Objective: To investigate the prevalence of peripheral arterial disease (PAD) in China type 2 diabetic patients and to demonstrate the relationships between putative risk factors and PAD.
Methods: In total 1,397 type 2 diabetic patients aged 50 years and older were enrolled and determined ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV) in 15 Class III Grade A hospitals in 7 major cities of China.
Results: Mean patient age was 63.7 +/- 8.2 years and mean duration of diabetes mellitus was 9.39 +/- 7.4 years. Two hundreds and seventy-two (19.47%) patients were diagnosed as PAD by ABI < 0.9, 122 (18.37%) in male and 150 (20.46%) in female. PAD patients had a significantly longer duration of diabetes mellitus, higher hemoglobin A1c, and a significantly lower mean body mass index than non-PAD ones. Aging, smoking, and systolic blood pressure were found to be positively related with the prevalence of PAD. In terms of lipid profiles, no variable was found to relate with PAD. Notably, baPWV showed as the same significant guiding index for PAD, almost matched with ABI.
Conclusions: PAD is a common complication in China type 2 diabetic patients. Therefore, PAD screening and treatment should be emphasized for diabetic patients with high risk factors.
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Lancet Reg Health West Pac
January 2025
Division of Nephrology, National Clinical Research Centre for Kidney Disease, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Background: Early diagnosis of chronic kidney disease (CKD) is crucial for timely intervention to delay disease progression and improve patient outcomes. However, data for clinical characteristics of Chinese patients with undiagnosed, early-stage CKD are lacking.
Methods: REVEAL-CKD is a multinational, observational study using real-world data in selected countries to describe factors associated with undiagnosed stage 3 CKD, time to diagnosis, and CKD management post diagnosis.
Front Immunol
January 2025
Laboratory of Immunohematology, Department of Internal Medicine, Medical School, University of Patras, Patras, Greece.
Obesity is a rapidly growing health problem worldwide, affecting both adults and children and increasing the risk of chronic diseases such as type 2 diabetes, hypertension and cardiovascular disease (CVD). In addition, obesity is closely linked to chronic kidney disease (CKD) by either exacerbating diabetic complications or directly causing kidney damage. Obesity-related CKD is characterized by proteinuria, lipid accumulation, fibrosis and glomerulosclerosis, which can gradually impair kidney function.
View Article and Find Full Text PDFPak J Med Sci
January 2025
Amirah Alhowiti Assistant Professor of Family Medicine, Department of Family and Community Medicine, Faculty of Medicine, University of Tabuk, Saudi Arabia.
Objectives: Dyslipidemias are major risk factors for cardiovascular disease, and other comorbidities. The focus on food and nutrition to prevent and treat cardiovascular risk factors including dyslipidemia is a paradigm shift. This is the first meta-analysis to assess the association of dates fruit and dyslipidemia in Type-2 diabetes.
View Article and Find Full Text PDFPak J Med Sci
January 2025
Sadia Anwer Research Student, Biochemistry, Federal Urdu University of Arts, Science & Technology, Karachi, Pakistan.
Objective: To explore the effect of seeds powder { 500 mg} capsule in diabetes Type-2 (T2DM) patients in Karachi.
Methods: A randomized selection of 40 T2DM patients from Sindh Government Hospital New Karachi with their consents was done for a non-blinded controlled trial from October to December 2019 and divided into P (Positive Control, metformin 500 mg) & T (Test, + was also included, using the same dosage of CapCASP on twenty healthy volunteers. The data were analyzed using an online graph pad student's t-test and a one-way ANOVA (SPSS version 24) metformin 500mg each).
Pak J Med Sci
January 2025
Juan Chen, Department of Ophthalmology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China.
Objective: To design a deep learning-based model for early screening of diabetic retinopathy, predict the condition, and provide interpretable justifications.
Methods: The experiment's model structure is designed based on the Vision Transformer architecture which was initiated in March 2023 and the first version was produced in July 2023 at Affiliated Hospital of Hangzhou Normal University. We use the publicly available EyePACS dataset as input to train the model.
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