Heart Atherosclerotic Disorders Research Articles

Predicting high sensitivity C-reactive protein levels and their associations in a large population using decision tree and linear regression

High-sensitivity C-reactive protein (hs-CRP) is a biomarker of inflammation predicting the incidence of different health pathologies. In this study, we aimed to evaluate the association between hematological and demographic factors with hs-CRP levels using decision tree (DT) and linear regression (LR) modeling. This study was conducted on a population of 9704 males and females aged 35 to 65 years recruited from the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) cohort study. We utilized a data mining approach to construct a predictive model of hs-CRP measurements, employing the DT methodology. DT model was used to predict hs-CRP level using biochemical factors and clinical features. A total of 9,704 individuals were included in the analysis, with 57% of them being female. Except for fasting blood glucose (FBG), hypertension (HTN), and Type 2 diabetes mellites (T2DM), all variables showed significant differences between the two groups. The results of the LR models showed that variables such as anxiety score, depression score, Systolic Blood Pressure, Cardiovascular disease, and HTN were significant in predicting hs-CRP levels. In the DT models, depression score, FBG, cholesterol, and anxiety score were identified as the most important factors in predicting hs-CRP levels. DT model was able to predict hs-CRP level with an accuracy of 72.1% in training and 71.4% in testing of both genders. The proposed DT model appears to be able to predict the hs-CRP levels based on anxiety score, depression scores, fasting blood glucose, systolic blood pressure, and history of cardiovascular diseases.

Multivariate linear regression to predict association of non-invasive arterial stiffness with cardiovascular events.

Arterial stiffness is a crucial factor in determining an increase in systolic blood pressure and pulse pressure and can also predict the development of cardiovascular disease (CVD). The purpose of this study was to examine the relationship between arterial stiffness and future CVD. Out of the original 9704 participants in the Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort study, we randomly selected 363 healthy participants, 226 normal subjects (who reported symptoms of CVD but were not confirmed) and 292 individuals who had experienced a major cardiovascular event. The SphygmoCor XCEL System (AtCor Medical Incorporation) was utilized to measure pulse wave velocity (PWV), central augmentation index (CAI), cardio-ankle vascular index (CAVI) and central aortic pressure (CAP). A multivariate multiple regression model was used to analyse the factors associated with non-invasive arterial stiffness parameters (PWV, CAVI, CAP and CAI) after adjusting for potential confounders. All statistical analyses were conducted using SPSS 21 with a significance level of 0.05. The mean PWV was significantly higher in patients who had experienced a confirmed CVD event (P<0.001). The multivariate multiple regression model results, after adjusting for potential confounders, showed a significant association between PWV and the CVD group (normal vs. healthy and event vs. healthy), as well as between hypertension and obesity with PWV and diabetes with CAI (P<0.05). PWV was found to be associated with CVD and its related risk factors such as diabetes, obesity and hypertension. It may be more effective than other arterial stiffness parameters in predicting CVD in clinical settings.

A novel index for diagnosis of type 2 diabetes mellitus: Cholesterol, High density lipoprotein, and Glucose (CHG) index.

Gold standard methods of type 2 diabetes mellitus are expensive and therefore not practical for large scale studies in low-income countries. We have investigated the total cholesterol, high density lipoprotein (HDL), and glucose (CHG) index for diagnosis of type 2 diabetes mellitus index which is derived from fasting state. In this study we aimed to compare the accuracy of with CHG index and triglycerides (TG) and glucose levels (TyG) as surrogates of type 2 diabetes mellitus. A total of 9,704 individuals between 35 and 65 years of age were recruited as part of the Mashhad stroke and heart atherosclerotic disorder (MASHAD) study. They were categorized into two groups, those with and without type 2 diabetes mellitus. The cut-off in groups to detection of type 2 diabetes mellitus was fasting blood glucose ≥126 mg/dL in blood sample. Receiver operating characteristic (ROC) curve analysis was used to establish the cut-off of indices to evaluate the sensitivity and specificity of them. The best cut-off of CHG index for diagnosis of type 2 diabetes mellitus was 5.57 which was associated with a sensitivity of 70.38% and specificity of 89.82% values. This was in comparison to the TyG index. LR+ CHG index was 6.91 compared to 3.47 for the TyG index and the AUC of CHG index was 0.864 (0.857, 0.871) compared with 0.825 (0.818, 0.833) for the TyG index. This indicates that the CHG index has a higher efficiency value to diagnose of type 2 diabetes mellitus. The CHG index could be useful for the detection of type 2 diabetes mellitus.

HTLV1 infection and long term association with liver function and lipid indices; 10 years’ follow-up

BackgroundHuman T-cell leukemia virus type 1 (HTLV-1) is a well-known retrovirus, particularly prevalent in northeastern Iran, where it is associated with a range of disorders, including liver dysfunction. Previous studies have demonstrated that HTLV-1 infection can alter lipid profiles, yet no research has examined lipid indices and liver function tests in these patients in the long term.MethodsThis data is part of the Mashhad stroke and heart atherosclerotic disorder (MASHAD) study. A total of 1116 participants were randomly selected, including 837 healthy individuals and 279 HTLV-1-infected patients. Following a 10-year follow-up period, Serum levels of liver enzymes were measured. Lipid indices such as the Atherogenic Index of Plasma (AIP), Body Adiposity Index (BAC), Castelli risk index (CRI-I, CRI-II), Lipid Accumulation Product (LAP), Visceral Adiposity Index (VAI), Triglyceride-glucose index (TyG), and Triglyceride and HDL-C Ratio (THR) were calculated.ResultsMultivariable-adjusted regression analysis demonstrated a significant coefficient for the Visceral Adiposity Index (VAI) in HTLV-infected patients compared to healthy controls (B: -0.014, 95% CI: -0.02, 0.00, p = 0.046). However, no significant differences were observed in other lipid indices between HTLV-infected patients and healthy individuals. Regarding liver enzymes, significant variations were noted in HTLV-infected patients compared to healthy controls: Aspartate Aminotransferase (AST) (B: 2.978, 95% CI: 1.34, 4.61, p < 0.001), Alanine Aminotransferase (ALT) (B: 3.687, 95% CI: 1.59, 5.78, p = 0.001), Alkaline Phosphatase (ALP) (B: 18.232, 95% CI: 6.81, 29.65, p = 0.002), and Gamma-Glutamyl Transferase (GGT) (B: 3.714, 95% CI: 0.18, 7.24, p = 0.039).ConclusionIndividuals with HTLV-1 infection exhibit reduced VAI but elevated levels of liver enzymes such as AST, ALT, ALP, and GGT, indicating liver damage. These findings emphasize the virus’s involvement in liver pathology. Also, HTLV-I is associated with reduced visceral fat tissue.

Oxidative balance and mental health: Exploring the link between prooxidant-antioxidant balance and depression in hypertensive and normotensive individuals, accounting for sex differences

BackgroundExisting studies have suggested a link between oxidative stress levels and depression. Additionally, factors such as gender and conditions like hypertension have been shown to influence oxidative stress. This ten-year follow-up cohort study aims to examine the association between prooxidant-antioxidant balance (PAB) and the onset of depression and its symptoms in both hypertensive and normotensive individuals, while considering gender differences. MethodsThe data for this study was obtained from the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study, a cohort study conducted in eastern Iran. Serum PAB levels were measured in 1702 hypertensive and 4096 normotensive individuals aged 35 to 65 years. After ten years, the participants' depression status was evaluated using the Beck questionnaire, and depression symptoms were investigated using the BDI-II structural model, which includes somatic, affective, and cognitive symptoms. ResultThe analysis indicates that in hypertensive male participants, the highest tertile of PAB is associated with an increased risk of depression (β: 1.22, 95 % CI: −0.046, 2.485; P = 0.059) and symptoms of depression, including cognitive (β: 2.937, 95 % CI: 0.511, 5.362; P = 0.018) and somatic (β: 2.654, 95 % CI: 0.37, 4.939; P = 0.023) symptoms. However, there was no significant association between affective symptoms and PAB tertiles. Additionally, there was no significant link between depression and depressive symptoms in female hypertensive and normotensive individuals. ConclusionIn male hypertensive patients, but not in normotensive individuals of both genders and hypertensive women, depression and its associated symptoms, including somatic and cognitive symptoms, are associated with elevated levels of oxidative stress, as evidenced by higher serum PAB values. PAB is not associated with affective symptoms. Future studies should focus on the gender-specific nature of this relationship and work to clarify its underlying mechanisms.

Investigation of the relationship between atherogenic index, anthropometric characteristics, and 10-year risk of metabolic syndrome: a population-based study.

People with metabolic syndrome (MetS) are at a higher risk of coronary artery disease, diabetes mellitus, stroke, osteoarthritis, and some types of cancers. Finding markers which are available and inexpensive are most useful for the prediction of MetS. The present study aimed to determine the relationship between atherogenic index and anthropometric indicators and the 10-year risk of MetS. During the 10-year follow-up on Mashhad stroke and heart atherosclerotic disorder (MASHAD study), 4684 subjects who did not MetS at baseline were recruited in this study. The anthropometric indices and atherogenic index including atherogenic index of plasma (AIP), Castelli's risk index I and II (CRI-I, CRI-I), and atherogenic coefficient (AC) were measured. SPSS-23 was used for all statistical analyses. Among subjects who did not have MetS at baseline 1599 cases (34.1%) developed MetS. The anthropometric and lipid indices were significantly elevated in patients with MetS compared to the healthy ones (p < 0.001). It was revealed that an increase of one unit in AIP and AC can raise the risk of MetS 22.7% (OR: 1.227 (95% CI, 1.166-1.291)) and 37.7% (OR: 1.377 (95% CI, 1.291-1.468)), respectively. Moreover, increasing one unit of WHtR decreases the risk of MetS by 8.5% (OR: 0.915 (95% CI, 0.886-0.946)). The results of this longitudinal study showed that increasing AC and AIP could enhance the risk of MetS. The present study also indicated that AC and AIP are useful predictors in the clinical setting for identifying individuals with MetS in the Iranian adult population.

Anxiety, a significant risk factor for coronary artery disease: what is the best index

BackgroundCoronary artery disease (CAD) is known as the leading cause of disability and death globally. Anxiety disorders are also recognized as common types of mental disorders that substantially impact global health. Iran ranks among the countries with a high incidence of CAD and anxiety disorders. Therefore, the present study aims to determine the potential association and epidemiological aspects of anxiety and CAD within the population of Mashhad, the second most popoulos city in Iran.MethodsThe present study is based on extracted data from the Mashhad stroke and heart atherosclerotic disorder (MASHAD) study which is a 10-year prospective cohort study intended to assess the effects of various CAD risk factors among Mashhad city residents. Anxiety scores were assessed at the baseline using Beck Anxiety Inventory and individuals were classified based on the BAI 4-factor structure model which included autonomic, cognitive, panic, and neuromotor components. Accordingly, the association between baseline anxiety scores and the BAI four-factor model with the risk of CAD events was analyzed using SPSS software version 21.ResultsBased on the results, 60.4% of the sample were female, and 5.6% were classified as having severe forms of anxiety. Moreover, severe anxiety was more prevalent in females. Results showed a 1.7% risk of CAD (p-value < 0.001) over 10 years with one unit increase in anxiety score. Based on the 4-factor model structure, we found that only panic disorder could significantly increase the risk of CAD by 1.1% over the 10-year follow-up (p-value < 0.001).ConclusionAnxiety symptoms, particularly panic disorder, are independently and significantly associated with an increased overall risk of developing CAD over a 10-year period. Therefore, further studies are warranted to investigate the mechanisms through which anxiety may cause CAD, as well as possible interventions to mitigate these processes.

Association of major and minor ECG abnormalities with traditional cardiovascular risk factors in the general population: a large scale study

Cardiovascular disease (CVD) can be determined and quantified using the electrocardiogram (ECG) analysis. Identification of the risk factors associated with ECG abnormalities may advise prevention approaches to decrease CVD burden. In this study we aimed to investigate the association between CVD risk factors and minor and major ECG abnormalities in a general Iranian adult population. This study was conducted in 2010 and covered a population of 9035 males and females aged 35 to 65 years recruiting from the phase I of Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) cohort study. The participants were drawn by a stratified cluster random sampling technique. The Bivariate and multinomial logistic regression analysis were conducted considering gender stratification to explore the association of ECG abnormalities with traditional cardiovascular risk factors. There was a significant association between minor and major ECG abnormalities and hypertension (HTN), type 2 diabetes (T2DM), smoking, and physical activity (p < 0.005). There was a significant trend, in both genders, for increasing major abnormalities as the number of CVD risk factors increased. But, only in women, the minor abnormalities increase in frequency as the number of CVD risk factors increased. The results of multinomial logistic regression showed that men with HTN [ARRR = 1.25, 95% CI 0.99, 1.57] and T2DM [ARRR = 1.31, 95% CI 0.99, 1.74] had the highest likelihood to have major abnormalities, although these are not statistically significant. For women, those with HTN had the highest likelihood to have major [ARRR = 1.36, 95% CI 1.13, 1.63] and minor [ARRR = 1.35, 95% CI 1.15, 1.58] abnormalities. Also, women aged > 60 years were more likely to have major [ARRR = 2.01, 95% CI 1.49, 2.74] and minor [ARRR = 1.59, 95% CI 1.20, 2.10] abnormalities compared to women aged < 45 years. Age and HTN were significantly associated with major and minor ECG abnormalities in women, and, on the other hand, HTN and T2DM were associated with major abnormalities in men. Taken together, these findings suggest that healthcare providers should advise preventive approaches to the asymptomatic adults with both major and minor electrocardiographic abnormalities that may predict cardiovascular risk.

Association of Three Novel Inflammatory Markers: Lymphocyte to HDL-C Ratio, High-Sensitivity C-Reactive Protein to HDL-C Ratio and High-Sensitivity C-Reactive Protein to Lymphocyte Ratio With Metabolic Syndrome.

We aimed to compare the association of three novel inflammatory indicators with metabolic syndrome (MetS) among Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort participants. According to the International Diabetes Federation (IDF) criteria, the cohort participants were divided into the MetS(+) and MetS(-) groups. The lymphocyte to high-density lipoprotein cholesterol (HDL-C) ratio (LHR), high-sensitivity C-reactive protein (hs-CRP) to HDL-C ratio (HCHR) and hs-CRP to lymphocyte ratio (HCLR) were calculated and were compared between the groups. Binary logistic regression (LR) analysis was performed to find the association of the indices with the presence of MetS among men and women. Receiver-operating characteristic (ROC) curve analysis was used to establish cut-off values in predicting MetS for men and women. p-Values <0.05 were considered as statistically significant. Among a total of 8890 participants (5500 MetS(-) and 3390 MetS(+)), LHR, HCHR and HCLR were significantly higher in the MetS(+) group than in MetS(-) group (p < 0.001). In LR analysis, after adjusting for multiple cofounders, LHR remained an independent factor for the presence of MetS among men (OR: 1.254; 95% CI: 1.202-1.308; p < 0.001) and women (OR: 1.393; 95% CI: 1.340-1.448; p < 0.001). HCHR also remained an independent factor for the presence of MetS only in women (OR: 1.058; 95% CI: 1.043-1.073; p < 0.001). ROC curve analysis showed that LHR had the higher AUC for predicting MetS in both men (AUC: 0.627; 95% CI: 0.611-0.643; p < 0.001) and women (AUC: 0.683; 95% CI: 0.670, 0.696; p < 0.001). This suggests that among both genders, the LHR as an inexpensive and easy-to-access marker has a better diagnostic performance and could be a promising alternative to the traditional expensive inflammatory markers such as hs-CRP for the evaluation of inflammation in patients with MetS.

The associations of oxidative stress and inflammatory markers with obesity in Iranian population: MASHAD cohort study

BackgroundLow-grade inflammation and stress oxidative condition play a role in the pathogenesis of obesity, and the serum levels of these markers, such as pro-oxidant-antioxidant balance (PAB), high-sensitivity C-reactive protein (hs-CRP), and uric acid may indicate obesity progression. In this study, we aimed to investigate the relationship between obesity with PAB, hs-CRP, and uric acid in the Iranian population.MethodsThis study was derived from the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study. A total of 7985 subjects aged 35 to 65 years were divided into three groups according to body mass index (BMI) as: normal, overweight and obese groups. Anthropometric indices and biochemical parameters such as PAB, superoxide dismutase type 1 (SOD1), hs-CRP, and uric acid were measured in all the participants. We evaluated the association of obesity with inflammatory factors by using multivariate regression analysis. Also, those participants with hypertension, an endocrine disorder, history of cardiovascular diseases and diabetes mellitus were excluded from the study.ResultsThere was a positive significant correlation between BMI and serum PAB, hs-CRP and uric acid (p < 0.001). While no statistically significant relation was observed between BMI and SOD1 (p = 0.85). Multivariate regression analysis showed that the risk of overweight and obesity increased 1.02 and 1.03-fold according to increase 10 units of PAB raise in comparison to reference group (normal weight) [(odds ratio (OR): 1.02, 95% CI (1.01–1.03)] and [OR: 1.03, 95% CI (1.01–1.04)], respectively). In addition, hs-CRP serum concentration was significantly associated with a high risk of obesity [(OR: 1.02; 95% CI (1.01–1.03)]. While the high levels of serum uric acid were associated with increased odds of overweight and obesity risk [OR: 1.4; CI (1.39–1.58) and OR: 1.76; CI (1.63–1.89), respectively].ConclusionsGenerally, we showed a significant association between BMI and serum PAB, hs-CRP values and uric acid levels, suggesting the role of these factors as risk stratification factors for obesity.

Uric acid is associated with type 2 diabetes: data mining approaches.

Several blood biomarkers have been related to the risk of type 2 diabetes mellitus (T2D); however, their predictive value has seldom been assessed using data mining algorithms. This cohort study was conducted on 9704 participants recruited from the Mashhad Stroke and Heart Atherosclerotic disorders (MASHAD) study from 2010 to 2020. Individuals who were not between the ages of 35 and 65 were excluded. Serum levels of biochemical factors such as creatinine (Cr), high-sensitivity C reactive protein (hs-CRP), Uric acid, alanine aminotransferase (ALT), aspartate aminotransferase (AST), direct and total bilirubin (BIL.D, BIL.T), lipid profile, besides body mass index (BMI), waist circumference (WC), blood pressure, and age were evaluated through Logistic Regression (LR) and Decision Tree (DT) methods to develop a predicting model for T2D. The comparison between diabetic and non-diabetic participants represented higher levels of triglyceride (TG), LDL, cholesterol, ALT, BIL.D, and Uric acid in diabetic cases (p-value < 0.05). The LR model indicated a significant association between TG, Uric acid, and hs-CRP, besides age, sex, WC, and blood pressure, hypertension and dyslipidemia history with T2D development. DT algorithm demonstrated dyslipidemia history as the most determining factor in T2D prediction, followed by age, hypertension history, Uric acid, and TG. There was a significant association between hypertension and dyslipidemia history, TG, Uric acid, and hs-CRP with T2D development, along with age, WC, and blood pressure through the LR and DT methods.

Predicting the 10-year incidence of dyslipidemia based on novel anthropometric indices, using data mining

BackgroundThe aim was to establish a 10-year dyslipidemia incidence model, investigating novel anthropometric indices using exploratory regression and data mining.MethodsThis data mining study was conducted on people who were diagnosed with dyslipidemia in phase 2 (n = 1097) of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study, who were compared with healthy people in this phase (n = 679). The association of dyslipidemia with several novel anthropometric indices including Conicity Index (C-Index), Body Roundness Index (BRI), Visceral Adiposity Index (VAI), Lipid Accumulation Product (LAP), Abdominal Volume Index (AVI), Weight-Adjusted-Waist Index (WWI), A Body Shape Index (ABSI), Body Mass Index (BMI), Body Adiposity Index (BAI) and Body Surface Area (BSA) was evaluated. Logistic Regression (LR) and Decision Tree (DT) analysis were utilized to evaluate the association. The accuracy, sensitivity, and specificity of DT were assessed through the performance of a Receiver Operating Characteristic (ROC) curve using R software.ResultsA total of 1776 subjects without dyslipidemia during phase 1 were followed up in phase 2 and enrolled into the current study. The AUC of models A and B were 0.69 and 0.63 among subjects with dyslipidemia, respectively. VAI has been identified as a significant predictor of dyslipidemias (OR: 2.81, (95% CI: 2.07, 3.81)) in all models. Moreover, the DT showed that VAI followed by BMI and LAP were the most critical variables in predicting dyslipidemia incidence.ConclusionsBased on the results, model A had an acceptable performance for predicting 10 years of dyslipidemia incidence. Furthermore, the VAI, BMI, and LAP were the principal anthropometric factors for predicting dyslipidemia incidence by LR and DT models.

The relationship between anthropometric indices and the presence of hypertension in an Iranian population sample using data mining algorithms.

Hypertension (HTN) is a common chronic condition associated with increased morbidity and mortality. Anthropometric indices of adiposity are known to be associated with a risk of HTN. The aim of this study was to identify the anthropometric indices that best associate with HTN in an Iranian population. 9704 individuals aged 35-65 years were recruited as part of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study. Demographic and anthropometric data of all participants were recorded. HTN was defined as a systolic blood pressure (SBP) ≥ 140 mmHg, and/ or a diastolic blood pressure (DBP) ≥ 90 mmHg on two subsequent measurements, or being treated with oral drug therapy for BP. Data mining methods including Logistic Regression (LR), Decision Tree (DT), and Bootstrap Forest (BF) were applied. Of 9704 participants, 3070 had HTN, and 6634 were normotensive. LR showed that body roundness index (BRI), body mass index (BMI) and visceral adiposity index (VAI) were significantly associated with HTN in both genders (P < 0.0001). BRI showed the greatest association with HTN (OR = 1.276, 95%CI = (1.224, 1.330)). For BMI we had OR = 1.063, 95%CI = (1.047, 1.080), for VAI we had OR = 1.029, 95%CI = (1.020, 1.038). An age < 47 years and BRI < 4.04 was associated with a 90% probability of being normotensive. The BF indicated that age, sex and BRI had the most important role in HTN. In summary, among anthropometric indices the most powerful indicator for discriminating hypertensive from normotensive patients was BRI.

Non-HDL cholesterol and long-term follow-up outcomes in patients with metabolic syndrome

BackgroundNon-high-density lipoprotein-cholesterol (non-HDL-C) has been identified as a potential biomarker for metabolic syndrome (MetS). However, its predictive capability for MetS varies among different ethnic groups, necessitating further investigation. This study aimed to assess the role of non-HDL-C in the early diagnosis of MetS in the Iranian population through a longitudinal study with a 10-year follow-up period.MethodsOur study enrolled 4684 individuals from the MASHAD (Mashhad Stroke and Heart Atherosclerotic Disorder) cohort who were followed for 10 years to examine the association between non-HDL-C and the incidence of MetS. Additionally, the contribution of individual MetS components to the overall burden was evaluated.ResultsA total of 1599 subjects developed MetS, while 3085 did not. Non-HDL-C levels ≥ 130 were associated with a 42% higher risk of developing MetS (relative risk (RR), 1.42; 95% confidence interval (CI), 1.25–1.62). Regarding MetS components, elevated waist circumference (WC) showed the strongest association with MetS incidence (RR, 2.32; 95% CI, 1.45–2.9), whereas triglyceride (TG) levels ≥ 150 mg/dL demonstrated the weakest association (RR, 1.23; 95% CI, 1.04–1.46). Additionally, higher HDL-C levels were reported to be 20% protective against the risk of MetS (RR, 0.8; 95% CI, 0.73–0.86). Moreover, fasting blood glucose (FBG) levels ≥ 100 mg/dL were not significantly linked to MetS burden, while systolic blood pressure (BP) levels ≥ 130 mmHg or diastolic BP levels ≥ 85 mmHg increased the risk of MetS incidence (RR, 1.25; 95% CI: 1.11–1.41).ConclusionsElevated non-HDL-C and increased WC serve as significant predictors of MetS in Iranians. Strategies targeting non-HDL-C levels and weight loss should be emphasized to mitigate the risk of MetS development.

A large population-based study on the prevalence of electrocardiographic abnormalities: A result of Mashhad stroke and heart atherosclerotic disorder cohort study.

Twelve-lead electrocardiogram (ECG) is a common and inexpensive tool for the diagnostic workup of patients with suspected cardiovascular disease, both in clinical and epidemiological settings. The present study was designed to evaluate ECG abnormalities in Mashhad population. ECGs were taken as part of MASHAD cohort study (phase1) and were coded according to the Minnesota coding criteria. Data were analyzed using SPSS. Total 9035 ECGs were available for final analysis including 3615 (40.0%) male and 5420 (60.0%) female. Among ECG abnormalities precordial Q wave, major T-wave abnormalities, inferior Q wave, sinus bradycardia, and left axis deviation were the most prevalent abnormalities. The frequency of precordial and inferior Q wave, inferior QS pattern, major and minor ST abnormalities, major and minor T abnormalities, Wolff-Parkinson-White and Brugada pattern, sinus bradycardia, sinus tachycardia, left axis deviation, ST elevation, and tall T wave were significantly different between two genders. Moreover, the frequency of Q wave in precordial and aVL leads, QS pattern in precordial and inferior leads, major and minor T-wave abnormalities, Wolff-Parkinson-White, atrial fibrillation, sinus bradycardia, left axis deviation, and ST elevation were significantly different in different age groups. A comparison of the heart rate, P-wave duration, and QRS duration between men and women indicated that there was a significant difference. Our finding indicated that the prevalence ECG abnormalities are different between men and women and also it varied in different age groups.

Association between the rs2241883 polymorphism of the fatty acid-binding protein-1 (FABP1) gene and obesity in a population of MASHAD study cohort.

The fatty acid-binding proteins (FABPs) gene polymorphisms are related to several metabolic properties. We investigated the association of SNPs rs2241883 of FABP 1 gene with obesity to evaluate the role of FABP1 gene in the pathogenesis of obesity in the population of MASHAD study cohort. In this cross-sectional study, 2731 individuals (1883 Obese and 848 nonobese) aged 35 to 65 years old, were enrolled from the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study cohort. DNA Quantitation was determined using the NanoDrop®-1000 instrument (NanoDrop-Technologies). The rs2241883 polymorphisms were genotyped by double ARMs PCR (double amplification refractory mutation system) reactions. Data analysis was carried out using SPSS 22 and a p < 0.05 was set for statistical significance. The results showed that after adjusting for confounding factors, subjects having the CC genotype for rs2241883 polymorphism were at a higher risk of BMI ≥ 30 mg/kg2 with OR of 1.79 (CI=1.05-3.07; p=0.03) and 1.76 (CI=1.04-2.99; p=0.04) comparing with reference group using codominant and dominant models, respectively. The results showed that CC genotype for rs2241883 polymorphism is related to an increased risk of the obesity in dominant and codominant models in a population of MASHAD study cohort.

Assessment of the Performances of Adaptive Neuro-Fuzzy Inference System and Two Statistical Methods for Diagnosing Coronary Artery Disease.

The accurate diagnosis of cardiac disease is vital in managing patients' health. Data mining and machine learning techniques play an important role in the diagnosis of heart disease. We aimed to examine the diagnostic performances of an adaptive neuro-fuzzy inference system (ANFIS) for predicting coronary artery disease and compare this with two statistical methods: flexible discriminant analysis (FDA) and logistic regression (LR). The data of this study is the result of descriptive-analytical research from the study of Mashhad. We used ANFIS, LR, and FDA to predict coronary artery disease. A total of 7385 subjects were recruited as part of the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) cohort study. The data set contained demographic, serum biochemical parameters, anthropometric, and many other variables. To evaluate the ability of trained ANFIS, LR, and FDA models to diagnose coronary artery disease, we used the Hold-Out method.For analyzing data, we used SPSS v25, R 4.0.4, and MATLAB 2018 software. The accuracy, sensitivity, specificity, Mean squared error (MSE) , and area under the roc curve (AUC) for ANFIS were 83.4%, 80%, 86%, 0.166 and 83.4%. The corresponding values based on the LR method were 72.4%, 74%, 70% , 0.175 and 81.5% and for the FDA method, these measurements were 77.7%, 74%, 81%, 0.223, and 77.6%, respectively. There was a significant difference between the accuracy of these three methods. The present findings showed that ANFIS was the most accurate method for diagnosing coronary artery disease compared with LR and FDA methods. Thus, it could be a helpful tool to aid medical decision-making for the diagnosis of coronary artery disease.

Prediction of type 2 diabetes mellitus using hematological factors based on machine learning approaches: a cohort study analysis

Type 2 Diabetes Mellitus (T2DM) is a significant public health problem globally. The diagnosis and management of diabetes are critical to reduce the diabetes complications including cardiovascular disease and cancer. This study was designed to assess the potential association between T2DM and routinely measured hematological parameters. This study was a subsample of 9000 adults aged 35–65 years recruited as part of Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort study. Machine learning techniques including logistic regression (LR), decision tree (DT) and bootstrap forest (BF) algorithms were applied to analyze data. All data analyses were performed using SPSS version 22 and SAS JMP Pro version 13 at a significant level of 0.05. Based on the performance indices, the BF model gave high accuracy, precision, specificity, and AUC. Previous studies suggested the positive relationship of triglyceride-glucose (TyG) index with T2DM, so we considered the association of TyG index with hematological factors. We found this association was aligned with their results regarding T2DM, except MCHC. The most effective factors in the BF model were age and WBC (white blood cell). The BF model represented a better performance to predict T2DM. Our model provides valuable information to predict T2DM like age and WBC.

Serum Anti-heat Shock Protein 27 Antibody Titers in Patients With Dyslipidemia: A Population-based Case-control Study

Background: Heat shock protein 27 (HSP27) is found in several cell types of adults, such as cardiomyocytes, and endothelial cells. It is expressed in response to different cellular stress conditions. HSP27 decreases the levels of reactive oxygen species (ROS) and dyslipidemia is closely associated with increased endothelial production of reactive oxygen species (ROS). Objective: Higher serum HSP27 antigen and anti-HSP27 antibodies have been reported in patients with unstable angina and myocardial infarction Methods: This population-based case-control study was conducted in 2018. We investigated serum anti-HSP27 antibody titers in all participants with dyslipidemia from the Mashhad stroke and heart atherosclerotic disorder (MASHAD) study (n=8141) and those who were healthy in terms of dyslipidemia (n=1637) using an in-house enzyme-linked immune sorbent assay (ELISA) in individuals with dyslipidemia. Findings: Anti-HSP27 titers were significantly lower in individuals with dyslipidemia compared to people without dyslipidemia (P=0.036). Conclusion: Our results revealed that the anti-HSP27 antibody titer was lower in the participants with dyslipidemia than in the negative group. However, there may be a confounding effect of drug therapy. In a subgroup of dyslipidemic subjects, we observed lower anti-HSP27 antibody titers in patients treated with some drugs (statins or corticosteroids, non-steroidal anti-inflammatory drugs [NSAIDs], or anti-diabetic and anti-hypertensive) compared to subjects untreated with these drugs.

Association of ANGPTL3 polymorphisms with high-density lipoprotein cholesterol uptake capacity in patients with cardiovascular disease.

IntroductionPrevious studies have shown the importance of angiopoietin‐like 3 (ANGPTL3) as a modulator of lipid profiles. Cholesterol uptake capacity (CUC) is one means for assessing high‐density lipoprotein (HDL) functionality. This study for the first time has investigated the relationship between genetic ANGPTL3 polymorphism and CUC in patients with cardiovascular disease.MethodsFive hundred three subjects comprising 350 healthy subjects and 153 individuals who developed a cardiovascular disease (CVD) event during follow‐up were recruited as part of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) cohort study. A modified CUC method was used to determine the CUC of serum samples. Applied amplification refractory mutation system PCR was performed for ANGPTL3 variants genotyping including: rs10789117, rs1748195, and rs11207997. Sanger sequencing was applied to confirm the genotypes.ResultsThe results showed that there was a significant relationship between the rs1748195 genotypes and HDL concentration in the CVD group (p = 0.02). Moreover, individuals with a GG genotype of the rs1748195 were associated with a lower risk of CVD (OR = 0.49, 95% CI = 0.24–0.98, p = 0.04) compared with CC genotype in the CUC ≤ 1.7 a.u subgroup. Moreover, the CT genotype of rs11207997 was associated with a lower risk of CVD (OR = 0.74, 95% CI = 0.41–1.3, p = 0.01) compared with CC genotype in CUC > 1.7 a.u subgroup.ConclusionThe results showed that the CT genotype of the rs11207997 variant was associated with a lower risk of incident CVD in patients with higher HDL functionality. As well, the rs1748195 gene variant may contribute to a reduced risk of CVD.