The association between renal function and neurological diseases in type 2 diabetes: a multicenter nationwide cross-sectional study

Diabetic peripheral neuropathy is associated with diabetic kidney disease and cardiovascular disease – The Silesia Diabetes-Heart Project

Microvascular complications of diabetes seem to be clustered and put patients at higher risk of developing cardiovascular disease (CVD). This was a questionnaire-based study designed to screen for the presence of diabetic peripheral neuropathy (DPN), defined as the score in the Michigan Neuropathy Screening Instrument (MNSI) above 2, and to evaluate its association with other complication of diabetes, including CVD. There were 184 patients included into the study. The prevalence of DPN in the study group was 37.5%. The regression model analysis revealed that the presence of DPN was significantly associated with the presence of diabetic kidney disease (DKD) (P = 0.0034;) and patient's age (P < 0.0001). Thirty-four patients (49.3%) with MNSI score >2 were diagnosed with CVD in comparison to 24 (20.1%) subjects with MNSI score ≤ 2 (P = 0.00006). In case of having one diabetes complication diagnosed, it is important to screen for others, including macrovascular ones.

Association Between Early Markers of Renal Injury and Type 2 Diabetic Peripheral Neuropathy

OBJECTIVE

Diabetic kidney disease (DKD) and diabetic peripheral neuropathy (DPN) are both common chronic complications of type 2 diabetes mellitus (T2DM). The aim of this study was to examine whether some markers of early renal injury were associated with DPN.

METHODS

Retrospective hospitalization data from 471 patients with T2DM were analyzed. Subjects were divided into DPN group and non-DPN group according to clinical history, symptoms, signs and nerve conduction study. Markers of glomerular injury [urinary albumin/creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR)] and tubular injury [urinary N-acetyl-β-D-glucosaminidase/creatinine ratio (NAG/Cr) and urinary β2 microglobulin (β2-MG)] were innovatively combined to assess the association with DPN. Staging of chronic kidney disease (CKD) was classified as G1, G2, G3a, G3b, G4 based on eGFR categories of ≥90, 60-89, 45-59, 30-44, 15-29 mL/min/1.73m2.

RESULTS

DPN was detected in 71.1% of our population. Subjects in DPN group suffered from older age, longer duration of diabetes and worse blood glucose control compared with non-DPN group. The levels of UACR, NAG/Cr and β2-MG were significantly increased in DPN group than those in non-DPN group, while eGFR was decreased. The prevalence of DPN increased gradually in G1, G2 and G3-4 of CKD, which were 66.3%, 73.2% and 82.7% (P = 0.014). After adjusting for confounding factors, NAG/Cr >1.41 U/mmol (the highest tertile) was a consistently independent risk factor for DPN [odds ratio, OR (95% confidence interval, CI) = 1.86 (1.04-3.33)]. However, UACR, eGFR and β2-MG did not significantly affect the risk of DPN.

CONCLUSION

When T2DM patients suffer from CKD, DPN will be more likely to appear, accelerate or deteriorate. Some easily available urinary markers of glomerular and tubular damage can be used for early prediction of DPN, in which increased NAG/Cr is an independent risk factor for DPN.

Association of Combined TCF7L2 and KCNQ1 Gene Polymorphisms with Diabetic Micro- and Macrovascular Complications in Type 2 Diabetes Mellitus

BACKGROUND

Vascular complications are the major morbid consequences of type 2 diabetes mellitus (T2DM). The transcription factor 7-like 2 (TCF7L2), potassium voltage-gated channel subfamily Q member 1 (KCNQ1), and inwardly-rectifying potassium channel, subfamily J, member 11 gene (KCNJ11) are common T2DM susceptibility genes in various populations. However, the associations between polymorphisms in these genes and diabetic complications are controversial. This study aimed to investigate the effects of combined gene-polymorphisms within TCF7L2, KCNQ1, and KCNJ11 on vascular complications in Thai subjects with T2DM.

METHODS

We conducted a case-control study comprising 960 T2DM patients and 740 non-diabetes controls. Single nucleotide polymorphisms in TCF7L2, KCNQ1, and KCNJ11 were genotyped and evaluated for their association with diabetic vascular complications.

RESULTS

The gene variants TCF7L2 rs290487-T, KCNQ1 rs2237892-C, and KCNQ1 rs2237897-C were associated with increased risk of T2DM. TCF7L2 rs7903146-C, TCF7L2 rs290487-C, KCNQ1 rs2237892-T, and KCNQ1 rs2237897-T revealed an association with hypertension. The specific combination of risk-alleles that have effects on T2DM and hypertension, TCF7L2 rs7903146-C, KCNQ1 rs2237892-C, and KCNQ1 rs2237897-T, as genetic risk score (GRS), pronounced significant association with coronary artery disease (CAD), cumulative nephropathy and CAD, and cumulative microvascular and macrovascular complications (respective odds ratios [ORs] with 95% confidence interval [95% CI], comparing between GRS 2-3 and GRS 5-6, were 7.31 [2.03 to 26.35], 3.92 [1.75 to 8.76], and 2.33 [1.13 to 4.79]).

CONCLUSION

This study demonstrated, for the first time, the effect conferred by specific combined genetic variants in TCF7L2 and KCNQ1 on diabetic vascular complications, predominantly with nephropathy and CAD. Such a specific pattern of gene variant combination may implicate in the progression of T2DM and life-threatening vascular complications.

Association Between Early Markers of Renal Injury and Type 2 Diabetic Peripheral Neuropathy

OBJECTIVE

Diabetic kidney disease (DKD) and diabetic peripheral neuropathy (DPN) are both common chronic complications of type 2 diabetes mellitus (T2DM). The aim of this study was to examine whether some markers of early renal injury were associated with DPN.

METHODS

Retrospective hospitalization data from 471 patients with T2DM were analyzed. Subjects were divided into DPN group and non-DPN group according to clinical history, symptoms, signs and nerve conduction study. Markers of glomerular injury [urinary albumin/creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR)] and tubular injury [urinary N-acetyl-β-D-glucosaminidase/creatinine ratio (NAG/Cr) and urinary β2 microglobulin (β2-MG)] were innovatively combined to assess the association with DPN. Staging of chronic kidney disease (CKD) was classified as G1, G2, G3a, G3b, G4 based on eGFR categories of ≥90, 60-89, 45-59, 30-44, 15-29 mL/min/1.73m².

RESULTS

DPN was detected in 71.1% of our population. Subjects in DPN group suffered from older age, longer duration of diabetes and worse blood glucose control compared with non-DPN group. The levels of UACR, NAG/Cr and β2-MG were significantly increased in DPN group than those in non-DPN group, while eGFR was decreased. The prevalence of DPN increased gradually in G1, G2 and G3-4 of CKD, which were 66.3%, 73.2% and 82.7% (P = 0.014). After adjusting for confounding factors, NAG/Cr >1.41 U/mmol (the highest tertile) was a consistently independent risk factor for DPN [odds ratio, OR (95% confidence interval, CI) = 1.86 (1.04-3.33)]. However, UACR, eGFR and β2-MG did not significantly affect the risk of DPN.

CONCLUSION

When T2DM patients suffer from CKD, DPN will be more likely to appear, accelerate or deteriorate. Some easily available urinary markers of glomerular and tubular damage can be used for early prediction of DPN, in which increased NAG/Cr is an independent risk factor for DPN.

Incidence and Risk Factors Associated with Outpatient Hypoglycemia in Patients with Type 2 Diabetes and Chronic Kidney Disease: A Nationwide Study

BACKGROUND

Chronic kidney disease and hypoglycemia are common complications in individuals with diabetes. Currently, the association of renal function with hypoglycemic complications in type 2 diabetes mellitus (T2DM) is inconclusive. This study aims to assess the associations between estimated glomerular filtration rate (eGFR) and cumulative incidence of hypoglycemia, hypoglycemia-related hospitalizations, and incidence of outpatient hypoglycemia among T2DM patients in Thailand using a nationwide patient sample.

METHODS

We conducted a nationwide retrospective cohort study based on the DM/HT study of the Medical Research Network of the Consortium of Thai Medical Schools. This study assessed adult T2DM patients from 831 public hospitals in Thailand in the year 2012-2013. eGFR was categorized into ≥90, 60-89, 30-59, 15-29, and <15 mL/min/1.73 m². The associations between eGFR and hypoglycemia, hypoglycemia-related hospitalizations, and incidence of outpatient hypoglycemia were assessed using multivariate logistic regression and Poisson regression.

RESULTS

A total of 25,056 T2DM patients with available eGFR were included in the analysis. The mean age was 60.9 ± 10.5 years. The cumulative incidence of hypoglycemia and hypoglycemia-related hospitalizations was 3.6% and 1.7%, respectively. Incidence of outpatient hypoglycemia, mild hypoglycemia, and severe hypoglycemia was 2.99 (2.59-3.43), 2.47 (2.11-2.88), and 0.52 (0.36-0.72) per 100 patient-years, respectively. Patients with eGFR of 30-59, 15-29, and <15 mL/min/1.73 m² were significantly associated with an increased risk of hypoglycemia, hypoglycemia-related hospitalizations, and incidence of outpatient hypoglycemia when compared to patients with eGFR of ≥90 mL/min/1.73 m².

CONCLUSION

Reduced eGFR was independently associated with increased hypoglycemia, hypoglycemia-related hospitalizations, and risk of outpatient hypoglycemia. Increasing awareness of the heightened risk of hypoglycemia with declining renal function may prompt changes to diabetic management for at-risk individuals.

Diagnosing peripheral neuropathy in South-East Asia: A focus on diabetic neuropathy

Burning and stabbing pain in the feet and lower limbs can have a significant impact on the activities of daily living, including walking, climbing stairs and sleeping. Peripheral neuropathy in particular is often misdiagnosed or underdiagnosed because of a lack of awareness amongst both patients and physicians. Furthermore, crude screening tools, such as the 10-g monofilament, only detect advanced neuropathy and a normal test will lead to false reassurance of those with small fiber mediated painful neuropathy. The underestimation of peripheral neuropathy is highly prevalent in the South-East Asia region due to a lack of consensus guidance on routine screening and diagnostic pathways. Although neuropathy as a result of diabetes is the most common cause in the region, other causes due to infections (human immunodeficiency virus, hepatitis B or C virus), chronic inflammatory demyelinating polyneuropathy, drug-induced neuropathy (cancer chemotherapy, antiretrovirals and antituberculous drugs) and vitamin deficiencies (vitamin B1 , B6 , B12 , D) should be actively excluded.

SGLT2 Inhibitors and Kidney Outcomes in Patients with Chronic Kidney Disease

Globally, diabetes mellitus is a leading cause of kidney disease, with a critical percent of patients approaching end-stage kidney disease. In the current era, sodium-glucose co-transporter 2 inhibitors (SGLT2i) have emerged as phenomenal agents in halting the progression of kidney disease. Positive effects of SGLT2i are centered on multiple mechanisms, including glycosuric effects, tubule-glomerular feedback, antioxidant, anti-fibrotic, natriuretic, and reduction in cortical hypoxia, alteration in energy metabolism. Concurrently, multiple kidney and cardiovascular outcome studies have reported remarkable advantages of SGLT2i including mortality benefits. Additionally, the superiority of combination therapies (SGLT2I along with metformin/DDP-4 Inhibitors) in treatment-naïve diabetic patients is further looked into with potential signal towards glycemic and blood pressure control. Reported promising results initiate a gateway for future research targeting kidney outcomes with combination therapies as an initial approach. In the current paper, we summarize leading cardiovascular and kidney outcome trials in patients with type 2 diabetes, the role of SGLT2i in non-diabetic proteinuric kidney disease, and the potential mechanisms of action of SGLT2i with special focus on combination therapy as an initial therapeutic approach in treatment-naïve diabetic patients.

The Association between Serum Uric Acid and Peripheral Neuropathy in Patients with Type 2 Diabetes Mellitus: A Multicenter Nationwide CrossSectional Study

Background

The role of uric acid in the development of diabetic peripheral neuropathy remains unclear. This study aimed to determine the association between uric acid and peripheral neuropathy among type 2 diabetes mellitus (T2DM) patients.

Methods

We conducted a nationwide cross-sectional study based on the diabetes and hypertension study of the Medical Research Network of the Consortium of Thai Medical Schools. Adult T2DM patients from 831 public hospitals in Thailand were evaluated. The serum uric acid level was categorized into five groups based on quintiles (<4.4, 4.4–5.3, 5.3–6.2, 6.2–7.3, and >7.3 mg/dL). A multivariate logistic regression model was used to assess the independent association between serum uric acid level and peripheral neuropathy.

Results

In total, 7,511 T2DM patients with available data about serum uric acid levels were included in the analysis. The mean age of the participants was 61.7±10.9 years, and approximately 35.6% were men. The prevalence rate of peripheral neuropathy was 3.0%. Moreover, the prevalence rates of peripheral neuropathy stratified according to uric acid levels <4.4, 4.4–5.3, 5.3–6.2, 6.2–7.3, and >7.3 mg/dL were 2.5%, 2.8%, 2.4%, 2.5%, and 4.7%, respectively. A serum uric acid level ≥7.3 mg/dL was found to be associated with an increase in odds ratio (1.54; 95% confidence interval, 1.02–2.32) for peripheral neuropathy compared with a serum uric acid level <4.4 mg/dL.

Conclusion

Serum uric acid level is independently associated with peripheral neuropathy in T2DM patients, and elevated serum uric acid levels should be considered a risk factor for diabetic peripheral neuropathy in clinical practice.

Diagnostics, Risk Factors, Treatment and Outcomes of Acute Kidney Injury in a New Paradigm

Acute kidney injury (AKI) is a common clinical condition among patients admitted in the hospitals. The condition is associated with both increased short-term and long-term mortality. With the development of a standardized definition for AKI and the acknowledgment of the impact of AKI on patient outcomes, there has been increased recognition of AKI. Two advances from past decades, the usage of computer decision support and the discovery of AKI biomarkers, have the ability to advance the diagnostic method to and further management of AKI. The increasingly widespread use of electronic health records across hospitals has substantially increased the amount of data available to investigators and has shown promise in advancing AKI research. In addition, progress in the finding and validation of different forms of biomarkers of AKI within diversified clinical environments and has provided information and insight on testing, etiology and further prognosis of AKI, leading to future of precision and personalized approach to AKI management. In this this article, we discussed the changing paradigms in AKI: from mechanisms to diagnostics, risk factors, and management of AKI.

Establishment of Clinical Prediction Model Based on the Study of Risk Factors of Stroke in Patients With Type 2 Diabetes Mellitus

Purpose: Stroke has sparked global concern as it seriously threatens people's life, bringing about dramatic health burdens on patients, especially for type 2 diabetes mellitus (T2DM) patients. Therefore, a risk scoring model is urgently valuable for T2DM patients to predict the risk of stroke incidence and for positive health intervention. Methods: We randomly divided 4,335 T2DM patients into two groups, training set (n = 3,252) and validation set (n = 1,083), at the ratio of 3:1. Characteristic variables were then selected based on the data of training set through least absolute shrinkage and selection operator regression. Three models were established to verify predictive ability. Foundation model was composed of basic information and physical indicators. Biochemical model consisted of biochemical indexes. Integrated model combined the above two models. Data of three models were then put into logistic regression analysis to form nomogram prediction models. Tools including C index, calibration plot, and curve analysis were implemented to test discrimination, calibration, and clinical use. To select the best predicting model, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were put into effect. Results: Eleven risk factors were determined, including age, duration of T2DM, estimated glomerular filtration rate, systolic blood pressure, diastolic blood pressure, low-density lipoprotein, high-density lipoprotein, triglyceride, body mass index, uric acid, and glycosylated hemoglobin A_1c, all with significant P-values through logistic regression analysis. In the training set, areas under the curve of three models were 0.810, 0.819, and 0.884, whereas in the validation set, they were 0.836, 0.832, and 0.909. Through calibration plot, the S:P values in the training set were 0.836, 0.754, and 0.621 and were 0.918, 0.682, and 0.666 separately in the validation set. In terms of the decision curve analysis, the risk thresholds were, respectively, 8-73%, 8-98%, and 8%~ in the training set and 8-70%, 8-90%, and 8-95% in the validation set. With the aid of NRI and IDI, integrated model is proved to be the best model in training set and validation set. Besides, internal validation was conducted on all the subjects in this study, and the C index was 0.890 (0.873-0.907). Conclusion: This study established a model predicting risk of stroke for T2DM patients through a community-based survey.