably associated with OAB, and systemic inflammation was an important mediator of this association.

Effect of glycotoxicity and lipotoxicity on carbohydrate antigen 19 - 9 in the patients with diabetes

OBJECTIVES

In comparison to the subjects without diabetes, a greater concentration of serum carbohydrate antigen 19 - 9 (CA 19 - 9) was observed in the subjects with diabetes. Nevertheless, since the occurrence of abnormal CA 19 - 9 is not widespread among the whole diabetic population, this phenomenon has not attracted enough attention. The prevalence of abnormal CA 19 - 9 in hospitalized patients with diabetes was the focus of our research.

METHOD

A total of 385 subjects with diabetes and 200 controls were enrolled and all had been tested the CA19-9 levels. Cases of cancers were excluded through examination and followup for 1 year.

RESULTS

We found that the rate of patients with abnormal CA19-9 level was 8.3%. The rate of patients with abnormal CA19-9 level was 14.0% in the HbA1c ≥ 9% group, and 3.0% in the HbA1c < 9% group, 2.5% in the control group. There was no significant difference in the HbA1c < 9% group and the control group. A significant correlation between serum CA19-9 and both HbA1c and total cholesterol was observed, yet no difference in CRP level was observed between subjects with normal CA19-9 level and subjects with abnormal CA19-9 level. However, a significant difference in fasting C-peptide levels was observed between the two groups, p = 0.039.

CONCLUSION

The percentage of patients with diabetes exhibiting elevated CA19-9 level is 14% in the HbA1c ≥ 9% diabetic patients, much higher than expected. The underlying mechanism may be related to islet injury caused by glycotoxicity and lipotoxicity.

STRENGTHS AND LIMITATIONS OF THE STUDY

We studied the rate of hospitalized diabetic patients with elevated CA 19 - 9 which were characterized with poorly controlled blood glucose. We found that the elevation of CA 19 - 9 was unexpectedly high in diabetic inpatients without development to cancer. The limitation of this study is that the underlying mechanism is not sufficiently studied.

Very short sleep duration reveals a proteomic fingerprint that is selectively associated with incident diabetes mellitus but not with incident coronary heart disease: a cohort study

BACKGROUND

The molecular pathways linking short and long sleep duration with incident diabetes mellitus (iDM) and incident coronary heart disease (iCHD) are not known. We aimed to identify circulating protein patterns associated with sleep duration and test their impact on incident cardiometabolic disease.

METHODS

We assessed sleep duration and measured 78 plasma proteins among 3336 participants aged 46-68 years, free from DM and CHD at baseline, and identified cases of iDM and iCHD using national registers. Incident events occurring in the first 3 years of follow-up were excluded from analyses. Tenfold cross-fit partialing-out lasso logistic regression adjusted for age and sex was used to identify proteins that significantly predicted sleep duration quintiles when compared with the referent quintile 3 (Q3). Predictive proteins were weighted and combined into proteomic scores (PS) for sleep duration Q1, Q2, Q4, and Q5. Combinations of PS were included in a linear regression model to identify the best predictors of habitual sleep duration. Cox proportional hazards regression models with sleep duration quintiles and sleep-predictive PS as the main exposures were related to iDM and iCHD after adjustment for known covariates.

RESULTS

Sixteen unique proteomic markers, predominantly reflecting inflammation and apoptosis, predicted sleep duration quintiles. The combination of PSQ1 and PSQ5 best predicted sleep duration. Mean follow-up times for iDM (n = 522) and iCHD (n = 411) were 21.8 and 22.4 years, respectively. Compared with sleep duration Q3, all sleep duration quintiles were positively and significantly associated with iDM. Only sleep duration Q1 was positively and significantly associated with iCHD. Inclusion of PSQ1 and PSQ5 abrogated the association between sleep duration Q1 and iDM. Moreover, PSQ1 was significantly associated with iDM (HR = 1.27, 95% CI: 1.06-1.53). PSQ1 and PSQ5 were not associated with iCHD and did not markedly attenuate the association between sleep duration Q1 with iCHD.

CONCLUSIONS

We here identify plasma proteomic fingerprints of sleep duration and suggest that PSQ1 could explain the association between very short sleep duration and incident DM.

Severity of COVID-19 infection in patients with COVID-19 combined with diabetes

PURPOSE

This study aimed to analyse the correlation between blood glucose control and the severity of COVID-19 infection in patients with diabetes.

METHODS

Clinical and imaging data of a total of 146 patients with diabetes combined with COVID-19 who visited our hospital between December 2022 and January 2023 were retrospectively collected. The patients were divided into the 'good blood glucose control' group and the 'poor blood glucose control' group based on an assessment of their blood glucose control. The clinical data, computed tomography (CT) appearance and score and the severity of COVID-19 infection of the two groups were compared, with the severity of COVID-19 infection being the dependent variable to analyse other influencing factors.

RESULTS

The group with poor blood glucose control showed a higher lobar involvement degree and total CT severity score (CTSS) than the group with good blood glucose control (13.30 ± 5.25 vs. 10.38 ± 4.84, p < 0.05). The two groups exhibited no statistically significant differences in blood lymphocyte, leukocyte, C-reaction protein, pleural effusion, consolidation, ground glass opacity or crazy-paving signs. Logistic regression analysis showed that the total CTSS significantly influences the clinical severity of patients (odds ratio 1.585, p < 0.05), whereas fasting plasma glucose and blood glucose control are not independent factors influencing clinical severity (both p > 0.05). The area under the curve (AUC) of CTSS prediction of critical COVID-19 was 0.895 with sensitivity of 79.3% and specificity of 88.1% when the threshold value is 12.

CONCLUSION

Blood glucose control is significantly correlated with the CTSS; the higher the blood glucose is, the more severe the lung manifestation. The CTSS can also be used to evaluate and predict the clinical severity of COVID-19.

Investigating the Role of FABP4 in Diabetes and Obesity and the Influence of Age and Ethnicity: A Comprehensive Analysis of a Cohort from the KEDP-Study

Adipocyte P2 (aP2), also known as FABP4, is an adipokine that adipose tissue produces and expresses in macrophages. Its primary role is to facilitate the transportation of fatty acids across cell membranes. Numerous studies have reported associations between FABP4 and the development of metabolic disorders. However, there is limited knowledge regarding FABP4 expression in diabetes and obesity, especially about different age groups, genders, and ethnicities. This study aims to investigate the association between FABP4 levels, diabetes mellitus, and obesity within various ethnic groups. We measured plasma FABP4 concentrations in a cohort of 2083 patients from the KDEP study and gathered anthropometric data. Additionally, we collected and analyzed clinical, biochemical, and glycemic markers using multivariate regression analysis. The average FABP4 concentration was significantly higher in female participants than in males (18.8 ng/mL vs. 14.4 ng/mL, p < 0.001, respectively), and in those over 50 years old compared to those under 50 years of age (19.3 ng/mL vs. 16.2 ng/mL, p < 0.001, respectively). In this study, significant positive associations were found between the plasma level of FABP4 and obesity markers: BMI (r = 0.496, p < 0.001), hip circumference (r = 0.463, p < 0.001), and waist circumference (WC) (r = 0.436, p < 0.001). Similar observations were also seen with glycemic markers, which included HbA1c (r = 0.126, p < 0.001), fasting blood glucose (FBG) (r = 0.184, p < 0.001), fasting insulin (r = 0.326, p < 0.001), and HOMA-IR (r = 0.333, p < 0.001). Importantly, these associations remained significant even after adjusting for age, gender, and ethnicity. Furthermore, FABP4 levels were negatively associated with male gender (β: -3.85, 95% CI: -4.92, -2.77, p < 0.001), and positively associated with age (β: 0.14, 95% CI: 0.096, 0.183, p < 0.001), BMI (β: 0.74, 95% CI: 0.644, 0.836, p < 0.001), and fasting insulin (β: 0.115, 95% CI: 0.091, 0.138, p < 0.001). In this study, plasma FABP4 levels were significantly higher in diabetic and obese participants, and they were strongly influenced by age, gender, and ethnicity. These findings suggest that FABP4 may serve as a valuable prognostic and diagnostic marker for obesity and diabetes, particularly among female patients, individuals over 50 years old, and specific ethnic groups.

The impact of triglyceride glucose-body mass index on all-cause and cardiovascular mortality in elderly patients with diabetes mellitus: evidence from NHANES 2007-2016

BACKGROUND

The relationship between triglyceride glucose-body mass index (TyG-BMI) index and mortality in elderly patients with diabetes mellitus (DM) are still unclear. This study aimed to investigate the association between TyG-BMI with all-cause and cardiovascular mortality among elderly DM patients in the United States (US).

METHODS

Patients aged over 60 years with DM from the National Health and Nutrition Examination Survey (2007-2016) were included in this study. The study endpoints were all-cause and cardiovascular mortality and the morality data were extracted from the National Death Index (NDI) which records up to December 31, 2019. Multivariate Cox proportional hazards regression model was used to explore the association between TyG-BMI index with mortality. Restricted cubic spline was used to model nonlinear relationships.

RESULTS

A total of 1363 elderly diabetic patients were included, and were categorized into four quartiles. The mean age was 70.0 ± 6.8 years, and 48.6% of them were female. Overall, there were 429 all-cause deaths and 123 cardiovascular deaths were recorded during a median follow-up of 77.3 months. Multivariate Cox regression analyses indicated that compared to the 1st quartile (used as the reference), the 3rd quartile demonstrated a significant association with all-cause mortality (model 2: HR = 0.64, 95% CI 0.46-0.89, P = 0.009; model 3: HR = 0.65, 95% CI 0.43-0.96, P = 0.030). Additionally, the 4th quartile was significantly associated with cardiovascular mortality (model 2: HR = 1.83, 95% CI 1.01-3.30, P = 0.047; model 3: HR = 2.45, 95% CI 1.07-5.57, P = 0.033). The restricted cubic spline revealed a U-shaped association between TyG-BMI index with all-cause mortality and a linear association with cardiovascular mortality, after adjustment for possible confounding factors.

CONCLUSIONS

A U-shaped association was observed between the TyG-BMI index with all-cause mortality and a linear association was observed between the TyG-BMI index with cardiovascular mortality in elderly patients with DM in the US population.

Development of sensor system and data analytic framework for non-invasive blood glucose prediction

Periodic quantification of blood glucose levels is performed using painful, invasive methods. The proposed work presents the development of a noninvasive glucose-monitoring device with two sensors, i.e., finger and wrist bands. The sensor system was designed with a near-infrared (NIR) wavelength of 940 nm emitter and a 900-1700 nm detector. This study included 101 diabetic and non-diabetic volunteers. The obtained dataset was subjected to pre-processing, exploratory data analysis (EDA), data visualization, and integration methods. Ambiguities such as the effects of skin color, ambient light, and finger pressure on the sensor were overcome in the proposed 'niGLUC-2.0v'. niGLUC-2.0v was validated with performance metrics where accuracy of 99.02%, mean absolute error (MAE) of 0.15, mean square error (MSE) of 0.22 for finger, and accuracy of 99.96%, MAE of 0.06, MSE of 0.006 for wrist prototype with ridge regression (RR) were achieved. Bland-Altman analysis was performed, where 98% of the data points were within ± 1.96 standard deviation (SD), 100% were under zone A of the Clarke Error Grid (CEG), and statistical analysis showed p < 0.05 on evaluated accuracy. Thus, niGLUC-2.0v is suitable in the medical and personal care fields for continuous real-time blood glucose monitoring.

Independent Correlates of Glycemic Control among Adults with Diabetes in South Africa

BACKGROUND

Globally, the prevalence of diabetes is increasing, especially in low- and middle-income countries (LMICs), including those in the sub-Saharan African region. However, the independent socioeconomic correlates of glycemic control as measured by hemoglobin A1C have yet to be identified. Therefore, the aim of this analysis was to understand the independent correlates of glycemic control in South Africa.

METHODS

Data from the 2016 South Africa Demographic and Health Survey on adults with diabetes were used for this analysis. The dependent variable, glycemic control, was defined using hemoglobin A1c (HbA1c). Independent variables included: age, gender, ethnicity, marital status, region, urban/rural residence, ability to read, education, insurance, wealth, occupation, and employment in the last year. Analysis of variance was used to test for differences in mean HbA1c for each category of all independent variables, and a fully adjusted linear regression model was used to identify independent correlates of glycemic control (HbA1c).

RESULTS

Among the 772 people included in this analysis, there were significant differences in mean HbA1c by age (p < 0.001), ethnicity (p < 0.001), place of residence (p = 0.024), wealth index (p = 0.001), and employment in the last year (p = 0.008). Independent correlates of HbA1c included age, ethnicity, and wealth index.

CONCLUSIONS

This study used data from a large diverse population with a high prevalence of diabetes in sub-Saharan Africa and provides new evidence on the correlates of glycemic control and potential targets for interventions designed to lower HbA1c and improve diabetes-related health outcomes of adults in South Africa.

Free triiodothyronine to free thyroxine ratio as a marker of poor prognosis in euthyroid patients with acute coronary syndrome and diabetes after percutaneous coronary intervention

Objectives

In recent years, the free triiodothyronine/free thyroxine (FT3/FT4) ratio, a new comprehensive index for evaluating thyroid function, which could reflect thyroid function more stably and truly than serum thyroid hormone level, has been demonstrated to correlate with the risks of diabetes and cardiovascular disease in euthyroid adults. However, the correlation between thyroid hormone sensitivity and long-term prognosis in euthyroid patients with acute coronary syndrome (ACS) and diabetes after percutaneous coronary intervention (PCI) remains unclear.

Methods

A total of 1,786 euthyroid patients with ACS who successfully underwent PCI at Beijing Anzhen Hospital from August 2021 to April 2022 were included in our study, which was divided into three groups according to tertiles of thyroid hormone sensitivity index. Cox regression, Kaplan-Meier, and receiver operating characteristic analyses were applied to analyze the associations between the FT3/FT4 ratio with ACS and diabetes after PCI.

Results

Our analysis indicated that a lower level of FT3/FT4 ratio in euthyroid patients with acute coronary syndrome (ACS) and diabetes after PCI showed significantly higher incidences of major adverse cardiac and cerebrovascular events (MACCE) when compared with a higher level of FT3/FT4 ratio. After adjusting for other covariates, patients with a lower level of FT3/FT4 ratio were negatively associated with the risk of MACCE than those with a higher level of FT3/FT4 ratio (adjusted OR =1.61, 95% CI 1.05-2.47, P = 0.028). In subgroup analyses, individuals were stratified by age, sex, BMI, ACS type, hypertension, and dyslipidemia, showing that there were no significant interactions between the FT3/FT4 ratio and all subgroups for MACCE. In addition, the FT3/FT4 ratio performed better on ROC analyses for cardiac death prediction [area under the curve (AUC), 0.738].

Conclusion

A reduced level of FT3/FT4 ratio was a potential marker of poor prognosis in euthyroid patients with ACS and diabetes after PCI.

Inflammatory risk of albumin combined with C-reactive protein predicts long-term cardiovascular risk in patients with diabetes

AIMS

The purpose of this study was to evaluate the predictive value of inflammatory risk as defined by the Glasgow Prognostic Score (GPS) for cardiovascular death in patients with diabetes.

METHODS

This study included 4956 patients (≥18 years old) with diabetes in the National Health and Nutrition Survey from 1999 to 2010. The mortality rate was determined by the correlation with the national death index on December 31, 2019. The GPS was composed of the serum C-reactive protein and the albumin. The primary outcome was cardiovascular death and the secondary outcome was all-cause death. The Cox proportional risk model adjusted for demographic factors and traditional cardiovascular risk factors was used to analyze the cumulative risk of outcomes.

RESULTS

Among 4956 diabetes patients with a median follow-up of 10.9 years, 601 cardiovascular deaths and 2187 all-cause deaths were recorded. After adequate model adjustment, compared with the low GPS group, the high GPS group (HR, 1.257 (1.007-1.570), P = 0.043) had a higher cardiovascular mortality. Compared with the low GPS group, the all-cause mortality of the high GPS group (HR, 1.394 (1.245-1.560), P < 0.001) was higher. The results of subgroup analyses were similar with that of the overall cohort.

CONCLUSIONS

The inflammatory risk as defined by the GPS was closely related to the increased risk of cardiovascular and all-cause death in patients with diabetes. It may be a convenient and efficient clinical practical risk assessment tool for patients with diabetes.

Research-based Analytical Procedures to Evaluate Diabetic Biomarkers and Related Parameters: In Vitro and In Vivo Methods

BACKGROUND

The degenerative tendency of diabetes leads to micro- and macrovascular complications due to abnormal levels of biochemicals, particularly in patients with poor diabetic control. Diabetes is supposed to be treated by reducing blood glucose levels, scavenging free radicals, and maintaining other relevant parameters close to normal ranges. In preclinical studies, numerous in vivo trials on animals as well as in vitro tests are used to assess the antidiabetic and antioxidant effects of the test substances. Since a substance that performs poorly in vitro won't perform better in vivo, the outcomes of in vitro studies can be utilized as a direct indicator of in vivo activities.

OBJECTIVE

The objective of the present study is to provide research scholars with a comprehensive overview of laboratory methods and procedures for a few selected diabetic biomarkers and related parameters.

METHOD

The search was conducted on scientific database portals such as ScienceDirect, PubMed, Google Scholar, BASE, DOAJ, etc. Conclusion: The development of new biomarkers is greatly facilitated by modern technology such as cell culture research, lipidomics study, microRNA biomarkers, machine learning techniques, and improved electron microscopies. These biomarkers do, however, have some usage restrictions. There is a critical need to find more accurate and sensitive biomarkers. With a few modifications, these biomarkers can be used with or even replace conventional markers of diabetes.

Serum uric acid is associated with chronic kidney disease in elderly Chinese patients with diabetes

BACKGROUND

The relationship between hyperuricemia and chronic kidney disease (CKD) has been investigated extensively. However, studies on elderly individuals are still limited. Moreover, there is no consensus on whether hyperuricemia or elevated serum uric acid (SUA) within the normal range is correlated with the new onset of CKD and whether there are differences between males and females.

METHODS

We included 39039 elderly diabetic patients without CKD at baseline from a community-based cohort in Wuhan, China. The outcome event was the new onset of CKD (defined as an estimated glomerular filtration rate < 60 mL/min/1.73 m2). Multivariate Cox models were used to assess the adjusted hazard ratio (HR).

RESULTS

During the 2-year follow-up period, 3162 (8.10%) patients with diabetes developed new-onset CKD. The optimal cutoff value of SUA for incident CKD was 347.4 μmol/L. The adjusted HRs of hyperuricemia for new-onset CKD were 1.925 (1.724-2.150) and 1.676 (1.520-1.848) for males and females, respectively. The risk of developing CKD increased across the Q4 group up to 2.242 times for their counterparts in the lowest SUA quartile, independent of age, sex, diabetes duration, obesity, hypertension, systolic blood pressure, diastolic blood pressure, smoking, drinking, dyslipidemia, triglyceride, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and fasting plasma glucose.

CONCLUSIONS

Hyperuricemia is an independent predictor of incident CKD. Elevated SUA was linearly correlated with CKD in elderly patients with diabetes, showing a relatively higher intensity among males compared with that among females. The optimal cutoff value of SUA for the risk of new-onset CKD in elderly patients with diabetes was 347.4 μmol/L.

Serum cystatin C for risk stratification of prediabetes and diabetes populations

BACKGROUND

The association between serum cystatin C level and vascular outcomes has not been fully elucidated in diabetes and is unclear in prediabetes. We aim to evaluate whether cystatin C level predicts future risk for mortality and vascular outcomes in prediabetes and diabetes.

METHODS

A total of 85,371 participants with prediabetes and diabetes, and available baseline cystatin C in the UK biobank were included with a 14-year follow-up. Cox hazards models were used to calculate the associations between cystatin C level, mortality (all-cause, cause-specfic mortality) and vascular outcomes (myocardial infarction [MI], stroke, end-stage renal disease [ESRD] and diabetic retinopathy [DR]). The 1136 diabetes subjects in Guangzhou Diabetic Eye Study (GDES) were included for examing the impact of cystatin C on in vivo retinal degeneration and microvascular changes by using SS-OCT and OCTA.

RESULTS

The highest cystatin C quartile had increased risks of all-cause (hazard ratio [HR], 2.02; 95% confidence interval [CI] 1.86-2.19), cardiovascular (HR, 2.29; 95% CI 1.97-2.67), cancer (HR, 1.86; 95% CI 1.65-2.10) and other-cause mortality (HR, 2.24; 95% CI 1.90-2.64), MI (HR, 1.40; 95% CI 1.26-1.55), stroke (HR, 1.88; 95% CI, 1.57-2.26), ESRD (HR, 7.33; 95% CI, 5.02-10.71), DR (HR, 1.17; 95% CI 1.03-1.32) than those in the lowest quartile. Adding cystatin C to the conventional model improved C-statistic for all-cause (0.699-0.724), cardiovascular (0.762-0.789), cancer (0.661-0.674) and other-cause mortality (0.675-0.715), MI (0.748-0.750), stroke (0.712-0.718), and ESRD (0.808-0.827). The GDES analysis identified a strong association between increased cystatin C levels and diminished retinal neural layers, as well as microvascular rarefaction in both macular and optic disc regions (all P < 0.05).

CONCLUSIONS

Serum cystatin C refines the risk stratification for mortality and vascular outcomes among patients with prediabetes or diabetes.

Serum uric acid to high-density lipoprotein cholesterol ratio is a promising marker for identifying metabolic syndrome in nondiabetic Chinese men

OBJECTIVES

To explore the relationship between serum uric acid (UA) and high-density lipoprotein cholesterol (HDL-C) ratio (UHR) and metabolic syndrome (MetS) in nondiabetic individuals.

METHODS

A total of 15,760 nondiabetic participants were screened from the China National Diabetes and Metabolic Disorders Study. Pearson correlation was used to determine the correlation between the components of MetS and UHR, HDL-C, and UA. Receiver operating characteristic curves were used to evaluate the ability of UHR, HDL-C, and UA to identify MetS in the nondiabetic population.

RESULTS

A total of 6,386 men and 9,374 women were enrolled in this study. There were 1,480 (23.2%) men and 1,828 (19.5%) women with MetS. UHR significantly correlated with the components of MetS in men and women, especially with waist circumference  and triglyceride. In men, although HDL-C showed a higher specificity index, UHR presented higher sensitivity index and area under the curve (AUC) than HDL-C (P = 0.0001) and UA (P < 0.0001), with AUC (95% CI) of 0.762 (0.752-0.773). Higher AUCs of UHR relative to HDL-C and UA were also observed in the age groups <40 and 40-59 years. There was no significant difference in AUC between UHR and HDL-C in the age group ≥60 years (P = 0.370). However, similar results were not observed in women.

CONCLUSION

UHR significantly correlated with the components of MetS and could serve as a novel and reliable marker for identifying the population at a high risk of MetS in nondiabetic men, especially in younger adults.

Association between serum ALT levels and incidence of new-onset diabetes in general population of Japanese: a longitudinal observational study (ISSA-CKD)

OBJECTIVE

We aimed to clarify the relationship between serum alanine transaminase (ALT) levels and incidence of new-onset diabetes in a Japanese general population.

SETTING

Population-based retrospective cohort study using annual health check-up data for residents of Iki City, Nagasaki Prefecture, Japan.

PARTICIPANTS

A total of 5330 Japanese individuals (≥30 years old) without diabetes at baseline were analysed.

PRIMARY AND SECONDARY OUTCOME MEASURES

Serum ALT levels were determined using an enzymatic method and were classified into gender-specific quartile groups as follows: group 1 (3-16 U/L in men and 3-13 U/L in women), group 2 (17-21 U/L in men and 14-16 U/L in women), group 3 (22-29 U/L in men and 17-22 U/L in women) and group 4 (30-428 U/L in men and 23-268 U/L in women). The study outcome was the incidence of diabetes (fasting glucose ≥7.0 mmol/L, non-fasting glucose ≥11.1 mmol/L, glycated haemoglobin ≥6.5% or use of glucose-lowering therapies).

RESULTS

After an average follow-up period of 5.0 years, 279 individuals developed diabetes. The incidence rate of diabetes increased with elevation of serum ALT levels (0.7% per 100 person-years in group 1, 0.9% in group 2, 0.9% in group 3 and 1.7% in group 4) (p<0.001 for trend). This association was significant after adjustment for other risk factors including age, sex, obesity, hypertension, dyslipidaemia, smoking, current daily alcohol intake and regular exercise (p<0.001 for trend). Comparable associations were observed between men and women (p=0.459 for interaction).

CONCLUSION

Serum ALT levels were associated with future development of diabetes in the general Japanese population.

Comparison of vitamin D levels in diabetes mellitus patients with and without diabetic foot ulcers: An analytical observational study in Jakarta, Indonesia

Diabetic foot ulcer (DFU) is a form of chronic wound which becomes a serious complication in diabetes mellitus (DM). Recently, the role of vitamin D on T cell-mediated immunity, pancreatic insulin secretion, and its mechanism on cell growth and healing processes have been reported. This study aims to compare the vitamin D level of DM patients with DFU and without DFU to assess the duration and severity of DFU and its correlation with vitamin D levels. The sociodemographic characteristics and DFU duration were documented. The severity was examined in accordance with PEDIS classification. 25-hydroxyvitamin D (25[OH]D) was analysed using in-vitro chemiluminescent immunoassay (CLIA). Statistical analysis was performed and the P-value <.05 was considered as statistically significant. The vitamin D levels in DM patients with and without DFU were 8.90 ng/mL (6.52-10.90) and 16.25 ng/mL (13-19.59), respectively, with P < .001. There was no correlation between the duration of DFU and DFU severity by PEDIS score with vitamin D levels. Vitamin D levels in DM patients with DFU are lower than those in patients without DFU. However, there was insufficient evidence to conclude that there is no correlation between the DFU duration and DFU severity by PEDIS score with vitamin D levels.

Is HbA1c an Indicator of Diabetic Ketoacidosis Severity in the Pediatric Population?

ABSTRACT

Glycosylated hemoglobin (HbA1c) reflects how well blood glucose is controlled and is one of the strongest predictors of chronic complications of diabetes mellitus. The degree of acidosis helps determine the severity of diabetic ketoacidosis (DKA) (mild: pH 7.2-7.3; moderate: pH 7.1-7.2; severe: pH <7.1) and guides the level of care and predicts outcome. Many studies have implicated that higher HbA1c levels lead to recurrent DKA. However, there is no description of the association of higher HbA1c with the severity of DKA. One hundred thirty-eight electronic medical records of patients aged 1 to 21 years admitted to the pediatric intensive care unit with DKA between 2011 and 2015 were analyzed. We excluded 50 patients because the HbA1c level was not available. Spearman correlation analyzed the data for 88 patients included in the study. The mean HbA1c was 13.3, with female patients having more admissions compared with male patients (58% vs 42%). The age group from 13 to 21 years accounted for 77.3% of the patients. The duration of type 1 diabetes mellitus did not affect the HbA1c level. Likewise, the blood glucose and serum creatinine level did not show a statistical correlation with blood pH levels. Mean HbA1c for mild, moderate, and severe DKA groups were 11.4%, 12.2%, and 14.8%, respectively. Blood pH and HbA1c returned a negative correlation (correlation coefficient, -0.557; P = 0.005). The HbA1c level correlated positively with the 3 groups of DKA (correlation coefficient, 0.595; P = 0.01). A higher A 1c was associated with more severe DKA.

Metabolomics analysis reveals serum biomarkers in patients with diabetic sarcopenia

INTRODUCTION

Diabetic sarcopenia (DS) is characterized by muscle atrophy, slower nerve conduction, reduced maximum tension generated by skeletal muscle contraction, and slower contraction rate. Hence, DS can cause limb movement degeneration, slow movement, reduced balance, reduced metabolic rate, falls, fractures, etc. Moreover, the relevant early biological metabolites and their pathophysiological mechanism have yet to be characterized.

METHOD

The current cross-sectional study employed serum metabolomics analysis to screen potential noninvasive biomarkers in patients with diabetic sarcopenia. A total of 280 diabetic patients were enrolled in the study (n = 39 sarcopenia [DS], n = 241 without sarcopenia [DM]). Ten patients were randomly selected from both groups. Non-targeted metabolomic analysis was performed by ultra-high-performance liquid chromatography-electrospray ionization tandem mass spectrometry.

RESULTS

A total of 632 differential metabolites were identified, including 82 that were significantly differentially abundant (P < 0.05, VIP > 1, FC > 1.2 or FC < 0.8). Compared with the DM group, the contents of pentadecanoic acid, 5'-methylthioadenosine (5'-MTA), N,N-dimethylarginine (asymmetric dimethylarginine, ADMA), and glutamine in the DS group were significantly increased, while that of isoxanthohumol was decreased.

DISCUSSION

Based on receiver operating characteristic curve analysis, pentadecanoic acid, 5'-MTA, ADMA, and glutamine may serve as potential biomarkers of DS. Moreover, ATP-binding cassette (ABC) transporters and the mammalian target of the rapamycin signaling pathway were found to potentially have important regulatory roles in the occurrence and development of DS (P < 0.05). Collectively, the differential metabolites identified in this study provide new insights into the underlying pathophysiology of DS and serve as a basis for therapeutic interventions.

Continuous Glucose Monitoring to Optimize Management of Diabetes in Patients with Advanced CKD

Treatment of patients with diabetes and CKD includes optimizing glycemic control using lifestyle modifications and drugs that safely control glycemia and improve clinical kidney and cardiovascular disease outcomes. However, patients with advanced CKD, defined as eGFR <30 ml/min per 1.73 m2 or kidney disease treated with dialysis, have limitations to the use of some preferred glucose-lowering medications, are often treated with insulin, and experience high rates of severe hypoglycemia. Moreover, hemoglobin A1c accuracy decreases as GFR deteriorates. Hence, there is a need for better glycemic monitoring tools. Continuous glucose monitoring allows for 24-hour glycemic monitoring to understand patterns and the effects of lifestyle and medications. Real-time continuous glucose monitoring can be used to guide the administration of insulin and noninsulin therapies. Continuous glucose monitoring can overcome the limitations of self-monitored capillary glucose testing and hemoglobin A1c and has been shown to prevent hypoglycemic excursions in some populations. More data are needed to understand whether similar benefits can be obtained for patients with diabetes and advanced CKD. This review provides an updated approach to management of glycemia in advanced CKD, focusing on the role of continuous glucose monitoring in this high-risk population.

Adipose and Plasma microRNAs miR-221 and 222 Associate with Obesity, Insulin Resistance, and New Onset Diabetes after Peritoneal Dialysis

BACKGROUND

The correlation between microRNA, obesity, and glycemic intolerance in patients on peritoneal dialysis (PD) is unknown. We aimed to measure the adipose and plasma miR-221 and -222 levels, and to evaluate their association with adiposity, glucose intolerance, and new onset diabetes mellitus (NODM) after the commencement of PD.

METHODS

We prospectively recruited incident adult PD patients. miR-221 and -222 were measured from adipose tissue and plasma obtained during PD catheter insertion. These patients were followed for 24 months, and the outcomes were changes in adiposity, insulin resistance, and NODM after PD.

RESULTS

One hundred and sixty-five patients were recruited. Patients with pre-existing DM had higher adipose miR-221 (1.1 ± 1.2 vs. 0.7 ± 0.9-fold, p = 0.02) and -222 (1.9 ± 2.0 vs. 1.2 ± 1.3-fold, p = 0.01). High adipose miR-221 and -222 levels were associated with a greater increase in waist circumference (miR-221: beta 1.82, 95% CI 0.57-3.07, p = 0.005; miR-222: beta 1.35, 95% CI 0.08-2.63, p = 0.038), Homeostatic Model Assessment for Insulin Resistance (HOMA) index (miR-221: beta 8.16, 95% CI 2.80-13.53, p = 0.003; miR-222: beta 6.59, 95% CI 1.13-12.05, p = 0.018), and insulin requirements (miR-221: beta 0.05, 95% CI 0.006-0.09, p = 0.02; miR-222: beta 0.06, 95% CI 0.02-0.11, p = 0.002) after PD. The plasma miR-222 level predicted the onset of NODM (OR 8.25, 95% CI 1.35-50.5, p = 0.02).

CONCLUSION

miR-221 and -222 are associated with the progression of obesity, insulin resistance, and NODM after PD.

Is hemoglobin A1c valuable for predicting concurrent endometrial cancer in diabetic women with endometrial intraepithelial neoplasia?

AIM

The purpose of this study was to determine the predictive value of preoperative hemoglobin A1c (HgA1c) level for endometrial cancer in diabetic women with endometrial intraepithelial neoplasia (EIN).

MATERIALS AND METHODS

Six hundred patients with EIN were retrospectively studied in a tertiary referral center in Turkey between January 2014 and December 2021. One hundred and thirteen diabetic patients with EIN who met the inclusion criteria were enrolled in the study and divided into three groups according to the final pathological results: Group 1 with benign findings (n = 29), Group 2 with EIN (n = 34) and Group 3 with endometrial cancer (n = 50). Demographic, clinical and biochemical characteristics were compared among the three groups. Receiver operating characteristic analysis (ROC) was used to evaluate the predictive value of HgA1c for concurrent endometrial cancer in EIN.

RESULTS

Mean preoperative HgA1c levels were different among three groups (5.41 ± 0.64, 6.01 ± 0.72, 6.65 ± 1.15, p < 0.001, respectively). The highest value of HgA1c level was found in cancer group and difference within pairs was statistically significant (p < 0.001). Age and duration of menopause were also different among groups (p < 0.005). After adjustment of HgA1c level for age and duration of menopause differences were maintained (p < 0.001), the cutoff value was detected as ≥6.05% for HgA1c and sensitivity, specificity was 60%, 70%, respectively (p < 0.001).

CONCLUSIONS

HgA1c could be used in prediction of endometrial cancer. The optimal cutoff value determined in our study could be considered in predicting endometrial cancer in diabetic women with EIN.

Comparative study of CNR1 and CNR2 cannabinoid receptors expression levels in COVID-19 patients with and without diabetes mellitus: Recommendations for future research targets

BACKGROUND AND AIMS

The COVID-19 pandemic has prompted researchers to look for effective therapeutic targets. The effect of endocannabinoid system against infectious diseases is investigated for several years. In this study, we evaluated the expression level of CNR1 and CNR2 genes in patients with COVID-19 with and without diabetes to provide new insights regarding these receptors and their potential effect in COVID-19 disease.

METHODS

In this study, peripheral blood monocytes cells (PBMCs) were isolated from eight different groups including COVID-19 patients, diabetic patients, and healthy individuals. RNA were extracted to evaluate the expression level of CNR1 and CNR2 genes using real-time PCR. The correlation between the expression levels of these genes in different groups were assessed.

RESULTS

A total of 80 samples were divided into 8 groups, with each group consisting of ten samples. When comparing severe and moderate COVID-19 groups to healthy control group, the expression levels of the CNR1 and CNR2 genes were significantly higher in the severe and moderate COVID-19 groups. There were no significant differences between the mild COVID-19 group and the healthy control group. It was found that the expression levels of these genes in patients with diabetes who were infected with SARS-COV-2 did not differ across COVID-19 groups with varying severity, but they were significantly higher when compared to healthy controls.

CONCLUSION

Our study suggests the possible role of endocannabinoid system during SARS-COV-2 pathogenicity as the expression of CNR1 and CNR2 were elevated during the disease.

HbA1c combined with glycated albumin or 1,5-anhydroglucitol improves the efficiency of diabetes screening in a Chinese population

AIMS

This study aimed to evaluate the ability of HbA_1c combined with glycated albumin (GA) or 1,5-anhydroglucitol (1,5-AG) to detect diabetes in residents of Jiangsu, China.

METHODS

The oral glucose tolerance test (OGTT) was performed on 2184 people in Jiangsu. HbA_1c , GA, 1,5-AG and other serum biochemical parameters were measured. Receiver operating characteristic curves were plotted to determine the optimal thresholds of HbA_1c , GA and 1,5-AG according to the Youden index.

RESULTS

(1) The optimal thresholds of HbA_1c , GA and 1,5-AG for the screening of diabetes were ≥45 mmol/mol (6.3%), ≥13.0% and ≤23.0 μg/ml, respectively. (2) The sensitivities of HbA_1c combined with GA and 1,5-AG were both 85%, higher than that of HbA_1c (70%, p < 0.001).

CONCLUSIONS

This study is suitable for cases where plasma glucose is unavailable. Among the residents of Jiangsu, HbA_1c combined with GA or 1,5-AG can improve the sensitivity of diabetes screening, reduce the miss rate and save the use of OGTT. GA and 1,5-AG are superior in individuals with mild glucose metabolism disorder. GA enhances the detection of diabetes in the nonobese, and 1,5-AG enhances the detection in those with hyperuricaemia.