Disease In Diabetic Patients Research Articles

Metformin Shortens Prolonged QT Interval in Diabetic Mice by Inhibiting L-Type Calcium Current: A Possible Therapeutic Approach.

The incidence and mortality of cardiovascular disease in diabetic patients are 2-3 times higher than those in non-diabetic patients. Abnormal function of the L-type calcium channel in myocardial tissue might result in multiple cardiac disorders such as a prolonged QT interval. Therefore, QT prolongation is an independent risk factor of cardiovascular disease in patients with diabetes mellitus. Metformin, a hypoglycemic agent, is widely known to effectively reduce the occurrence of macrovascular diseases. The aim of the present study was to evaluate the effect of metformin on prolonged QT interval and to explore potential ionic mechanisms induced by diabetes. Diabetic mouse models were established with streptozotocin and an electrocardiogram was used to monitor the QT interval after 4 weeks of metformin treatment in each group. Action potential duration (APD) and L-type calcium current (ICa-L) were detected by patch-clamp in isolated mice ventricular cardiomyocytes and neonatal cardiomyocytes of mice. The expression levels of CACNA1C mRNA and Cav1.2 were measured by real-time PCR, western blot and immunofluorescence. A shortened QT interval was observed after 4 weeks of metformin treatment in diabetic mice. Patch-clamp results revealed that both APD and ICa-L were shortened in mouse cardiomyocytes. Furthermore, the expression levels of CACNA1C mRNA and Cav1.2 were decreased in the metformin group. The same results were also obtained in cultured neonatal mice cardiomyocytes. Overall, these results verify that metformin could shorten a prolonged QT interval by inhibiting the calcium current, suggesting that metformin may play a role in the electrophysiology underlying diabetic cardiopathy.

Influence of exercise training on diabetic kidney disease: A brief physiological approach.

Diabetic kidney disease (DKD) is associated with increased mortality in diabetic patients and has a negative impact on public health. The identification of potential therapies that help the management of DKD can contribute to the improvement of health and quality of life of patients. Thus, this paper is timely and relevant because, in addition to presenting a concise review of the pathogenesis and major pathophysiological mechanisms of DKD, it addresses the most recent findings on the impact of exercise training on this disease. Thus, since non-pharmacological interventions have gained increasing attention in the fight against chronic diseases, this paper appears as an important tool to increase knowledge and stimulate innovative research on the impact of exercise on kidney disease.

Identification of Susceptibility Modules and Genes for Cardiovascular Disease in Diabetic Patients Using WGCNA Analysis.

Objective To identify susceptibility modules and genes for cardiovascular disease in diabetic patients using weighted gene coexpression network analysis (WGCNA). Methods The raw data of GSE13760 were downloaded from the Gene Expression Omnibus (GEO) website. Genes with a false discovery rate < 0.05 and a log2 fold change ≥ 0.5 were included in the analysis. WGCNA was used to build a gene coexpression network, screen important modules, and filter the hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for the genes in modules with clinical interest. Genes with a significance over 0.2 and a module membership over 0.8 were used as hub genes. Subsequently, we screened these hub genes in the published genome-wide SNP data of cardiovascular disease. The overlapped genes were defined as key genes. Results Fourteen gene coexpression modules were constructed via WGCNA analysis. Module greenyellow was mostly significantly correlated with diabetes. The GO analysis showed that genes in the module greenyellow were mainly enriched in extracellular matrix organization, extracellular exosome, and calcium ion binding. The KEGG analysis showed that the genes in the module greenyellow were mainly enriched in antigen processing and presentation, phagosome. Fifteen genes were identified as hub genes. Finally, HLA-DRB1, LRP1, and MMP2 were identified as key genes. Conclusion This was the first study that used the WGCNA method to construct a coexpression network to explore diabetes-associated susceptibility modules and genes for cardiovascular disease. Our study identified a module and several key genes that acted as essential components in the etiology of diabetes-associated cardiovascular disease, which may enhance our fundamental knowledge of the molecular mechanisms underlying this disease.

A PKB-SPEG signaling nexus links insulin resistance with diabetic cardiomyopathy by regulating calcium homeostasis

Diabetic cardiomyopathy is a progressive disease in diabetic patients, and myocardial insulin resistance contributes to its pathogenesis through incompletely-defined mechanisms. Striated muscle preferentially expressed protein kinase (SPEG) has two kinase-domains and is a critical cardiac regulator. Here we show that SPEG is phosphorylated on Ser2461/Ser2462/Thr2463 by protein kinase B (PKB) in response to insulin. PKB-mediated phosphorylation of SPEG activates its second kinase-domain, which in turn phosphorylates sarcoplasmic/endoplasmic reticulum calcium-ATPase 2a (SERCA2a) and accelerates calcium re-uptake into the SR. Cardiac-specific deletion of PKBα/β or a high fat diet inhibits insulin-induced phosphorylation of SPEG and SERCA2a, prolongs SR re-uptake of calcium, and impairs cardiac function. Mice bearing a Speg3A mutation to prevent its phosphorylation by PKB display cardiac dysfunction. Importantly, the Speg3A mutation impairs SERCA2a phosphorylation and calcium re-uptake into the SR. Collectively, these data demonstrate that insulin resistance impairs this PKB-SPEG-SERCA2a signal axis, which contributes to the development of diabetic cardiomyopathy.

Assessment of Cardiovascular Disease Risk among Qatari Patients with Type 2 Diabetes Mellitus, Attending Primary Health Care Centers, 2014

Background: The accumulated knowledge on the development of cardiovascular disease in diabetic patients due to clustering and synergistic interaction of multiple risk factors leads to the establishment of cardiovascular disease 10-year risk prediction tools. The management of patients based on their total risk prediction is an effective way to reduce disease burden. The behavior of such tools varies based on population and their risk profile. Objective: To estimate the total 10-year cardiovascular disease risk using General Framingham Risk Prediction Score and World Health Organization /International Society for Hypertension (WHO/ISH) Risk Prediction Chart on Qatari diabetic patients. Methods: Cross-sectional design was used. A total of 532 Qatari diabetic patients attending primary healthcare were enrolled. Data were collected using an interview administered questionnaire, anthropometric &amp; blood pressure measurement, and medical records. The total 10-year cardiovascular disease risk was assessed using the WHO/ISH risk prediction chart and Framingham score. Results: The former categorized (81.6%) of participants as low risk and only (3.8%) as in high and very high risk. While the later categorized (12.2%) of participants as low risk and (57.6%) as in high and very high risk. No agreement between both tools in assessment of cardiovascular disease risk (κ = - 0.019, p-value = 0.216). All risk factors used by both tools illustrated a statistically significant relation with risk categories, except ‘anti-hypertensive medications intake’ in the Framingham score. Conclusion: Encouraging assessment of patients based on total risk rather than single risk factor and further study of total risk prediction can help to establish a national tool for Qatar.

Epicardial fat thickness and severity of coronary artery disease: a review

People with diabetes are at high risk of coronary artery disease (CAD,) duration of diabetes is directly proportional to macro vascular complications. Epicardial fat through its various mechanism and anatomical closeness to the myocardium it has the direct impact on the severity of CAD. Aim of the study was to determine the correlation between epicardial fat thickness and severity of coronary artery disease in diabetic patients using syntax scoring system. The references used in this review were identified through PubMed and Google Schlor searches of articles published for the last 20 years. Search terms included CAD, correlation of EFT in CAD, syntax scoring system , Gensini scoring system, 2D-ECHO, diabetes in CAD. We reviewed 50 articles done on only humans. We reviewed relevant review articles also. It can be concluded that Epicardial fat thickness has significant correlation with severity of coronary artery disease.

Evaluation of hemogram parameters in diabetic patients with coronary artery ectasia

Aim: To compare the importance of hemogram parameters in predicting the disease in diabetic patients with coronary artery ectasia (CAE) and normal coronary artery. Methods: The records of 7287 patients who underwent coronary angiography between January 2017 and October 2019 were reviewed. After appropriate exclusions, diabetic patients were divided into coronary artery ectasia and normal coronary artery groups. A total of 248 patients were included in the study and hemogram parameters of these two groups were compared. Results: Compared to control group white blood count (WBC) [8 (4-13) vs. 7 (5-12) u/mm3, p=0.023], hemoglobin [13 (10-16) vs. 14 (10-20) gr/dL, p=0.015], red cell distribution width (RDW) [16 (14-20) vs. 15 (12-19) %, p=0.026], neutrophil [4.5 (2.1-11.4) vs. 4.0 (0.2-7.5) u/mm3, p=0.003], platelet counts (Plt) [266 (196-450) vs. 236 (163-362) k/mm3 p<0.001], platelet distribution width (PDW) (17.9 (16.2-20.4) vs. 17.7 (15.9-19.7) % p=0.011), mean platelet volume (MPV) [8.4 (6.4-11.2) vs. 7.9 (6.6-10.1) Fl, p=0.015], plateletcrit (PCT) [0.20 (0.14-0.32) vs. 0.19 (0.13-0.26), p<0.001], and neutrophil lymphocyte ratio (NLR) [2.1 (1.0-9.7) vs. 1.6 (0.2-5.7), p=0.002] were significantly higher in CAE patients. Conclusion: The results of this study suggest that the increased some hemogram parameters may be useful in predicting disease in diabetic patients with CAE.

A Clinical Decision Support System for Assessing the Risk of Cardiovascular Diseases in Diabetic Hemodialysis Patients.

One of the greatest challenges in the field of medicine is the increasing burden of chronic diseases, such as diabetes. Diabetes may cause several complications, such as kidney failure which is followed by hemodialysis and an increasing risk of cardiovascular diseases. The purpose of this research was to develop a clinical decision support system for assessing the risk of cardiovascular diseases in diabetic patients undergoing hemodialysis by using a fuzzy logic approach. This study was conducted in 2018. Initially, the views of physicians on the importance of assessment parameters were determined by using a questionnaire. The face and content validity of the questionnaire was approved by the experts in the field of medicine. The reliability of the questionnaire was calculated by using the test-retest method (r = 0.89). This system was designed and implemented by using MATLAB software. Then, it was evaluated by using the medical records of diabetic patients undergoing hemodialysis (n=208). According to the physicians' point of view, the most important parameters for assessing the risk of cardiovascular diseases were glomerular filtration, duration of diabetes, age, blood pressure, type of diabetes, body mass index, smoking, and C reactive protein. The system was designed and the evaluation results showed that the values of sensitivity, accuracy, and validity were 85%, 92% and 90%, respectively. The K-value was 0.62. The results of the system were largely similar to the patients' records and showed that the designed system can be used to help physicians to assess the risk of cardiovascular diseases and to improve the quality of care services for diabetic patients undergoing hemodialysis. By predicting the risk of the disease and classifying patients in different risk groups, it is possible to provide them with better care plans.

Association between serum insulin like growth factor-1 (IGF-1) and insulin-like growth factor-binding protein-3 levels and chronic kidney disease in diabetic patients

Introduction: Insulin-like growth factor-1 (IGF-1) is a potent mitogen for glomerular mesangial cells which can stimulate cell migration and the production of fibronectin, proteoglycan, and type IV collagen, thereby promoting the development of the chronic kidney disease (CKD) in patients with diabetes. Objectives: The aim of the study was to assess the associations between serum levels of IGF-1 and insulin-like growth factor-binding protein-3 (IGFBP-3) and CKD in diabetic patients. Patients and Methods: We investigated 102 Belarusian men and women with diabetes type 2 aged 56.67±0.81 years. Control group included 68 healthy people the same age. We estimated GFR with the use of the CKD-EPI creatinine-cystatin C equation to determine eGFRcr_cys. Serum total IGF-1 and IGFBP-3 levels were measured using immunoradiometric assay (IRMA) (Beckman Coulter, Czech Republic s.r.o.). Results: Patients with diabetes had significantly lower level of IGF-1 than controls. However, IGFBP-3 levels were similar in the two groups. Diabetic patients with CKD had significantly higher levels of IGF-1 and IGFBP-3 than diabetic patients without CKD (P=0.0031). However, according to multivariate analysis, only IGF-1 and cystatin C were associated with renal impairment. In detail, the odds of having eGFR&lt;60 mL/min/1.73 m2 increased with rising IGF-1 levels (OR: 1.025, [CI 1.002-1.048]). Conclusion: Our study revealed that higher serum IGF-1 levels were positively associated with CKD in patients with diabetes. We suggest that IGF-1 might be a predictor of CKD in patients with diabetes. Further research is necessary to confirm the observed this association and to detect the causal relations.

Correlation between Atherogenic index and the severity of coronary artery disease in diabetic patients undergoing elective coronary angiography using Gensini score

Abstract Background Dyslipidemia is one of the most important factors for CAD. Atherogenic index of plasma (AIP) is a new indicator involved in dyslipidemia. However, its relation with CAD severity in diabetic patients is not well established yet. Aim of the Study To study the relationship between atherogenic index of plasma and severity of coronary artery disease (CAD) in the diabetic patients. Methods Our study was conducted on 150 diabetic patient with stable CAD undergoing elective coronary angiography in Al-Agoza Hospital from april 2016 to august 2018. Atherogenic index was calculated from the logarithmically transformed ratio of concentrations of TGs to HDL-C obtained from the patient’s lipid profile. correlation of the AIP and the severity of CAD according to Gensini scoring system was done. Results AIP had a statistically significant positive relation with IDDM (p = 0.033), NIDDM (p = 0.033), HTN (p = 0.024), dyslipedemia (p = 0.042). And a highly significant positive correlation with FBS (p &amp;lt; 0.001, r = 0.479) and HbA1c (p &amp;lt; 0.001, r = 0.538), proximal LAD lesions (p = 0.002), LCX (p &amp;lt; 0.001), and the number of vessls affected (p = 0.005). AIP Also had a highly significant positive correlation with severity of CAD in terms of Gensini score (p &amp;lt; 0.001, r = 0.692). Conclusion AIP is considered a good predictor of CAD severity and multivessel affection in diabetic patients.

A Framework for Diagnosing Kidney Disease in Diabetes Patients Using Classification Algorithms

Data mining algorithms are widely used to extract latent trends or patterns from databases. They are used to predict unknown class labels in order to help in accurate decision making process. The machine learning techniques are very useful in applications of healthcare domain. In this domain, the techniques are employed to diagnose diseases and even predicting the probabilities related to health and other aspects. Since diabetes is one of the diseases that prevail in Indians now and it causes other diseases as well, in this paper we studied the kidney disease diagnosis in diabetes patients. Kidney disease dataset is used to explore four different data mining algorithms. They are known as Naive Bayes, decision table, J48 and random forest. The dataset is used to have both training and testing sets and produce prediction details. These algorithms are evaluated by using measures like accuracy, mean absolute error (MAE) and root-mean-squared error (RMSE). The results revealed that all the machine learning algorithms are able to predict the disease. However, they differ in accuracy levels. With tenfold cross-validation, it is understood that random forest showed the highest accuracy, while Naive Bayes showed least MAE and RMSE. We built prototype application to demonstrate proof of the concept. Our experimental results revealed that the proposed framework to evaluate machine learning algorithms is useful.

Comparative Study between Diabetic and non- Diabetic Patients Regarding Prevalence of Coronary Artery Disease and Plaque Composition by Multi-detector CT Coronary Angiography

Abstract Diabetes is known to be a major cardiovascular risk factor associated with significantly increased morbidity and mortality and particularly increased risk of major cardiac events especially myocardial infarction as a manifestation of highly incident coronary artery disease (CAD).This can lead to decreased life expectation and life quality. Major cause for myocardial infarction is plaque rupture. Prevalence of obstructive and non-obstructive plaques is increased in diabetic patients. Background and Objectives The prevalence of coronary heart disease in diabetic patients compared to non- diabetics and evaluating the composition of the plaque in diseased individuals in both groups by usage of multislice computed tomography (MSCT) angiography . Subjects and Methods A total of 80 consecutive MSCT angiography examinations were performed between August 2017 and June 2018. Of these, the patients were evaluated for the presence and type of atherosclerotic plaque and severity of luminal narrowing. Results Eighty (40 in the diabetic group and 40 in the non-diabetic group) patients underwent MSCT angiography with DM prevalence of 0.212 (95% Cl for AOR 0.056 -1.896). Among them, 20 patients (50 %) in the diabetic group and 14 patients (35 %) in the non-diabetic group had +ve coronary heart disease, 33.3 % had significant and moderately significant coronary narrowing on diabetic group and 31.3 % in non-diabetic group on MSCT angiography. Diabetic patients had more soft plaque compared with non-diabetic patients. Conclusion DM is not an independent factor for the disease occurrence in coronary artery disease but is a dependent factor in the association of other risk factors such as smoking ,hypertension and dyslipidemia.

Rhein-8-O-β-D-glucopyranoside inhibited high glucose-induced apoptosis of human mesangial cells by regulating the lincRNA ANRIL/let-7a/TGF-β1/Smad signaling pathway.

Diabetic nephropathy is one of most frequent complications of diabetes, and is the major cause of end-stage disease in diabetic patients. The present study investigated the roles and mechanisms of Rhein-8-O-β-D-glucopyranoside (Rg) protecting human mesangial cells (HMCs) from high glucose (HG)-induced apoptosis. Using a Cell Counting Kit-8 assay the proliferation of HMCs was analyzed, and flow cytometry was applied to detect apoptosis. The apoptosis-associated protein Bcl-2, caspase-3 and members of the transforming growth factor-β1 (TGF-β1)/Smad signaling pathway were analyzed using a western blotting assay. HG significantly induced HMC apoptosis, and Rg markedly attenuated the HG-induced apoptosis. HG decreased the Bcl-2 expression and increased the caspase-3 expression, and Rg treatment recovered the expressions of Bcl-2 and caspase-3 affected by HG. The underlying mechanisms were further analyzed, and it was demonstrated that HG significantly upregulated the long intervening non-coding RNA (lincRNA) ANRIL expression level, downregulated let-7a expression and activated the TGF-β1/Smad signaling pathway; Rg treatment recovered the expressions of lincRNA ANRIL and let-7a, and inhibited the TGF-β1/Smad signaling pathway in the condition of HG. In conclusion, the present results suggested that Rg attenuated HG-induced apoptosis of HMCs by regulating the lincRNA ANRIL/let-7a/TGF-β1/Smad signaling pathway.

Correlation of glycosylated hemoglobin level with the severity of coronary artery disease in diabetic patients

Background: Diabetes Mellitus (DM) is known to cause microvascular and possibly macrovascular complications as it one of the major risk factors for Coronary Artery Disease (CAD). CAD is a major cause of death in developed countries. The study aims to assess the relation of glycated Hemoglobin (HbA1c) levels and severity of CAD in diabetic patients.

Prevalence and risk factors of diabetic retinopathy in diabetic patients

In China, there is a significant lack of awareness of diabetes and its complications. Screening of diabetic retinopathy has important for early detection, prevention, and treatment. This large, cross-sectional study aimed to characterize the demographic, physical, serological, and ocular characteristics of subjects with diabetes mellitus in Shijiazhuang, China. It also aimed to associate these characteristics with the presence of diabetic retinopathy.From May 2, 2018 to August 25, 2019, under diabetes care program, the diabetic patients (n = 1008) were subjected to standardized questionnaires to collect demographical characteristics. Also, telescreens and laboratory tests were performed for the enrolled patients. Multivariate logistic regression analysis was used to evaluate factors associated with diabetic retinopathy.Forty percent of diabetics in its population had some form of diabetic retinopathy. Diabetic retinopathic patients were likely to be elder (P = .0003), men (P = .018), hypertensive (P < .0001), and had high body mass index (P < .0001), metabolic abnormalities, and longer duration of diabetes (P < .0001). Higher intraocular pressure (P = .0008), fasting blood glucose (P < .0001), serum total cholesterol (P < .0001), serum triglyceride (P = .0006), % glycated hemoglobin (HbA1c) (P < .0001), and disc asymmetry including cup–disc ratio (P = .041) reported in patients with diabetic retinopathy. Age (P = .049), male sex (P = .048), hypertension (P = .048), duration of diabetes (P = .012), diabetic neuropathy (P = .048), diabetic nephropathy (P = .048), diabetic foot ulcer (P = .041), foot amputation (P = .042), fasting blood glucose (P = .022), serum total cholesterol (P = .028), serum triglyceride (P = .035), and HbA1c (P = .042) were associated with diabetic retinopathy.Diabetic retinopathy was the most common ocular fundus disease in diabetic patients. Also, aging, the other comorbidities, and metabolic syndrome are associated with diabetic retinopathy.Level of Evidence: III.

A novel automated system of discriminating Microaneurysms in fundus images

Diabetic retinopathy, a chronic disease in diabetic patients leads to Vision loss, by disabling microvascular complications, if not recognized and cured at the earlier stage. This article explores a novel and reliable method for automatic early detection of Microaneurysms (MA) in fundus images. Microaneurysms characterized by small red spots on the retina, the red lesions are symptoms of early stage of DR. Development of an automated screening system would assist an ophthalmologist in diagnosing DR at an early stage. Hence, in this paper, a novel feature extraction technique using a Local Neighborhood Differential Coherence Pattern (LNDCP) is proposed. In this method, texture characteristics needed for classification by Feed Forward Neural Network (FFNN) is captured efficiently. The performance of the algorithm is validated using experiments on Retinopathy Online Challenge (ROC) public dataset and a single real-time dataset, AGAR300. Efficiency of the algorithm is benchmarked with state-of-art approaches and a Free-response Receiver Operating Characteristic (FROC) score of 0.481 and 0.442 have been achieved for ROC and AGAR300 respectively.

Risk factors for non-diabetic renal disease in diabetic patients.

BackgroundDiabetic patients with kidney disease have a high prevalence of non-diabetic renal disease (NDRD). Renal and patient survival regarding the diagnosis of diabetic nephropathy (DN) or NDRD have not been widely studied. The aim of our study is to evaluate the prevalence of NDRD in patients with diabetes and to determine the capacity of clinical and analytical data in the prediction of NDRD. In addition, we will study renal and patient prognosis according to the renal biopsy findings in patients with diabetes.MethodsRetrospective multicentre observational study of renal biopsies performed in patients with diabetes from 2002 to 2014.ResultsIn total, 832 patients were included: 621 men (74.6%), mean age of 61.7 ± 12.8 years, creatinine was 2.8 ± 2.2 mg/dL and proteinuria 2.7 (interquartile range: 1.2–5.4) g/24 h. About 39.5% (n = 329) of patients had DN, 49.6% (n = 413) NDRD and 10.8% (n = 90) mixed forms. The most frequent NDRD was nephroangiosclerosis (NAS) (n = 87, 9.3%). In the multivariate logistic regression analysis, older age [odds ratio (OR) = 1.03, 95% CI: 1.02–1.05, P < 0.001], microhaematuria (OR = 1.51, 95% CI: 1.03–2.21, P = 0.033) and absence of diabetic retinopathy (DR) (OR = 0.28, 95% CI: 0.19–0.42, P < 0.001) were independently associated with NDRD. Kaplan–Meier analysis showed that patients with DN or mixed forms presented worse renal prognosis than NDRD (P < 0.001) and higher mortality (P = 0.029). In multivariate Cox analyses, older age (P < 0.001), higher serum creatinine (P < 0.001), higher proteinuria (P < 0.001), DR (P = 0.007) and DN (P < 0.001) were independent risk factors for renal replacement therapy. In addition, older age (P < 0.001), peripheral vascular disease (P = 0.002), higher creatinine (P = 0.01) and DN (P = 0.015) were independent risk factors for mortality.ConclusionsThe most frequent cause of NDRD is NAS. Elderly patients with microhaematuria and the absence of DR are the ones at risk for NDRD. Patients with DN presented worse renal prognosis and higher mortality than those with NDRD. These results suggest that in some patients with diabetes, kidney biopsy may be useful for an accurate renal diagnosis and subsequently treatment and prognosis.

Percutaneous transluminal angioplasty for isolated infrapopliteal arterial occlusive disease in diabetic patients with critical limb ischemia

Background Critical limb ischemia (CLI) is considered the most severe stage of peripheral artery disease. Patients with CLI typically have the disease affecting multiple levels (i.e. aortoiliac, femoropopliteal, and infrapopliteal). CLI due to isolated infrapopliteal arterial disease is commonly seen in patients with long-standing diabetes mellitus, chronic kidney disease, or the elderly. Endovascular treatment of infrapopliteal arteries has been considered a primary approach for revascularization in CLI. Objective The aim of this study was to evaluate the efficacy of percutaneous transluminal angioplasty (PTA) for isolated infrapopliteal arterial occlusive disease in diabetic patients with CLI. Patients and methods This prospective study included 20 diabetic patients with CLI in 28 limbs due to isolated infrapopliteal arterial occlusive disease who underwent infrapopliteal PTA between January 2017 and January 2019 in Mataria Teaching Hospital, Cairo, Egypt. Results The study was conducted on 20 diabetic patients, 12 (60%) men and eight (40%) women. Their age ranged between 54 and 76 years with a mean age of 65 years. Successful recanalization was achieved in 23 (82.1%) limbs. Reintervention was needed in five (17.9%) limbs and it was successful in four limbs. The follow-up period ranged from 6 to 18 months with the mean overall follow-up being 12.5 months. The primary patency rate and secondary patency rate were, respectively, 78.3 and 80% at 1 year. The limb salvage rates after 1 year were 75%. Mortality rate after 1 year was 10%. Conclusion PTA is effective and the preferred procedure for revascularization and limb salvage in diabetic patients with CLI due to isolated infrapopliteal arterial occlusive disease.

Prevalence and pattern of skin diseases in patients with diabetes mellitus at a tertiary hospital in Northern Nigeria.

Diabetes mellitus is one of the most common metabolic disorders with a rising prevalence. It cuts across all ages and socioeconomic status. Various skin lesions are frequently observed in diabetic patients. This study was carried out to determine the prevalence, pattern, and determinants of skin diseases in diabetic patients at the Barau Dikko Teaching Hospital, Kaduna, North West Nigeria. One hundred consecutive diabetic patients attending the clinic were included in the study. Many of the patients had more than one skin condition at a time. The most prevalent skin diseases were idiopathic guttate hypomelanosis which was seen in 61% of patients, infections from fungal, bacterial, and viral causes occurred in 30% of patients, other skin disorders were diabetic dermopathy seen in 17% of patients, palmoplantar hyperpigmentation was seen in 13% of patients, while pruritus occurred in 12% of patients and xerosis was seen in 10% of patients. Skin disorders are common among diabetic patients at Barau Dikko Teaching Hospital, Kaduna, North West Nigeria.

Prevalence and Biomarkers of Diabetic Kidney Disease in Diabetic Patients on Treatment in Buea and Ngaoundere, Cameroon

Diabetic Kidney Disease (DKD) is a complication of diabetes that often leads to the End Stage Renal Disease. It is characterised by the presence of persistent albuminuria and a reduction of the Glomerular Filtration Rate (GFR) in diabetic condition. No study has revealed the prevalence of DKD in Cameroon. This cross-sectional study was conducted in Buea and Ngaoundere to determine the prevalence of DKD and characterize its biochemical profile in diabetic population under medical care. A total of 250 diabetics were enrolled with a mean age of 56.78±12.06 years, out of which 59.6% were diagnosed with Chronic Kidney Disease (CKD), 32.8% presented micro-albuminuria and 3.6% were diagnosed with macroalbuminuria. The prevalence of DKD was 15.2% out of which 78.9% were females (p=0.002). The prevalence of the co-morbidity hypertension and DKD was 8.8%. Significant association was found between DKD and two variables: female gender (OR: 2.28 (1.21-4.29); p=0.002) and hyper-creatinemia (OR: 3.47 (2.13-5.66); p < 0.001). The high prevalence of micro-albuminuria found in this study may reflect a high frequency of micro-albuminuria in diabetic population in Cameroon. This study is the first, to assess DKD in Cameroon according to the ADA consensus on CKD and diabetes. The findings showed that, diabetic complication is a serious problem in Cameroon and, more actions should be taken to improve its management.