Impact of vitamin D on glycemic control and microvascular complications in type 2 diabetes: A cross-sectional study

by Salma Ahi, Amirreza Reiskarimian, Mohammad Aref Bagherzadeh, Zhila Rahmanian, Parisa Pilban, Saeed Sobhanian

Vitamin D has been increasingly recognized for its potential role in modulating various health conditions, including diabetes and its complications. Despite growing evidence suggesting that adequate vitamin D levels may reduce the risk of developing type 2 diabetes and its associated microvascular complications, the precise nature of this relationship remains unclear. This study aims to elucidate the connection among vitamin D status, glycemic control, and microvascular complications in patients with type 2 diabetes, thereby highlighting the importance of vitamin D in diabetes management.This analytical cross-sectional study included 199 type 2 diabetic mellitus (T2DM) patients from the Jahrom city endocrinology clinic. Serum 25(OH)D levels were measured, and their microvascular complications (microalbuminuria, retinopathy, neuropathy, macroalbuminuria) and glycemic control (HbA1C) were measured and confirmed according to ADA guidelines and endocrinologist supervision. All analysis were done with SPSS software. The study enrolled 199 type 2 diabetic patients with a mean age of 56.79 ± 10.8 years, of which 63.3% were female and 57.3% had hypertension. The mean BMI was 28.91 kg/m², and 29.1% of participants had vitamin D deficiency. The prevalence of microvascular complications was 25.6% for retinopathy, 14.1% for neuropathy, and 40% for nephropathy. Vitamin D deficiency was notably higher among patients with retinopathy (37.25%), neuropathy (50%), and macroalbuminuria (56.25%). Patients with neuropathy and retinopathy had significantly lesser serum 25(OH)D concentrations compared to patients without these complications. There was a slight inverse correlation between vitamin D levels and both the urine albumin creatinine ratio (r = -0.175, p = 0.018) and HbA1C (r = -0.19, p = 0.007). Although the link between vitamin D levels and retinopathy was not statistically significant (η = 0.903, p = 0.68), the alteration in vitamin D levels was suggestively linked with neuropathy (η = 0.975, p 

Enhanced heart sound classification using Mel frequency cepstral coefficients and comparative analysis of single vs. ensemble classifier strategies

by Mehdi Hosseinzadeh, Amir Haider, Mazhar Hussain Malik, Mohammad Adeli, Olfa Mzoughi, Entesar Gemeay, Mokhtar Mohammadi, Hamid Alinejad-Rokny, Parisa Khoshvaght, Thantrira Porntaveetus, Amir Masoud Rahmani

This paper seeks to enhance the performance of Mel Frequency Cepstral Coefficients (MFCCs) for detecting abnormal heart sounds. Heart sounds are first pre-processed to remove noise and then segmented into S1, systole, S2, and diastole intervals, with thirteen MFCCs estimated from each segment, yielding 52 MFCCs per beat. Finally, MFCCs are used for heart sound classification. For that purpose, a single classifier and an innovative ensemble classifier strategy are presented and compared. In the single classifier strategy, the MFCCs from nine consecutive beats are averaged to classify heart sounds by a single classifier (either a support vector machine (SVM), the k nearest neighbors (kNN), or a decision tree (DT)). Conversely, the ensemble classifier strategy employs nine classifiers (either nine SVMs, nine kNN classifiers, or nine DTs) to individually assess beats as normal or abnormal, with the overall classification based on the majority vote. Both methods were tested on a publicly available phonocardiogram database. The heart sound classification accuracy was 91.95% for the SVM, 91.9% for the kNN, and 87.33% for the DT in the single classifier strategy. Also, the accuracy was 93.59% for the SVM, 91.84% for the kNN, and 92.22% for the DT in the ensemble classifier strategy. Overall, the results demonstrated that MFCCs were more effective than other features, including time, time-frequency, and statistical features, evaluated in similar studies. In addition, the ensemble classifier strategy improved the accuracies of the DT and the SVM by 4.89% and 1.64%, implying that the averaging of MFCCs across multiple phonocardiogram beats in the single classifier strategy degraded the important cues that are required for detecting the abnormal heart sounds, and therefore should be avoided.