Risk Factors For Diabetic Complications Research Articles

The relationship between weight-adjusted-waist index and diabetic kidney disease in patients with type 2 diabetes mellitus.

Obesity, particularly abdominal obesity, is seen as a risk factor for diabetic complications. The weight-adjusted-waist index (WWI) is a recently developed index for measuring adiposity. Our goal was to uncover the potential correlation between the WWI index and diabetic kidney disease (DKD) risk. This cross-sectional study included adults with type 2 diabetes mellitus (T2DM) who participated in the NHANES database (2007-2018). The WWI index was calculated as waist circumference (WC, cm) divided by the square root of weight (kg). DKD was diagnosed based on impaired estimated glomerular filtration rate (eGFR<60 mL/min/1.73m2), albuminuria (urinary albumin to urinary creatinine ratio>30 mg/g), or both in T2DM patients. The independent relationship between WWI index and DKD risk was evaluated. A total of 5,028 participants with T2DM were included, with an average WWI index of 11.61 ± 0.02. As the quartile range of the WWI index increased, the prevalence of DKD gradually increased (26.76% vs. 32.63% vs. 39.06% vs. 42.96%, P<0.001). After adjusting for various confounding factors, the WWI index was independently associated with DKD risk (OR=1.32, 95%CI:1.12-1.56, P<0.001). The area under the ROC curve (AUC) of the WWI index was higher than that of body mass index (BMI, kg/m2) and WC. Subgroup analysis suggested that the relationship between the WWI index and DKD risk was of greater concern in patients over 60 years old and those with cardiovascular disease. Our findings suggest that higher WWI levels are linked to DKD in T2DM patients. The WWI index could be a cost-effective and simple way to detect DKD, but further prospective studies are needed to confirm this.

Macronutrient Intake and Association with the Risk Factors of Diabetic Complications among People with Type 2 Diabetes Mellitus in Al-Madinah Al-Munawara

BACKGROUND: Worldwide, Type 2 diabetes mellitus (T2DM) is a leading cause of morbidity and mortality. There is little research on the relationship between T2DM problems and daily macronutrient intake in Saudi Arabia, particularly in Al-Madina Al-Munawara. AIM: This study aimed to investigate the relationship between T2DM complications and daily carbohydrate, protein, and fat intake in T2DM patients. MATERIALS AND METHODS: A cross-sectional study was conducted on 138 T2DM patients in Al-Madina Al-Munawara City, Saudi Arabia. The data were collected using a questionnaire that was published on social media. The macronutrient data were collected by a 24-h dietary recall questionnaire on 2 non-consecutive days. Appropriate statistical tests were done, and univariate and multivariate logistic regression were used to examine the association of macronutrient intake with diabetes complications among the studied patients. RESULTS: The mean age of patients was 53.8 ± 11.3 years, and 55.8% were females. The prevalence of T2DM complications was 55.8% for diabetic retinopathy, 30.4% for cardiovascular diseases (CVD), 26.1% for diabetic foot, 19.6% for stroke, and 5.3% for kidney diseases with no significant difference by patients’ sex. Daily carbohydrates intake &gt;65% was associated with an increased risk of CVD, retinopathy, and diabetic foot with odds ratio (OR) of 4.75, 4.35, and 65.5, respectively. Daily proteins intake &gt;20% and daily fat intake ≥30% were associated with a significant increased risk of stroke and CVD, respectively. CONCLUSION: The study findings suggest that high daily calorie intake from carbohydrate protein and fat plays an important role in the risk of T2DM complications. Patients with diabetes who understand the value of consuming calories from macronutrients and how to distribute their daily intake of these calories may reduce their risk of developing diabetic complications.

Related Factors Mining of Diabetes Complications Based on Manifold-Constrained Multi-Label Feature Selection.

The primary cause of mortality among individuals with diabetes stems from complications. Identifying related factors for these complications holds immense potential for early prevention. Previous research predominantly employed traditional machine-learning techniques to establish prediction models utilizing medical indicators for related factor selection. However, uncovering the intricate correlations among complication labels and identifying similar characteristics among medical indicators has been challenging. We propose a novel embedded multi-label feature selection approach called LCFSM(Label Cosine and Feature Similar Manifold) to address the issue. LCFSM introduces manifold constraints into the objective function to uncover risk factors associated with diabetes complications. Label cosine similarity is set to optimize feature weights, forming label manifold constraints. Similarly, feature manifold constraints are established to utilize feature kernel similarity in optimizing feature weights. LCFSM formulates an objective function based on the l2,1 regularized Least Squares and previous manifolds constraints, employing the Sylvester equationfor convergence assurance. The experimental evaluation compares LCFSM against eight baselines, demonstrating superior performance in top-10 feature selection and feature stacking.LCFSM is applied to identify primary risk factors for diabetes complications. Related factors involve Electromyogram, Urine Routine Protein Positive, etc, offering valuable insights for early treatment.

Evaluation of association between time in range, a continuous glucose monitoring metric, and cardiac autonomic neuropathy in type 2 diabetes patients.

Time in range (TIR), a metric of continuous glucose monitoring (CGM) provides better information regarding the individual's glycemic variability than a static measure like glycated hemoglobin (HbA1c). TIR is emerging as an independent risk factor for diabetic complications, both microvascular and macrovascular complications independent of HbA1c. Hence, this study evaluates the association between TIR and cardiac autonomic neuropathy (CAN) in type 2 diabetic patients. A total of 42 patients with type 2 diabetes mellitus were enrolled in this study and underwent a 3-day CGM using the "FreeStyle Libre Pro Flash Glucose Monitoring System Sensor" along with tests for CAN within the 3 days of attaching the CGM. Out of 42 patients, 36 patients (85.7%) were diagnosed with CAN (early CAN 57.1% and definite CAN 28.6%) and the mean TIR was 64.4% ±23.5%. Out of those with TIR <70%, 42.9% were affected with definite CAN compared to only 14.3% among those with TIR >70%. Patients with more severe CAN were found to have a lower TIR (P = 0.115). The study found a high prevalence of cardiac autonomic neuropathy (CAN) of around 85.7% in type 2 diabetes patients. Lower TIR values were associated with a higher incidence of definite CAN (42.9% vs. 14.3% in TIR <70% vs. >70% groups). The findings suggest TIR is inversely associated with the presence and severity of cardiac autonomic neuropathy in type 2 diabetic patients and also a potential link between TIR and CAN severity.

Glucose fluctuation promotes mitochondrial dysfunctions in the cardiomyocyte cell line HL-1.

Glycemic variability has been suggested as a risk factor for diabetes complications but the precise deleterious mechanisms remain poorly understood. Since mitochondria are the main source of energy in heart and cardiovascular diseases remain the first cause of death in patients with diabetes, the aim of the study was to evaluate the impact of glucose swings on mitochondrial functions in the cardiomyocyte cell line HL-1. HL-1 cells were exposed to low (LG, 2.8 mmol/l), normal (NG, 5.5 mmol/l), high (HG, 25 mmol/l) or intermittent high glucose (IHG, swing between low and high) every 2h during 12h (short-time treatment) or every 12h during 72h (long-time treatment). Anaerobic catabolism of glucose was evaluated by measuring glucose consumption and lactate production, oxidative phosphorylation was evaluated by polarography and ATP measurement, mitochondrial superoxide anions and the mitochondrial membrane potential (MMP) were analysed using fluorescent probes, and the protein oxidation was measured by oxyblot. IHG and HG increased glucose consumption and lactate production compared to LG and NG but without any difference between short- and long-time treatments. After 72h and unlike to LG, NG and HG, we didn't observe any increase of the mitochondrial respiration in the presence of succinate upon IHG treatment. IHG, and to a lesser extent HG, promoted a time-dependent decrease of the mitochondrial membrane potential compared to LG and NG treatments. HG and IHG also increased superoxide anion production compared to LG and NG both at 12 and 72h but with a higher increase for IHG at 72h. At last, both HG and IHG stimulated protein oxidation at 72h compared to LG and NG treatments. Our results demonstrated that exposure of HL-1 cells to glucose swings promoted time-dependent mitochondrial dysfunctions suggesting a deleterious effect of such condition in patients with diabetes that could contribute to diabetic cardiomyopathy.

IGF1 and PPARG polymorphisms are associated with reduced estimated glomerular filtration rate in a cohort of children and adolescents with type 1 diabetes.

Several genetic loci have been associated with diabetic nephropathy; however, the underlying genetic mechanisms are still poorly understood, with no robust candidate genes identified yet. We aimed to determine whether two polymorphisms, previously associated with renal decline, influence kidney impairment evaluating their association with markers of renal function in a pediatric population with type 1 diabetes (T1D). Renal function was evaluated by glomerular filtration rate (eGFR) and albumin-to-creatinine ratio (ACR) in a cohort of pediatric subjects with T1D (n = 278). Risk factors for diabetes complications (diabetes duration, blood pressure, HbA1c) were assessed. The IGF1 rs35767 and PPARG rs1801282 SNPs were genotyped by TaqMan RT-PCR system. An additive genetic interaction was calculated. Association analysis between markers of renal function and both SNPs or their additive interaction were performed. Both SNPs showed a significant association with eGFR: the A allele of rs35767 or the C allele of rs1801282 were associated to reduced eGFR compared to G alleles. Multivariate regression analysis adjusted for age, sex, z-BMI, T1D duration, blood pressure and Hba1c values showed that the additive genetic interaction was independently associated with lower eGFR (β = -3.59 [-6.52 to -0.66], p = 0.017). No associations were detected between SNPs, their additive interaction and ACR. These results provide new insight into the genetic predisposition to renal dysfunction, showing that two polymorphisms in IGF1 and PPARG genes can lead to a reduction in renal filtration rate leading these patients to be exposed to a higher risk of early renal complications.

Cardiovascular complications in insulin resistance and endocrine diseases.

Cerebrovascular diseases, such as stroke and cardiovascular disease, are one of the leading causes of death in Japan. Type 2 diabetes is the most common form of diabetes and an important risk factor for these diseases. Among various pathological conditions associated with type 2 diabetes, insulin resistance has already been reported to be an important risk factor for diabetic complications. The major sites of insulin action in glucose metabolism in the body include the liver, skeletal muscle, and adipose tissue. However, insulin signaling molecules are also constitutively expressed in vascular endothelial cells, vascular smooth muscle, and monocytes/macrophages. Forkhead box class O family member proteins (FoxOs) of transcription factors play important roles in regulating glucose and lipid metabolism, oxidative stress response and redox signaling, and cell cycle progression and apoptosis. FoxOs in vascular endothelial cells strongly promote arteriosclerosis by suppressing nitric oxide production, enhancing inflammatory response, and promoting cellular senescence. In addition, primary aldosteronism and Cushing's syndrome are known to have adverse effects on the cardiovascular system, apart from hypertension, diabetes, and dyslipidemia. In the treatment of endocrine disorders, hormonal normalization by surgical treatment and receptor antagonists play an important role in preventing cardiovascular complications.

Glucose and HbA1c variability and time in range (TIR)

Glycated hemoglobin (HbA1c) is the pillar of diabetes management, but does not capture blood glucose fluctuations over time. Recent data suggest that additional glucose-related metrics might improve prevention of the increased cardiovascular risk in diabetes. Variabilities in both blood glucose and HbA1cappear to represent additional, independent risk factors for diabetes complications. Continuous glucose monitoring also allows calculation of a new, intuitive metric, i.e., time in range (TIR), which is strictly related to glucose variability and is also an independent risk factor for diabetes complications. Here, we review the main findings on the influence of TIR, glucose, and HbA1cvariability on the development of complications and highlight the possible role of novel drugs in improving glucose variability.

Glukose- und HbA1c-Variabilität sowie Zeit im Zielbereich (TIR)

Glycated hemoglobin (HbA1c) is the pillar of diabetes management, but does not capture blood glucose fluctuations over time. Recent data suggest that additional glucose-related metrics might improve prevention of the increased cardiovascular risk in diabetes. Variabilities in both blood glucose and HbA1c appear to represent additional, independent risk factors for diabetes complications. Continuous glucose monitoring also allows calculation of a new, intuitive metric, i.e., time in range (TIR), which is strictly related to glucose variability and is also an independent risk factor for diabetes complications. Here, we review the main findings on the influence of TIR, glucose, and HbA1c variability on the development of complications and highlight the possible role of novel drugs in improving glucose variability.

Role of insulin action in the pathogenesis of diabetic complications.

Among the various pathological conditions associated with type 2 diabetes, insulin resistance has long been reported to be a potent risk factor for diabetic complications. The liver, skeletal muscle, and adipose tissue are the major organs of action of insulin in systemic glucose metabolism, but insulin receptors and their downstream insulin signaling molecules are also constitutively expressed in vascular endothelial cells, vascular smooth muscle, and monocytes/macrophages. Forkhead box class O family member proteins (FoxOs) of transcription factors are essential regulators of cellular homeostasis, including glucose and lipid metabolism, oxidative stress response and redox signaling, cell cycle progression and apoptosis. In vascular endothelial cells, FoxOs strongly promote atherosclerosis via suppressing nitric oxide production and enhancing inflammatory responses. In liver sinusoidal endothelial cells, FoxOs induces hepatic insulin resistance by inducing nitration of insulin receptor in hepatocytes. Insulin resistance in adipose tissue limits capacity of lipid accumulation in adipose tissue, which promotes ectopic lipid accumulation and organ dysfunction in liver, vascular, and kidney. Modulation of insulin sensitivity in adipose tissue to induce healthy adipose expansion is expected to be a promising strategy for diabetic complications.

Early marker of ocular neurodegeneration in children and adolescents with type 1 diabetes: the contributing role of polymorphisms in mir146a and mir128a genes

BackgroundEarly ocular neurodegenerative signs of diabetic neuropathy (DN) can be found in children and adolescents with type 1 diabetes (T1D). No data are available on the potential role of polymorphisms in miRNAs genes in predisposing T1D subjects to these signs.AimsTo determine whether MIR146A rs2910164 and MIR128A rs11888095 polymorphisms are associated with early retinal and corneal neurodegenerative changes in pediatric patients with T1D.MethodsA total of 140 T1D children/adolescents underwent spectral domain-optical coherence tomography (SD-OCT) and in vivo confocal microscopy (IVCM) with measurement of retinal and corneal nerve fiber parameters. Risk factors for diabetes complications (diabetes duration, blood pressure, HbA1c) were recorded. Genotyping of rs2910164 and rs1188095 SNPs and genotype–phenotype association analysis were performed.ResultsThe C allele of rs2910164 in MIR146A was associated with higher values of IVCM parameters and minimum rim width (MRW) of the peripapillary region of optic nerve head measured in the retina, whereas the T allele of rs1188095 in MIR128A was associated with a significant impairment of them. Multiple regression analysis showed that MIR146A and MIR128A polymorphisms were significantly associated with corneal nerve fiber length (beta = 0.225 and − 0.204, respectively) and other IVCM parameters, independently from age, diabetes duration, HbA1c and systolic blood pressure percentile. Similar results were found for MRW (beta = 0.213 and − 0.286, respectively).ConclusionsThese results provide new insight into the genetic predisposition to DN showing that two polymorphisms in MIR146A and MIR128A genes could significantly contribute to the development of early ocular preclinical signs of DN.

Association of hypoxia inducible factor 1-Alpha gene polymorphisms with multiple disease risks: A comprehensive meta-analysis.

HIF1A gene polymorphisms have been confirmed the association with cancer risk through the statistical meta-analysis based on single genetic association (SGA) studies. A good number SGA studies also investigated the association of HIF1A gene with several other diseases, but no researcher yet performed statistical meta-analysis to confirm this association more accurately. Therefore, in this paper, we performed a statistical meta-analysis to draw a consensus decision about the association of HIF1A gene polymorphisms with several diseases except cancers giving the weight on large sample size. This meta-analysis was performed based on 41 SGA study’s findings, where the polymorphisms rs11549465 (1772 C/T) and rs11549467 (1790 G/A) of HIF1A gene were analyzed based on 11544 and 7426 cases and 11494 and 7063 control samples, respectively. Our results showed that the 1772 C/T polymorphism is not significantly associated with overall disease risks. The 1790 G/A polymorphism was significantly associated with overall diseases under recessive model (AA vs. AG + GG), which indicates that the A allele is responsible for overall diseases though it is recessive. The subgroup analysis based on ethnicity showed the significant association of 1772 C/T polymorphism with overall disease for Caucasian population under the all genetic models, which indicates that the C allele controls overall diseases. The ethnicity subgroup showed the significant association of 1790 G/A polymorphism with overall disease for Asian population under the recessive model (AA vs. AG + GG), which indicates that the A allele is responsible for overall diseases. The subgroup analysis based on disease types showed that 1772 C/T is significantly associated with chronic obstructive pulmonary disease (COPD) under two genetic models (C vs. T and CC vs. CT + TT), skin disease under two genetic models (CC vs. TT and CC + CT vs. TT), and diabetic complications under three genetic models (C vs. T, CT vs. TT and CC + CT vs. TT), where C allele is high risk factor for skin disease and diabetic complications (since, ORs > 1), but low risk factor for COPD (since, ORs < 1). Also the 1790 G/A variant significantly associated with the subgroup of cardiovascular disease (CVD) under homozygote model, diabetic complications under allelic and homozygote models, and other disease under four genetic models, where the A is high risk factor for diabetic complications and low risk factor for CVD. Thus, this study provided more evidence that the HIF1A gene is significantly associated with COPD, CVD, skin disease and diabetic complications. These might be the severe comorbidities and risk factors for multiple cancers due to the effect of HIF1A gene and need further investigations accumulating large number of studies.

The WISDOM self-management intervention: A cost-effectiveness analysis to support the transformation of type 2 diabetes care in England.

ObjectivesTo assess the cost‐effectiveness of the WISDOM self‐management intervention for type 2 diabetes compared with care as usual.DesignWe performed a difference‐in‐differences analysis to estimate differences in risk factors for diabetes complications between people in the WISDOM group (n = 25, 276) and a control group (n = 15, 272) using GP records. A decision analytic model was then used to extrapolate differences in risk factors into costs and outcomes in the long term.SettingParticipating GP practices in West Hampshire and Southampton, UK.ParticipantsAll people diagnosed with type 2 diabetes between January 1990 and March 2020 (n = 40,548).OutcomesDiabetes‐related complications, quality‐adjusted life years (QALYs) and costs to the English National Health Service at 5 years and lifetime.InterventionsThe WISDOM intervention included risk stratification, self‐management education programme to professionals and people with type 2 diabetes, and monitoring of key treatment targets.ResultsWISDOM was associated with less atrial fibrillation [p = 0.001], albuminuria [p = 0.002] and blood pressure [p = 0.098]. Among all people in the intervention group, WISDOM led to 51 [95%CI: 25; 76] QALYs gained and saved £278,036 [95%CI: −631,900; 176,392] in the first 5 years after its implementation compared with care as usual. During those people' lifetime, WISDOM led to 253 [95%CI: 75; 404] QALYs gained and cost saving of £126,380 [95%CI: −1,466,008; 1,339,628]. The gains in QALYs were a result of reduced diabetes‐related complications through improved management of the associated risk factors.ConclusionsThe WISDOM risk‐stratification and education intervention for type 2 diabetes appear to be cost‐effective compared to usual care by reducing diabetes complications.

Vitamin D Supplementation Modulates Platelet-Mediated Inflammation in Subjects With Type 2 Diabetes: A Randomized, Double-Blind, Placebo-Controlled Trial.

BackgroundRecently, our group identified increased platelet-mediated inflammation in type 2 diabetes (T2DM) patients, and it is a well-established risk factor for diabetes complications, particularly for the development of cardiovascular diseases (CVD). Furthermore, vitamin D is reported to play an important role in the modulation of platelet hyperactivity and immune function, although the effect of vitamin D on platelet-mediated inflammation is not well studied. Hence, we aimed to investigate the effect of vitamin D supplementation on platelet-mediated inflammation in T2DM patients.MethodsAfter screening a total of 201 subjects, our randomized, double-blind, placebo-controlled trial included 59 vitamin-D-deficient T2DM subjects, and the participants were randomly assigned to placebo (n = 29) or vitamin D3 (n = 30) for 6 months. Serum vitamin D metabolite levels, immunome profiling, platelet activation, and platelet–immune cell aggregate formation were measured at baseline and at the end of the study. Similarly, the serum levels of inflammatory cytokines/chemokines were assessed by a multiplex assay.ResultsSix months of vitamin D supplementation increases the serum vitamin D3 and total 25(OH)D levels from the baseline (p < 0.05). Vitamin D supplementation does not improve glycemic control, and no significant difference was observed in immune cells. However, platelet activation and platelet immune cell aggregates were altered after the vitamin D intervention (p < 0.05). Moreover, vitamin D reduces the serum levels of IL-18, TNF-α, IFN-γ, CXCL-10, CXCL-12, CCL-2, CCL-5, CCL-11, and PF-4 levels compared to the baseline levels (p < 0.05). Our ex vivo experiment confirms that a sufficient circulating level of vitamin D reduces platelet activation and platelet intracellular reactive oxygen species.ConclusionOur study results provide evidence that vitamin D supportive therapy may help to reduce or prevent the disease progression and cardiovascular risk in T2DM patients by suppressing oxidative stress and platelet-mediated inflammation.Clinical Trial RegistrationClinical Trial Registry of India: CTRI/2019/01/016921.

Prevalence and Risk Factors for Diabetic Complications: 8-Year Retrospective Report from a Single Regional Diabetes Center to the Eastern Region of Morocco

Objective: This study aims to investigate the risk factors of diabetes and its complications in the eastern region. Design: This is a retrospective study conducted on diabetic patients followed at the regional center of diabetology and chronic diseases in Oujda for the period 2012-2019. Materials and Methods:Clinical, biological, therapeutic and anthropometric data were collected from patient records. Result: A total of 3.976 patients participated in the study. The frequency of complications is around 1/3. One diabetic out of four has at least one modifiable cardiovascular risk factor: arterial hypertension at 25.35%, dyslipidemia at 12.67%, overweight and obesity at 35.48% and 27.8%. The most discriminating factors in the pathogenesis of diabetic complications in order of importance are age of diabetes, hypertension, HbA1c and dyslipidemia, statistically significant associations were found with p 0.0082, 0.0001, 0.002, 0.0001 respectively). Then a multifactorial analysis coupled with a hierarchical ascending classification in birth data to two large groups of diabetics with complications and those without complications. Discussion: The age of trend T2DM has fallen to less than 40 years, so that the first characteristics of an epidemiological and nutritional transition are being established in our region. In addition, blood pressure and glycemic imbalance in diabetics reflect a problem of medical and therapeutic management that needs to be resolved. Conclusion: The pathogenesis of diabetic complications is multifactorial. However, medical care must be taken to reduce the risk of degenerative complications.

Association Among Lipid Accumulation Product, Chinese Visceral Obesity Index and Diabetic Retinopathy in Patients with Type 2 Diabetes: A Cross-Sectional Study

Background and AimObesity often coexists with diabetes, especially abdominal obesity, recognized as a risk factor for diabetic complications. Diabetic retinopathy (DR), as one of the most common microvascular complications of diabetes, may be associated with these indices. Lipid accumulation product (LAP) and Chinese visceral obesity index (CVAI) are novel visceral obesity indicators, which have been proven to be an influential factor predicting type 2 diabetes (T2DM). However, the correlation among LAP, CVAI, and DR still lacks systematic research in T2DM. The study aimed to explore the relationship among LAP, CVAI levels in different DR stages of T2DM patients and the diagnostic efficacy of LAP and CVAI for DR.MethodsA total of 263 participants were recruited in this cross-sectional study. We enrolled 169 patients with T2DM, divided into the non-DR group (NDR, n = 61), non-proliferative DR group (NPDR, n = 55), and proliferative DR group (PDR, n = 53). And we also enrolled 94 healthy control participants. We collected demographic, anthropometric, and biochemical data on each subject. LAP and CVAI are calculated according to different formulas for men and women.ResultsCompared with the control group, LAP and CVAI were significantly higher (P < 0.05). After adjusting for confounding factors, LAP (OR: 1.029, 95CI%: 1.010–1.049, P < 0.05), WC (OR: 1.073, 95CI%: 1.009–1.141, P < 0.05) and CVAI (OR: 1.017, 95CI%: 1.000–1.033, P < 0.05) were all associated with an increased risk of DR. Furthermore, increased LAP (OR: 1.020, 95% CI: 0.100–0.290) is associated with DR severity (P < 0.001). Moreover, the LAP had the most significant area under the receiver operating characteristics (ROC) curve (AUC) (AUC = 0.728, 95% CI: 0.653–0.804).ConclusionA high LAP is associated with an increased risk of DR in T2DM patients, and the LAP index appears to be a good predictor of DR risk and severity in patients with T2DM, compared with BMI, WC, and CVAI.

HbA1C variability among type 2 diabetic patients: a retrospective cohort study

BackgroundStudies have found that HbA1C variability is an independent risk factor for diabetic complications in type 2 diabetic patients. This study aims to find factors contributing to higher HbA1C variability in the community.MethodsThe study was conducted in the southern district of Israel, in Clalit Health Services (CHS). The study population was type 2 diabetic individuals aged 40–70 years in 2005, with a follow-up period of 11 years, until 2015. The definition of HbA1C variability was done by the standard deviation from the average HbA1C value of the entire study period, which was calculated for each participant. The study population was divided into two groups, “variability group” with HbA1C SD > 1.2, and “comparison group” of participants with HbA1C SD ≤ 1.2. In the univariate analysis we used X2 or Fisher test for categorical variables and independent t-test for numeric continuous variables. In the multivariate analysis we used logistic regression as well as assessing for possible interactions. Statistical analysis was ascribed for p < 0.05. All the data was drawn from the computerized medical system used by all primary care physicians and nurses in CHS working in the community.ResultsThe study population included 2866 participants, the average age was 58.6 years, 43.3% men and 56.7% women. Each participant had an average of 20.9 HbA1C measures in their computerized medical record during the 11 years of follow up. The mean HbA1C value was 7.8%. We found 632 patients (22%) with a high variability, whereas 2234 (78%) had a low variability of HbA1C. In the “variability group” there was a higher percentage of smokers, BMI ≥ 30 and a higher rate of visits to diabetic clinics compared to the “no variability” group. In the “variability group” we found a much higher use of insulin and ACE inhibitors. The highest frequency of variability was between HbA1c values of 8.1–8.5. The multivariate analysis showed that HbA1C variability was associated with insulin use (OR = 4.1, p < 0.001), with age (OR = 0.939, p < 0.001), and Ischemic heart disease (OR = 1.258, p = 0.03). BMI ≥ 30 was almost statistically significant (OR = 1.206, p = 0.063). Gender was statistically insignificant.ConclusionsIn conclusion, HbA1C variability might be used as an additional marker in Diabetes Mellitus type 2, reflecting the disease complexity characteristics and the patient’s lifestyle profile.

Comparison of glycation degrees of HbG-Coushatta and HbG-Taipei with HbA using liquid chromatography with tandem mass spectrometry

BackgroundHemoglobin A1c(HbA1c) is widely used to measure glycemic status and control in diabetes testing and treatment and is an important risk factor forcomplications of diabetes. Hemoglobin variants can interfere with the HbA1c testing method by reducing the life span of erythrocytes or due to differences in glycation degrees. In this study, glycation levels of the HbA, HbG-Coushatta, and HbG-Taipei β-chains (βA, βG-Coushatta, and βG-Taipei, respectively) were examined. MethodsBlood samples from heterozygotic patients (HbG-Coushatta/HbA, HbG-Taipei/HbA) were analyzed. Glycation rateswere determined using high-performance liquid chromatography with tandem mass spectrometry. Ratios of glycated βG-Coushatta to glycated βA and glycated βG-Taipei to glycated βA were calculated by comparingareas under the curves from extracted ion chromatograms. ResultsβG-Coushatta and βG-Taipei were 6.08 ± 1.38% and 5.95 ± 0.93% glycated (respectively), which were significantly higher than βA chains(4.55 ± 1.30% and 4.51 ± 0.91%, respectively; p = 0.000). The total glycation degree (α + β) in HbG-Coushatta and HbG-Taipei heterozygotes were estimated to be 9% and 8% higher than those of HbA homozygotes (P＜0.001), respectively. ConclusionβG-Coushatta and βG-Taipei glycation degrees were significantly higher than βA, while the differences in total hemoglobin (α + β) were small and unlikely to impact the clinical interpretation of HbA1c results.

Machine Learning Approaches to Predict Risks of Diabetic Complications and Poor Glycemic Control in Nonadherent Type 2 Diabetes.

Purpose: The objective of this study was to evaluate the efficacy of machine learning algorithms in predicting risks of complications and poor glycemic control in nonadherent type 2 diabetes (T2D). Materials and Methods: This study was a real-world study of the complications and blood glucose prognosis of nonadherent T2D patients. Data of inpatients in Sichuan Provincial People’s Hospital from January 2010 to December 2015 were collected. The T2D patients who had neither been monitored for glycosylated hemoglobin A nor had changed their hyperglycemia treatment regimens within the last 12 months were the object of this study. Seven types of machine learning algorithms were used to develop 18 prediction models. The predictive performance was mainly assessed using the area under the curve of the testing set. Results: Of 800 T2D patients, 165 (20.6%) met the inclusion criteria, of which 129 (78.2%) had poor glycemic control (defined as glycosylated hemoglobin A ≥7%). The highest area under the curves of the testing set for diabetic nephropathy, diabetic peripheral neuropathy, diabetic angiopathy, diabetic eye disease, and glycosylated hemoglobin A were 0.902 ± 0.040, 0.859 ± 0.050, 0.889 ± 0.059, 0.832 ± 0.086, and 0.825 ± 0.092, respectively. Conclusion: Both univariate analysis and machine learning methods reached the same conclusion. The duration of T2D and the duration of unadjusted hypoglycemic treatment were the key risk factors of diabetic complications, and the number of hypoglycemic drugs was the key risk factor of glycemic control of nonadherent T2D. This was the first study to use machine learning algorithms to explore the potential adverse outcomes of nonadherent T2D. The performances of the final prediction models we developed were acceptable; our prediction performances outperformed most other previous studies in most evaluation measures. Those models have potential clinical applicability in improving T2D care.

Increased Hemoglobin A1c Time in Range Reduces Adverse Health Outcomes in Older Adults With Diabetes.

Short- and long-term glycemic variability are risk factors for diabetes complications. However, there are no validated A1C target ranges or measures of A1C stability in older adults. We evaluated the association of a patient-specific A1C variability measure, A1C time in range (A1C TIR), on major adverse outcomes. We conducted a retrospective observational study using administrative data from the Department of Veterans Affairs and Medicare from 2004 to 2016. Patients were ≥65 years old, had diabetes, and had at least four A1C tests during a 3-year baseline period. A1C TIR was the percentage of days during the baseline in which A1C was in an individualized target range (6.0-7.0% up to 8.0-9.0%) on the basis of clinical characteristics and predicted life expectancy. Increasing A1C TIR was divided into categories of 20% increments and linked to mortality and cardiovascular disease (CVD) (i.e., myocardial infarction, stroke). The study included 402,043 veterans (mean [SD] age 76.9 [5.7] years, 98.8% male). During an average of 5.5 years of follow-up, A1C TIR had a graded relationship with mortality and CVD. Cox proportional hazards models showed that lower A1C TIR was associated with increased mortality (A1C TIR 0 to <20%: hazard ratio [HR] 1.22 [95% CI 1.20-1.25]) and CVD (A1C TIR 0 to <20%: HR 1.14 [95% CI 1.11-1.19]) compared with A1C TIR 80-100%. Competing risk models and shorter follow-up (e.g., 24 months) showed similar results. In older adults with diabetes, maintaining A1C levels within individualized target ranges is associated with lower risk of mortality and CVD.