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Maryam Asgari, Masoud Mohammadi,
Volume 75, Issue 11 (2-2018)
Volume 75, Issue 11 (2-2018)
Abstract
Fateme Azizi Mayvan , Mehdi Jabbari Nooghabi , Ali Taghipour , Mohammad Taghi Shakeri , Mahsa Mokarram ,
Volume 76, Issue 7 (10-2018)
Volume 76, Issue 7 (10-2018)
Abstract
Background: Regarding the increased risk of developing type 2 diabetes in pre-diabetic people, identifying pre-diabetes and determining of its risk factors seems so necessary. In this study, it is aimed to compare ordinary logistic regression and robust logistic regression models in modeling pre-diabetes risk factors.
Methods: This is a cross-sectional study and conducted on 6460 people, over 30 years old, who have participated in the screening of diabetes plan in Mashhad city that it was done by Mashhad University of Medical Sciences from October to December 2010. According to the fasting blood sugar criteria, 5414 individuals were identified as healthy and 1046 individuals were identified as pre-diabetic. Age, gender, body mass index, systolic blood pressure, diastolic blood pressure and waist-to-hip ratio were measured for every participant. The data was entered into the Microsoft Excel 2013 (Microsoft Corp., Redmond, WA, USA) and then analysis of the data was done in R Project for Statistical Computing, Version R 3.1.2 (www.r-project.org). Ordinary logistic regression model was fitted on the data. The outliers were identified. Then Mallow, WBY and BY robust logistic regression models were fitted on the data. And then, the robust models were compared with each other and with ordinary logistic regression model according to goodness of fit and prediction ability using Pearson's chi-square and area under the receiver operating characteristic (ROC) curve respectively.
Results: Among the variables that were included in the ordinary logistic regression model and three robust logistic models, age, body mass index and systolic blood pressure were statistically significant (P< 0.01) but waist-to-hip ratio was not statistically significant (P> 0.1). There were 552 outliers with misclassification error in the ordinary logistic regression model. Pearson's chi-square value and area under the ROC curve value in the Mallow model were almost the same as for ordinary logistic regression model. But it was relatively higher in BY and WBY models.
Conclusion: Based on results of this study age, overweight and hypertension are risk factors of prediabetes. Also, WBY and BY models were better than ordinary logistic regression model, according to goodness of fit criteria and prediction ability.
Methods: This is a cross-sectional study and conducted on 6460 people, over 30 years old, who have participated in the screening of diabetes plan in Mashhad city that it was done by Mashhad University of Medical Sciences from October to December 2010. According to the fasting blood sugar criteria, 5414 individuals were identified as healthy and 1046 individuals were identified as pre-diabetic. Age, gender, body mass index, systolic blood pressure, diastolic blood pressure and waist-to-hip ratio were measured for every participant. The data was entered into the Microsoft Excel 2013 (Microsoft Corp., Redmond, WA, USA) and then analysis of the data was done in R Project for Statistical Computing, Version R 3.1.2 (www.r-project.org). Ordinary logistic regression model was fitted on the data. The outliers were identified. Then Mallow, WBY and BY robust logistic regression models were fitted on the data. And then, the robust models were compared with each other and with ordinary logistic regression model according to goodness of fit and prediction ability using Pearson's chi-square and area under the receiver operating characteristic (ROC) curve respectively.
Results: Among the variables that were included in the ordinary logistic regression model and three robust logistic models, age, body mass index and systolic blood pressure were statistically significant (P< 0.01) but waist-to-hip ratio was not statistically significant (P> 0.1). There were 552 outliers with misclassification error in the ordinary logistic regression model. Pearson's chi-square value and area under the ROC curve value in the Mallow model were almost the same as for ordinary logistic regression model. But it was relatively higher in BY and WBY models.
Conclusion: Based on results of this study age, overweight and hypertension are risk factors of prediabetes. Also, WBY and BY models were better than ordinary logistic regression model, according to goodness of fit criteria and prediction ability.
Fatemeh Bahadori , Zahra Sahebazzamani , Leila Zarei, Neda Valizadeh,
Volume 76, Issue 9 (12-2018)
Volume 76, Issue 9 (12-2018)
Abstract
Background: Gestational diabetes is one of the common causes of maternal and fetal complications. Due to fetal and maternal complications of diabetes, it is very important to reduce the prevalence of diabetes and its consequences. The relationship between vitamin D deficiency and type 2 diabetes has been reported. There is little information about the relationship between serum vitamin D levels and the risk of gestational diabetes mellitus (GDM). The aim of this study was to determine the relationship between the levels of vitamin D and gestational diabetes.
Methods: This case-control study was conducted in health centers of Urmia University of Medical Sciences in May 2015 until March 2016. A total of 100 pregnant women with gestational diabetes and 100 healthy pregnant women were entered into the study by nonrandom and available sampling. The level of vitamin D was measured and levels were divided into three levels. Vitamin D levels were considered less than 20 ng/ml, 20-30 ng/ml and more than 30 ng/ml as deficiency, insufficiency and sufficient, respectively. Exclusion criteria include pre-pregnancy glucose tolerance, history of medical disease, and supplementation with vitamin D.
Results: The mean age of women in the study group was 30.31±5 years and in the control group was 28.83±4.95 years (P=0.06). The vitamin D levels in GDM and control groups were 7.25±4.76 ng/ml and 11.93±16.12 ng/ml, which is lower in the gestational diabetes than the control group (P=0.01). The severe deficiency of vitamin D in the gestational diabetes group and in control group were 34% and 27% respectively (P<0.0001). There was a significant difference in mean fasting plasma glucose level between gestational diabetes group and healthy pregnant group (P<0.001). There was no relationship between vitamin D levels and body mass index of pregnant women (P=0.1).
Conclusion: In this study, the majority of patients had vitamin D deficiency and in the gestational diabetes group, vitamin D deficiency was significantly higher than the control group. The severe deficiency of vitamin D in the gestational diabetes group was higher than patients without gestational diabetes.
Methods: This case-control study was conducted in health centers of Urmia University of Medical Sciences in May 2015 until March 2016. A total of 100 pregnant women with gestational diabetes and 100 healthy pregnant women were entered into the study by nonrandom and available sampling. The level of vitamin D was measured and levels were divided into three levels. Vitamin D levels were considered less than 20 ng/ml, 20-30 ng/ml and more than 30 ng/ml as deficiency, insufficiency and sufficient, respectively. Exclusion criteria include pre-pregnancy glucose tolerance, history of medical disease, and supplementation with vitamin D.
Results: The mean age of women in the study group was 30.31±5 years and in the control group was 28.83±4.95 years (P=0.06). The vitamin D levels in GDM and control groups were 7.25±4.76 ng/ml and 11.93±16.12 ng/ml, which is lower in the gestational diabetes than the control group (P=0.01). The severe deficiency of vitamin D in the gestational diabetes group and in control group were 34% and 27% respectively (P<0.0001). There was a significant difference in mean fasting plasma glucose level between gestational diabetes group and healthy pregnant group (P<0.001). There was no relationship between vitamin D levels and body mass index of pregnant women (P=0.1).
Conclusion: In this study, the majority of patients had vitamin D deficiency and in the gestational diabetes group, vitamin D deficiency was significantly higher than the control group. The severe deficiency of vitamin D in the gestational diabetes group was higher than patients without gestational diabetes.
Rohollah Kalhor , Asghar Mortezagholi , Fatemeh Naji, Saeed Shahsavari, Mohammad Zakaria Kiaei ,
Volume 76, Issue 12 (3-2019)
Volume 76, Issue 12 (3-2019)
Abstract
Background: Diabetes mellitus has several complications. The Late diagnosis of diabetes in people leads to the spread of complications. Therefore, this study has been done to determine the possibility of predicting diabetes type 2 by using data mining techniques.
Methods: This is a descriptive-analytic study that was conducted as a cross-sectional study. The study population included people referring to health centers in Mohammadieh City in Qazvin Province, Iran, from April to June 2015 for screening for diabetes. The 5-step CRISP method was used to implement this study. Data were collected from March 2015 to June 2015. In this study, 1055 persons with complete information were included in the study. Of these, 159 were healthy and 896 were diabetic. A total of 11 characteristics and risk factors were examined, including the age, sex, systolic and diastolic blood pressure, family history of diabetes, BMI, height, weight, waistline, hip circumference and diagnosis. The results obtained by support vector machine (SVM), decision tree (DT) and the k-nearest neighbors algorithm (k-NN) were compared with each other. Data was analyzed using MATLAB® software, version 3.2 (Mathworks Inc., Natick, MA, USA).
Results: Data analysis showed that in all criteria, the best results were obtained by decision tree with accuracy (0.96) and precision (0.89). The k-NN methods were followed by accuracy (0.96) and precision (0.83) and support vector machine with accuracy (0.94) and precision (0.85). Also, in this study, decision tree model obtained the highest degree of class accuracy for both diabetes classes and healthy in the analysis of confusion matrix.
Conclusion: Based on the results, the decision tree represents the best results in the class of test samples which can be recommended as a model for predicting diabetes type 2 using risk factor data.
Methods: This is a descriptive-analytic study that was conducted as a cross-sectional study. The study population included people referring to health centers in Mohammadieh City in Qazvin Province, Iran, from April to June 2015 for screening for diabetes. The 5-step CRISP method was used to implement this study. Data were collected from March 2015 to June 2015. In this study, 1055 persons with complete information were included in the study. Of these, 159 were healthy and 896 were diabetic. A total of 11 characteristics and risk factors were examined, including the age, sex, systolic and diastolic blood pressure, family history of diabetes, BMI, height, weight, waistline, hip circumference and diagnosis. The results obtained by support vector machine (SVM), decision tree (DT) and the k-nearest neighbors algorithm (k-NN) were compared with each other. Data was analyzed using MATLAB® software, version 3.2 (Mathworks Inc., Natick, MA, USA).
Results: Data analysis showed that in all criteria, the best results were obtained by decision tree with accuracy (0.96) and precision (0.89). The k-NN methods were followed by accuracy (0.96) and precision (0.83) and support vector machine with accuracy (0.94) and precision (0.85). Also, in this study, decision tree model obtained the highest degree of class accuracy for both diabetes classes and healthy in the analysis of confusion matrix.
Conclusion: Based on the results, the decision tree represents the best results in the class of test samples which can be recommended as a model for predicting diabetes type 2 using risk factor data.
Mansour Rezaei , Fateme Rajati , Negin Fakhri ,
Volume 77, Issue 4 (7-2019)
Volume 77, Issue 4 (7-2019)
Abstract
Background: Gestational diabetes mellitus (GDM) is one of the most common medical complications in pregnancy, which is associated with many serious consequences for mother and her fetus. Body mass index (BMI) in pregnant women is considered as one of most effective factor for the incidence of GDM. The aim of this study was to determine the relationship between BMI at pregnant women in the early months of pregnancy and the incidence of GDM.
Methods: In this retrospective cohort study, the case of six hundred fifty-nine pregnant women who referred to health centers in Kermanshah City from September 2010 to September 2012 by convenience sampling method were selected and investigated. This study was sponsored by Kermanshah University of Medical Sciences. Height and weight were measured for each woman at the beginning of pregnancy and maternal body mass index (BMI) was calculated based on height and weight measurements. Then the pregnant women were divided into four groups based on BMI: thin (BMI less than 18.9 kg/m2), normal (BMI between 19 kg/m2 and 24.9 kg/m2), overweight (BMI between 25 kg/m2 and 29.9 kg/m2) and obese (BMI more than 30 kg/m2). Those women who had diabetes at the beginning of pregnancy were excluded from the study. GDM was considered as fasting blood glucose ≥92 between 26-30 weeks of gestation.
Results: The mean±SD age of pregnant women was 27.7±5.85 year and the mean of BMI was 24.4±4.0 kg/m2. The GDM was shown in 30.7% of women. Association between BMI and GDM were statistically significant (P<0.001). The risk of GDM onset was 1.24 times, for each unit increased in BMI, (P<0.001). The risk of GDM was significantly higher in overweight [OR=2.97, CI (2.01-4.39)] and obese [OR=16.89, CI (8.46-33.70)] women. Being underweight increased the risk of GDM onset up to 1.19 times, but not significant.
Conclusion: There is a significant relationship between maternal BMI in pregnant women at the beginning of pregnancy with GDM onset. Increased BMI is correlated with an increase in the incidence of GDM.
Methods: In this retrospective cohort study, the case of six hundred fifty-nine pregnant women who referred to health centers in Kermanshah City from September 2010 to September 2012 by convenience sampling method were selected and investigated. This study was sponsored by Kermanshah University of Medical Sciences. Height and weight were measured for each woman at the beginning of pregnancy and maternal body mass index (BMI) was calculated based on height and weight measurements. Then the pregnant women were divided into four groups based on BMI: thin (BMI less than 18.9 kg/m2), normal (BMI between 19 kg/m2 and 24.9 kg/m2), overweight (BMI between 25 kg/m2 and 29.9 kg/m2) and obese (BMI more than 30 kg/m2). Those women who had diabetes at the beginning of pregnancy were excluded from the study. GDM was considered as fasting blood glucose ≥92 between 26-30 weeks of gestation.
Results: The mean±SD age of pregnant women was 27.7±5.85 year and the mean of BMI was 24.4±4.0 kg/m2. The GDM was shown in 30.7% of women. Association between BMI and GDM were statistically significant (P<0.001). The risk of GDM onset was 1.24 times, for each unit increased in BMI, (P<0.001). The risk of GDM was significantly higher in overweight [OR=2.97, CI (2.01-4.39)] and obese [OR=16.89, CI (8.46-33.70)] women. Being underweight increased the risk of GDM onset up to 1.19 times, but not significant.
Conclusion: There is a significant relationship between maternal BMI in pregnant women at the beginning of pregnancy with GDM onset. Increased BMI is correlated with an increase in the incidence of GDM.
Hossein Tireh , Mohammad Taghi Shakeri , Sadegh Rasoulinezhad , Habibollah Esmaily , Razieh Yousefi ,
Volume 77, Issue 5 (8-2019)
Volume 77, Issue 5 (8-2019)
Abstract
Background: Diabetes mellitus as a chronic disease is the most common disease caused by metabolic disorders and it is one of the most important health issues all around the world. Nowadays, data mining methods are applied in different fields of sciences due to data mining methods capability. Therefore, in this study, we compared the efficiency of data mining methods in predicting type 2 diabetes.
Methods: In this cross-sectional study, the data of 7,000 participants in the Diabetes Screening Project in Samen, Mashhad City, Iran, were considered in 2016. There were 540 untreated diabetic patients. The Samen Project was included in the routine examinations of diabetes patients like blood glucose, eyes health, nephropathy, and legs health. So, in order to maintain balance, 600 healthy individuals were selected in a proportional volume sampling in this study. Therefore, the total sample size was 1140 people. In this study, people with diabetes aged over 30 years old were enrolled and participants with the previous history of type 2 diabetes, with normal blood glucose due to drug use or other issues at the time of the study, were excluded.
Results: All three models (Logistic regression, simple Bayesian and support vector machine models) had the same test accuracy (86%), however, in terms of area under the receiver operating characteristic (ROC) curve (AUC), logistic regression and simple Bayesian models had better performance (AUC=90% against AUC=88%). In the simple Bayesian model and logistic regression, body mass index (BMI) and age variables were the most important variables, while BMI and blood pressure variables were the most important factors in the support vector machine model.
Conclusion: According to the results, all three models had the same accuracy. In terms of area under the curve (AUC), logistic and simple Bayes models had better performance than the support vector machine model. Totally all three models had almost the same performance. Based on all three models, BMI was the most important variable.
Methods: In this cross-sectional study, the data of 7,000 participants in the Diabetes Screening Project in Samen, Mashhad City, Iran, were considered in 2016. There were 540 untreated diabetic patients. The Samen Project was included in the routine examinations of diabetes patients like blood glucose, eyes health, nephropathy, and legs health. So, in order to maintain balance, 600 healthy individuals were selected in a proportional volume sampling in this study. Therefore, the total sample size was 1140 people. In this study, people with diabetes aged over 30 years old were enrolled and participants with the previous history of type 2 diabetes, with normal blood glucose due to drug use or other issues at the time of the study, were excluded.
Results: All three models (Logistic regression, simple Bayesian and support vector machine models) had the same test accuracy (86%), however, in terms of area under the receiver operating characteristic (ROC) curve (AUC), logistic regression and simple Bayesian models had better performance (AUC=90% against AUC=88%). In the simple Bayesian model and logistic regression, body mass index (BMI) and age variables were the most important variables, while BMI and blood pressure variables were the most important factors in the support vector machine model.
Conclusion: According to the results, all three models had the same accuracy. In terms of area under the curve (AUC), logistic and simple Bayes models had better performance than the support vector machine model. Totally all three models had almost the same performance. Based on all three models, BMI was the most important variable.
Mansour Rezaei, Negin Fakhri , Fateme Rajati , Soodeh Shahsavari ,
Volume 77, Issue 6 (9-2019)
Volume 77, Issue 6 (9-2019)
Abstract
Background: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnancy, which is associated with serious complications. In the event of early diagnosis of this disease, some of the maternal and fetal complications can be prevented. The aim of this study was to early predict gestational diabetes mellitus by two statistical models including artificial neural network (ANN) and decision tree and also comparing these models in the diagnosis of GDM.
Methods: In this modeling study, among the cases of pregnant women who were monitored by health care centers of Kermanshah City, Iran, from 2010 to 2012, four hundred cases were selected, therefore the information in these cases was analyzed in this study. Demographic information, mother's maternal pregnancy rating, having diabetes at the beginning of pregnancy, fertility parameters and biochemical test results of mothers was collected from their records. Perceptron ANN and decision tree with CART algorithm models were fitted to the data and those performances were compared. According to the accuracy, sensitivity, specificity criteria and surface under the receiver operating characteristic (ROC) curve (AUC), the superior model was introduced.
Results: Following the fitting of an artificial neural network and decision tree models to data set, the following results were obtained. The accuracy, sensitivity, specificity and area under the ROC curve were calculated for both models. All of these values were more in the neural network model than the decision tree model. The accuracy criterion for these models was 0.83, 0.77, the sensitivity 0.62, 0.56 and specificity 0.95, 0.87, respectively. The surface under the ROC curve in ANN model was significantly higher than decision tree (0.79, 0.74, P=0.03).
Conclusion: In predicting and categorizing the presence and absence of gestational diabetes mellitus, the artificial neural network model had a higher accuracy, sensitivity, specificity, and surface under the receiver operating characteristic curve than the decision tree model. It can be concluded that the perceptron artificial neural network model has better predictions and closer to reality than the decision tree model.
Methods: In this modeling study, among the cases of pregnant women who were monitored by health care centers of Kermanshah City, Iran, from 2010 to 2012, four hundred cases were selected, therefore the information in these cases was analyzed in this study. Demographic information, mother's maternal pregnancy rating, having diabetes at the beginning of pregnancy, fertility parameters and biochemical test results of mothers was collected from their records. Perceptron ANN and decision tree with CART algorithm models were fitted to the data and those performances were compared. According to the accuracy, sensitivity, specificity criteria and surface under the receiver operating characteristic (ROC) curve (AUC), the superior model was introduced.
Results: Following the fitting of an artificial neural network and decision tree models to data set, the following results were obtained. The accuracy, sensitivity, specificity and area under the ROC curve were calculated for both models. All of these values were more in the neural network model than the decision tree model. The accuracy criterion for these models was 0.83, 0.77, the sensitivity 0.62, 0.56 and specificity 0.95, 0.87, respectively. The surface under the ROC curve in ANN model was significantly higher than decision tree (0.79, 0.74, P=0.03).
Conclusion: In predicting and categorizing the presence and absence of gestational diabetes mellitus, the artificial neural network model had a higher accuracy, sensitivity, specificity, and surface under the receiver operating characteristic curve than the decision tree model. It can be concluded that the perceptron artificial neural network model has better predictions and closer to reality than the decision tree model.
Pedram Ataee , Rezvan Yahiapour , Bahram Nikkhoo , Nadia Shakiba , Ebrahim Ghaderi , Rasoul Nasiri , Kambiz Eftekhari ,
Volume 77, Issue 6 (9-2019)
Volume 77, Issue 6 (9-2019)
Abstract
Background: Celiac disease is a chronic inflammation of small intestine which is caused by an increased permanent sensitivity to a protein named gluten. This protein is present in some cereals such as wheat, barley, and rye. The immunologic response to this protein can cause clinical symptoms in people with specific human leukocyte antigens (HLAs) (including HLADQ2 or HLADQ8). Most studies have reported an increased incidence of celiac disease in patients with diabetes mellitus type I. This study aimed to determine the prevalence of the celiac disease in patients with diabetes mellitus type I under the age of 18 years old.
Methods: This cross-sectional, analytic descriptive study was performed on forty children with diabetes mellitus type I in Sanandaj Diabetes Association (Kurdistan University of Medical Sciences), Iran, from September 2012 to September 2013. After obtaining consent from their parents, demographic data, including gender, age, family history of diabetes, duration of illness, symptoms of celiac disease, were recorded in the questionnaire. The measurement of the tissue transglutaminase (tTG) antibody and total immunoglobulin type A in the serum was necessary for the screening of celiac disease. Therefore in the laboratory, 5 ml of the venous blood sample was taken and then the serum levels of tTG antibody (from immunoglobulin type A) and total serum levels of this immunoglobulin were measured by the enzyme-linked immunosorbent assay (ELISA) method. Upper endoscopy with multiple biopsies from small intestine was performed in patients with positive serological screening. Finally, the disease was evaluated by histological finding.
Results: Forty children with diabetes mellitus type I included 19 boys (47.5%) and 21 girls (52.5%) were enrolled in the study. The mean age of these patients was 10.53±4.05. The prevalence of celiac disease was 7.5% in these individuals. In the subjects, there was no significant relationship between gastrointestinal symptoms and celiac disease.
Conclusion: In the present study, the prevalence of the celiac disease in type 1 diabetic patients was 7.5% which is higher than the normal population.
Methods: This cross-sectional, analytic descriptive study was performed on forty children with diabetes mellitus type I in Sanandaj Diabetes Association (Kurdistan University of Medical Sciences), Iran, from September 2012 to September 2013. After obtaining consent from their parents, demographic data, including gender, age, family history of diabetes, duration of illness, symptoms of celiac disease, were recorded in the questionnaire. The measurement of the tissue transglutaminase (tTG) antibody and total immunoglobulin type A in the serum was necessary for the screening of celiac disease. Therefore in the laboratory, 5 ml of the venous blood sample was taken and then the serum levels of tTG antibody (from immunoglobulin type A) and total serum levels of this immunoglobulin were measured by the enzyme-linked immunosorbent assay (ELISA) method. Upper endoscopy with multiple biopsies from small intestine was performed in patients with positive serological screening. Finally, the disease was evaluated by histological finding.
Results: Forty children with diabetes mellitus type I included 19 boys (47.5%) and 21 girls (52.5%) were enrolled in the study. The mean age of these patients was 10.53±4.05. The prevalence of celiac disease was 7.5% in these individuals. In the subjects, there was no significant relationship between gastrointestinal symptoms and celiac disease.
Conclusion: In the present study, the prevalence of the celiac disease in type 1 diabetic patients was 7.5% which is higher than the normal population.
Azim Adibmanesh , Narges Mohammad Taghvaei , Mehrnoosh Zakerkish , Hamid Yaghooti ,
Volume 77, Issue 12 (3-2020)
Volume 77, Issue 12 (3-2020)
Abstract
Background: Nitric oxide (NO) produced by endothelial NO synthase (eNOS) mediates a large range of processes, and abnormality in the production of NO has been implicated in diabetic complications including diabetic nephropathy (DN). G894T polymorphism in the eNOS gene has been shown to decreased activity the NO levels of plasma. The association between eNOS Glu298Asp gene polymorphism and DN risk is still controversial. The present study investigated the effect of eNOS gene G894T polymorphism on susceptibility to type 2 diabetes (T2D) and DN and measures of kidney function in a population with and without diabetes.
Methods: This case-control study was carried out at the diabetes specialist clinic of Golestan Hospital of Ahvaz Jundishapur University of Medical Sciences, Iran, from September 2016 to December 2017. The study comprised 132 patients with T2D (with and without nephropathy). They were compared to 66 normal subjects. The subjects were genotyped for the eNOS G894T polymorphism by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Blood glucose, HbA1c, BUN, creatinine and urinary albumin were evaluated by a biochemistry analyzer.
Results: Higher prevalence of the mutant T allele and homozygous TT genotypes and biochemical parameters) like FBS, TG, and BUN) were seen in T2D patients compared to healthy subjects. For T2DM, the odds ratios (ORs) for the TT genotype and the T allele carrier were 3.1 (P=0.0001) and 2.6 (P=0.0001), respectively. In contrast to the significant association between the eNOS G894T polymorphism and T2D, we could not find a significant correlation to the DN. For DN, the ORs for the TT genotype and the T allele carrier were 1.1 (P=0.76) and 0.8 (P=0.6). For decreased epidermal growth factor receptor (EGFR) below 60 ml/min/ 1.73 m2 in diabetic patients, the OR for TT was 0.8 (P=0.7).
Conclusion: Our results confirm that the risk of T allele and TT genotype of the eNOS G894T polymorphism were significantly associated with T2D, The TT genotype of this polymorphism also conferred the risk of developing T2D, but they were not correlated with DN and decreased eGFR.
Methods: This case-control study was carried out at the diabetes specialist clinic of Golestan Hospital of Ahvaz Jundishapur University of Medical Sciences, Iran, from September 2016 to December 2017. The study comprised 132 patients with T2D (with and without nephropathy). They were compared to 66 normal subjects. The subjects were genotyped for the eNOS G894T polymorphism by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Blood glucose, HbA1c, BUN, creatinine and urinary albumin were evaluated by a biochemistry analyzer.
Results: Higher prevalence of the mutant T allele and homozygous TT genotypes and biochemical parameters) like FBS, TG, and BUN) were seen in T2D patients compared to healthy subjects. For T2DM, the odds ratios (ORs) for the TT genotype and the T allele carrier were 3.1 (P=0.0001) and 2.6 (P=0.0001), respectively. In contrast to the significant association between the eNOS G894T polymorphism and T2D, we could not find a significant correlation to the DN. For DN, the ORs for the TT genotype and the T allele carrier were 1.1 (P=0.76) and 0.8 (P=0.6). For decreased epidermal growth factor receptor (EGFR) below 60 ml/min/ 1.73 m2 in diabetic patients, the OR for TT was 0.8 (P=0.7).
Conclusion: Our results confirm that the risk of T allele and TT genotype of the eNOS G894T polymorphism were significantly associated with T2D, The TT genotype of this polymorphism also conferred the risk of developing T2D, but they were not correlated with DN and decreased eGFR.
Mostafa Bahremand, Ehsan Zereshki, Behzad Karami Matin, Samira Mohammadi,
Volume 78, Issue 5 (8-2020)
Volume 78, Issue 5 (8-2020)
Abstract
Background: Coronary artery ectasia (CAE) is dilatation of an arterial segment to a diameter at least 1.5 times that of the adjacent normal coronary artery. The incidence of coronary artery ectasia is distinct in different countries that can be found in 1.2% to 5% of angiographic examinations.
Methods: This is a retrospective study that was conducted from September 2019 to February 2020 in Kermanshah University of Medical Sciences and the results were reported briefly. To obtain the desired articles, electronic searches were conducted in databases including the Scopus, PubMed, and Science Direct databases without time limited until October 2019. The keywords used were Coronary Artery Ectasia AND (Diabetes OR "Diabetes Mellitus"). This was done by two individuals separately and the final results were confirmed by a third person. Mixed method appraisal tool (MMAT) was used to evaluate the quality of studies. The structure of writing and the process of performing and reporting the study are based on the PRISMA checklist.
Methods: This is a retrospective study that was conducted from September 2019 to February 2020 in Kermanshah University of Medical Sciences and the results were reported briefly. To obtain the desired articles, electronic searches were conducted in databases including the Scopus, PubMed, and Science Direct databases without time limited until October 2019. The keywords used were Coronary Artery Ectasia AND (Diabetes OR "Diabetes Mellitus"). This was done by two individuals separately and the final results were confirmed by a third person. Mixed method appraisal tool (MMAT) was used to evaluate the quality of studies. The structure of writing and the process of performing and reporting the study are based on the PRISMA checklist.
|
Results: Based on the search strategy carried out at PubMed, Scopus and Science Direct databases, 106 studies were found, which resulted in 24 articles being analyzed based on inclusion and exclusion criteria of which three were conducted in China, 18 in Turkey and one in Sweden, Egypt, and France. Finally, 24 articles were analyzed and the results showed a direct and effective relationship between diabetes mellitus and CAE (OR=1.19, CI: 0.94, 1.51).
Conclusion: Based on these results, the risk of CAE in subjects with diabetes mellitus was 19% higher than in subjects without diabetes mellitus. |
Alireza Sarmadi, Ahmad Kachoei, Mostafa Vahedian, Enayatollah Noori , Mojdeh Bahadorzadeh, Amrollah Salimi , Mohammad Hossein Assi,
Volume 79, Issue 9 (12-2021)
Volume 79, Issue 9 (12-2021)
Abstract
Background: Cholecystectomy is one of the most common abdominal surgeries and its preferred method is laparoscopy. The difficulty of laparoscopic cholecystectomy in diabetic patients is not clear and the preferred method of cholecystectomy in these patients is still under controversy. Therefore, this study was performed to evaluate the difficulty of laparoscopic cholecystectomy in diabetic and non-diabetic patients.
Methods: This retrospective analytical study was performed in Shahid Beheshti Hospital and Forghani Educational and Medical Center from April 2019 to April 2020. Samples were easily selected and 86 people in two groups of diabetic and non-diabetic patients were included in the study. All patient records were reviewed based on inclusion and exclusion criteria for factors such as age, sex, diet, duration of surgery, bleeding, adhesions, and open surgery, and finally, diabetes as a risk factor. It was compared between the two groups. Data were analyzed in SPSS software version 22, an independent t-test was used to analyze quantitative data and the chi-square test was used to analyze qualitative data. In this study, a significance level of less than 0.05 was considered.
Results: Abdominal scar, palpable gallbladder and gallstone were not significantly different between the two groups (P=0.33). But the history of cholecystectomy attacks was significantly different between the two groups (P<0.05). Laboratory values were not significant (P>0.05) . Hard operations in diabetic patients were more than nondiabetic
patients and even two cases of open surgery were seen in the group of diabetic
patients, but there was no significant relationship (P=0.09). Intraoperative bleeding was
statistically significant between the two groups (P=0.02), But adhesion during the
operation was not related (P=0.38).
Conclusion: Finally, our study showed that diabetes can be a predictive risk factor for the difficulty of cholecystectomy.
Methods: This retrospective analytical study was performed in Shahid Beheshti Hospital and Forghani Educational and Medical Center from April 2019 to April 2020. Samples were easily selected and 86 people in two groups of diabetic and non-diabetic patients were included in the study. All patient records were reviewed based on inclusion and exclusion criteria for factors such as age, sex, diet, duration of surgery, bleeding, adhesions, and open surgery, and finally, diabetes as a risk factor. It was compared between the two groups. Data were analyzed in SPSS software version 22, an independent t-test was used to analyze quantitative data and the chi-square test was used to analyze qualitative data. In this study, a significance level of less than 0.05 was considered.
Results: Abdominal scar, palpable gallbladder and gallstone were not significantly different between the two groups (P=0.33). But the history of cholecystectomy attacks was significantly different between the two groups (P<0.05). Laboratory values were not significant (P>0.05) . Hard operations in diabetic patients were more than nondiabetic
patients and even two cases of open surgery were seen in the group of diabetic
patients, but there was no significant relationship (P=0.09). Intraoperative bleeding was
statistically significant between the two groups (P=0.02), But adhesion during the
operation was not related (P=0.38).
Conclusion: Finally, our study showed that diabetes can be a predictive risk factor for the difficulty of cholecystectomy.
Parisa Zakeri, Masoud Amini, Ashraf Aminorroaya, Fahimeh Haghighatdoost, Awat Feizi,
Volume 79, Issue 9 (12-2021)
Volume 79, Issue 9 (12-2021)
Abstract
Background: Examining the course of changes in predictive indicators of future diabetes, such as blood sugar in high-risk individuals including pre-diabetic patients, can provide valuable information about the incidence of diabetes in these individuals. This study aimed to classify people at risk (pre-diabetes) based on the course of changes in their blood sugar and blood lipid and to investigate the incidence of diabetes in these classes on a sample of patients who were referred to the Endocrine and Metabolism Research Center of Isfahan.
Methods: This cohort study was performed based on the information of the Isfahan Diabetes Prevention Plan (IDPs). This project was implemented from April 2004 to March 2018 in the clinics of the Endocrine and Metabolism Research Center of Isfahan. The subjects in this study include 1228 pre-diabetic patients who participated in this project. Demographic and clinical variables of patients including blood sugar and lipid-blood variables were obtained using a questionnaire and laboratory measurements. Also in this study, the number of clinical variables was recorded 3 times. Data analysis was performed using the latent class growth trees model in R software version v4. (R v4.1.0)
Methods: This cohort study was performed based on the information of the Isfahan Diabetes Prevention Plan (IDPs). This project was implemented from April 2004 to March 2018 in the clinics of the Endocrine and Metabolism Research Center of Isfahan. The subjects in this study include 1228 pre-diabetic patients who participated in this project. Demographic and clinical variables of patients including blood sugar and lipid-blood variables were obtained using a questionnaire and laboratory measurements. Also in this study, the number of clinical variables was recorded 3 times. Data analysis was performed using the latent class growth trees model in R software version v4. (R v4.1.0)
| Results: The mean (standard deviation) age of participants was 44 (6.86) years. Subjects were classified into two classes of low-risk impaired blood sugar (n=1165) and high-risk impaired blood sugar (n=63) based on the trend of changes in blood sugar levels. Blood sugar levels were reported in the first class (104.28) and the second class (132.41). Conclusion: In the present study, it was concluded that there is a significant relationship between the incidence of diabetes and the different classes formed based on the course of changes in blood sugar of at-risk individuals. Therefore, by classifying people at risk, the incidence of this disease can be predicted and thus prevented. Also,measures such as managing the blood sugar and lifestyle variables of pre-diabetic patients through nutrition counseling classes and regular periodic tests can be used to reduce the incidence of diabetes in the future is used in people with pre-diabetes who are at high risk for the disease. |
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Hossein Shirvani , Ebrahim Fasihi Ramandi ,
Volume 80, Issue 1 (4-2022)
Volume 80, Issue 1 (4-2022)
Abstract
Background: Type2 diabetes is a metabolic disease that is rapidly increasing in the world. GLUT4 and RBP4 are factors that play a role in glucose uptake. This study aimed to investigate the effect of moderate-intensity continuous training on RBP4 and GLUT4 gene expression of soleus muscle in STZ induced diabetic rats.
Methods: This experimental study was conducted between May and September 2016 at Baqiyatallah University of Medical Sciences. In this study, there were 48 8-week-old male Wistar rats (mean weight 250±20) that were randomly divided into four groups: basic control, 12-week control, diabetes, diabetes and moderate continuous training. Diabetes was induced by injection of streptozotocin solution. The training protocol consisted of continuous aerobic training for 12 weeks, five sessions per week in the form of running on a treadmill. After sampling, real-time PCR expression was used to measure gene expression. Statistical analysis was performed by SPSS software, version 22 (IBM SPSS, Armonk, NY, USA) and graphs were drawn using GraphPad Prism, version 8, (GraphPad Software, USA).
Results: According to the results, there was a significant increase in RBP4 in the diabetic group compared to other groups. compared to the two groups of diabetes and diabetes, along with moderate continuous training, RBP4 gene expression was less expressed in diabetic training. Regarding GLUT4, there was a significant difference between diabetes and diabetes groups with training. Also, the expression of the GLUT4 gene in the diabetic group with training was higher than the other groups. According to this study, it was shown that moderate-intensity continuous training somehow reduces the negative effects of diabetes on metabolism and health by activating various cellular and molecular pathways and mechanisms.
Methods: This experimental study was conducted between May and September 2016 at Baqiyatallah University of Medical Sciences. In this study, there were 48 8-week-old male Wistar rats (mean weight 250±20) that were randomly divided into four groups: basic control, 12-week control, diabetes, diabetes and moderate continuous training. Diabetes was induced by injection of streptozotocin solution. The training protocol consisted of continuous aerobic training for 12 weeks, five sessions per week in the form of running on a treadmill. After sampling, real-time PCR expression was used to measure gene expression. Statistical analysis was performed by SPSS software, version 22 (IBM SPSS, Armonk, NY, USA) and graphs were drawn using GraphPad Prism, version 8, (GraphPad Software, USA).
Results: According to the results, there was a significant increase in RBP4 in the diabetic group compared to other groups. compared to the two groups of diabetes and diabetes, along with moderate continuous training, RBP4 gene expression was less expressed in diabetic training. Regarding GLUT4, there was a significant difference between diabetes and diabetes groups with training. Also, the expression of the GLUT4 gene in the diabetic group with training was higher than the other groups. According to this study, it was shown that moderate-intensity continuous training somehow reduces the negative effects of diabetes on metabolism and health by activating various cellular and molecular pathways and mechanisms.
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Conclusion: the present study showed the effect of moderate-intensity continuous training on the expression of RBP4 and GLUT4 genes in soleus muscle which can be effective in glucose uptake. It was also shown that moderate-intensity continuous training can minimize the complications of diabetes by reducing RBP4 gene expression.
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Sasan Dogohar, Saber Soltani, Ali Jafarpour, Fatemeh Tavangar , Sara Akhavan Rezayat , Maryam Ghiasi, Maryam Nasimi,
Volume 80, Issue 1 (4-2022)
Volume 80, Issue 1 (4-2022)
Abstract
Background: Psoriasis is a chronic and recurrent inflammatory disease that involves skin, joints and different organ systems. It is associated with Multiple morbidities such as cardiovascular disorders, diabetes, hypertension, hyperlipidemia and chronic kidney disease (CKD). Due to the high importance of the association between psoriasis and CKD which results in major side effects the aim of this study was to evaluation of CKD and associated factors in Psoriasis patients at Razi Hospital, Tehran, Iran.
Methods: This retrospective study was conducted as a cross-sectional descriptive and analytical study to evaluate the frequency of CKD and associated factors in psoriatic patients admitted to the Razi Hospital whose last time of admission was from June 2018 to January 2019. According to the K/DOQI guideline, CKD is defined as the GFR<60 mL/min/1.73 m² during at least a period of three months. GFR was calculated based on the MDRD formula. The sample size was equal to 265. The hospital documents of inpatients who have been admitted to Razi Hospital wards or follow-up clinics during 2017-2019 were used for collecting information and data. This information has been extracted based on the initial checklist for data collection. Collected data has been analyzed and performed by using SPSS 25 software.
Results: The study found that 18 (6.8%) of psoriasis patients had CKD. Patients were in the age range of 3.5-92 years, the majority of them were in the age range of 18.65–79.7 years. 171 (64.5%) patients were male and 94 (35.5%) were female. 41 (15.5%) patients had diabetes, 94 (35.5%) had hyperlipidemia and 41 (15.5%) had hypertension. History of NSAID, Methotrexate, Cyclosporine, Acitretin, Infliximab, and Adalimumab medication use among 9 (3.4%), 205 (77.4%), 56 (21.1%), 147 (55.5%), 30 (11.3%), and 28 (10.6%) patients were observed, respectively. Also, 54 (20.4%) had a history of phototherapy. 217 (81.9%) of the psoriatic patients had CPP (Chronic Plaque Psoriasis) and 48 (18.1%) had PP (pustular Psoriasis) and finally, 21 (7.9%) of the patients had psoriatic arthritis.
Methods: This retrospective study was conducted as a cross-sectional descriptive and analytical study to evaluate the frequency of CKD and associated factors in psoriatic patients admitted to the Razi Hospital whose last time of admission was from June 2018 to January 2019. According to the K/DOQI guideline, CKD is defined as the GFR<60 mL/min/1.73 m² during at least a period of three months. GFR was calculated based on the MDRD formula. The sample size was equal to 265. The hospital documents of inpatients who have been admitted to Razi Hospital wards or follow-up clinics during 2017-2019 were used for collecting information and data. This information has been extracted based on the initial checklist for data collection. Collected data has been analyzed and performed by using SPSS 25 software.
Results: The study found that 18 (6.8%) of psoriasis patients had CKD. Patients were in the age range of 3.5-92 years, the majority of them were in the age range of 18.65–79.7 years. 171 (64.5%) patients were male and 94 (35.5%) were female. 41 (15.5%) patients had diabetes, 94 (35.5%) had hyperlipidemia and 41 (15.5%) had hypertension. History of NSAID, Methotrexate, Cyclosporine, Acitretin, Infliximab, and Adalimumab medication use among 9 (3.4%), 205 (77.4%), 56 (21.1%), 147 (55.5%), 30 (11.3%), and 28 (10.6%) patients were observed, respectively. Also, 54 (20.4%) had a history of phototherapy. 217 (81.9%) of the psoriatic patients had CPP (Chronic Plaque Psoriasis) and 48 (18.1%) had PP (pustular Psoriasis) and finally, 21 (7.9%) of the patients had psoriatic arthritis.
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Conclusion: The prevalence of CKD was shown to increase by age. The other correlated factors are diabetes, hypertension, and hyperlipidemia. On the other hand, there was not found any significant correlation between drugs (NSAIDs, Methotrexate, Cyclosporine, Acitretin, Infliximab, Adalimumab) and CKD prevalence. There was also no significant correlation between phototherapy, psoriasis type and psoriatic arthritis, duration of psoriasis and CKD prevalence.
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Seyed Mohammad Hassan Adel, Saad Fazeli, Fatemeh Jorfi , Hoda Mombeini, Homeira Rashidi,
Volume 80, Issue 3 (6-2022)
Volume 80, Issue 3 (6-2022)
Abstract
Background: Diabetes mellitus is associated with an increased risk of cardiovascular disease. The effects of add-in Sodium-glucose cotransporter 2 (SGLT2) inhibitors to standard statin treatments in acute coronary syndrome (ACS) patients remains controversial. The effects of the empagliflozin treatment after percutaneous coronary intervention (PCI) on the lipid profile of patients with type 2 diabetes mellitus (T2DM) have not been investigated yet. This study aimed to evaluate the efficacy of empagliflozin administration on lipid profile in diabetic patients with ACS after PCI.
Methods: This randomized, double-blind, placebo-controlled trial study was conducted from March until December 2020 on type 2 diabetes patients who underwent PCI and were referred to the Golestan and Imam Khomeini Hospitals. 93 patients (56 males and 37 females, mean age of 56.55 years old) were included. The patients were randomly assigned into two groups of receiving empagliflozin (10 mg, once daily) or a matching placebo, in addition to standard therapies for 6 months. The changes in metabolic parameters including lipid profile before and 6 months after interventions were assessed.
Methods: This randomized, double-blind, placebo-controlled trial study was conducted from March until December 2020 on type 2 diabetes patients who underwent PCI and were referred to the Golestan and Imam Khomeini Hospitals. 93 patients (56 males and 37 females, mean age of 56.55 years old) were included. The patients were randomly assigned into two groups of receiving empagliflozin (10 mg, once daily) or a matching placebo, in addition to standard therapies for 6 months. The changes in metabolic parameters including lipid profile before and 6 months after interventions were assessed.
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Results: After treatment in placebo group the level of LDL-C (median 0.90 mg/dl to 0.82, P=0.008) and HDL-C (median 0.40 mg/dl to 0.35, P=0.090) were decreased, while in the empagliflozin group the levels of LDL-C (median 0.87 mg/dl to 0.96, P=0.875) and HDL-C (median 0.38 mg/dl to 0.48), P=0.007) increased. Treatment with Empagliflozin and placebo had no significant effect on changing the levels of total cholesterol, TG and eGFR (P>0.05). The weight loss and FBS reduction in the empagliflozin group were significantly higher than placebo (P=0.001 and P=0.048, respectively).
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Conclusion: Our results showed that adding Empagliflozin to standard treatment compared with a placebo for 6 months significantly increased LDL-C and significantly increased HDL-C. Also, except for weight loss and FBS, Empagliflozin was not more effective in improving the metabolic parameters of diabetic patients after PCI compared with placebo, so it seems that the use of this drug in diabetic patients with ACS after PCI is not very cost-effective.
Hosein Shabani-Mirzaee , Zahra Haghshenas , Mohsen Vigeh, Armen Malekiantaghi, Kambiz Eftekhari,
Volume 80, Issue 5 (8-2022)
Volume 80, Issue 5 (8-2022)
Abstract
Background: Due to the chronic nature of diabetes, children with type 1 diabetes are prone to a number of long-term complications. One of the most important complications of this disease is cardiovascular involvement due to atherosclerosis, which is directly related to the control of blood lipids. The use of probiotics may be effective in the process of complications in these patients by affecting fat metabolism. The aim of this study was to evaluate the effect of oral probiotics on lipid profiles in children with type 1 diabetes.
Methods: This study was conducted at Bahrami Children's Hospital from May 2018 to May 2019. In this single-blind randomized controlled clinical trial, 52 children with type 1 diabetes (aged 2 to 16 years) were studied. We created two groups of 26 individuals. The inclusion criteria were determined as follows: Proof of T1DM by history and information of children’s medical record. Also, the Exclusion criteria were determined in this way: Patients consuming probiotics in the last 4 weeks, gastrointestinal infections in the last 2 weeks, and presence of chronic underlying intestinal diseases. The probiotic group received, in addition to insulin therapy, a daily probiotic capsule for 90 days. The control group received only routine insulin therapy. Blood samples were taken to measure lipid profiles at the beginning and end of the trial.
Results: A total of 52 patients were included. The mean age of children was 9.3±2.9 (4 to 14 years). The mean age in the probiotic and control groups was 9.6±3.5 and 9.4±3.0 respectively. The results of this study showed that HDL-C was increased in the probiotic group compared to the control group, although it was not statistically significant (P>0.05). Also, changes in total cholesterol, LDL-C, and triglyceride were not statistically significant.
Methods: This study was conducted at Bahrami Children's Hospital from May 2018 to May 2019. In this single-blind randomized controlled clinical trial, 52 children with type 1 diabetes (aged 2 to 16 years) were studied. We created two groups of 26 individuals. The inclusion criteria were determined as follows: Proof of T1DM by history and information of children’s medical record. Also, the Exclusion criteria were determined in this way: Patients consuming probiotics in the last 4 weeks, gastrointestinal infections in the last 2 weeks, and presence of chronic underlying intestinal diseases. The probiotic group received, in addition to insulin therapy, a daily probiotic capsule for 90 days. The control group received only routine insulin therapy. Blood samples were taken to measure lipid profiles at the beginning and end of the trial.
Results: A total of 52 patients were included. The mean age of children was 9.3±2.9 (4 to 14 years). The mean age in the probiotic and control groups was 9.6±3.5 and 9.4±3.0 respectively. The results of this study showed that HDL-C was increased in the probiotic group compared to the control group, although it was not statistically significant (P>0.05). Also, changes in total cholesterol, LDL-C, and triglyceride were not statistically significant.
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Conclusion: In this study, the use of oral probiotics for 90 days in children with type 1 diabetes did not have a significant effect on blood lipid profiles compared to the control group.
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Mahmoud Parham, Davoud Oulad Dameshghi , Hossein Saghafi, Azam Sarbandy Farahani, Saeed Karimi Matloub, Rasool Karimi Matloub,
Volume 80, Issue 8 (11-2022)
Volume 80, Issue 8 (11-2022)
Abstract
Background: Vitamin B12 deficiency is one of the most well-known disorders due to long-term use of metformin due to interference with its absorption.
Methods: This double-blind randomized trial was conducted from June to October 2016 at Shahid Beheshti Hospital in Qom on 60 patients in the age group of 30 to 60 years with a history of type 2 diabetes for one to two years and taking metformin in the amount of one to two grams. Patients were divided into two groups of 30 people. The intervention group received metformin with 1 gram of calcium carbonate daily, and the control group received metformin without calcium. Each of the patients in the intervention group was given 200 calcium carbonate tablets. Vitamin B12 levels of the patients in both groups were measured before the start of the intervention, and they were evaluated in terms of neuropathy according to the Michigan questionnaire. Vitamin B12 of patients and neuropathy in two groups were measured before the intervention and after three months.
Results: There was a difference between the two groups in terms of gender, and no significant difference was observed between the mean ages in the two groups. The mean level of vitamin B12 before receiving calcium in group A (intervention) was lower than group B (control) (P=0.036) and after receiving calcium, the level of vitamin B12 in the intervention group increased (P=0.002). In the control group, the level of vitamin B12 decreased (P=0.030). (P=0.006), and in the control group there was no significant difference in the examination of neuropathy (P=0.2).
Methods: This double-blind randomized trial was conducted from June to October 2016 at Shahid Beheshti Hospital in Qom on 60 patients in the age group of 30 to 60 years with a history of type 2 diabetes for one to two years and taking metformin in the amount of one to two grams. Patients were divided into two groups of 30 people. The intervention group received metformin with 1 gram of calcium carbonate daily, and the control group received metformin without calcium. Each of the patients in the intervention group was given 200 calcium carbonate tablets. Vitamin B12 levels of the patients in both groups were measured before the start of the intervention, and they were evaluated in terms of neuropathy according to the Michigan questionnaire. Vitamin B12 of patients and neuropathy in two groups were measured before the intervention and after three months.
Results: There was a difference between the two groups in terms of gender, and no significant difference was observed between the mean ages in the two groups. The mean level of vitamin B12 before receiving calcium in group A (intervention) was lower than group B (control) (P=0.036) and after receiving calcium, the level of vitamin B12 in the intervention group increased (P=0.002). In the control group, the level of vitamin B12 decreased (P=0.030). (P=0.006), and in the control group there was no significant difference in the examination of neuropathy (P=0.2).
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Conclusion: Oral calcium daily intake increases vitamin B12 levels in patients with type 2 diabetes and calcium may be able to moderate the decrease in serum vitamin B12 levels induced by metformin in patients with type 2 diabetes.
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Hassan Boskabadi , Nafiseh Pourbadakhshan, Maryam Zakerihamidi,
Volume 80, Issue 10 (1-2023)
Volume 80, Issue 10 (1-2023)
Abstract
Background: Maternal diseases such as diabetes, hypertension, preeclampsia, hypothyroidism and epilepsy in pregnancy are associated with fetal and neonatal complications. The aim of this study was to compare the prognosis of neonates in maternal diseases.
Methods: This study was a cross-sectional study. The present study was performed on 600 preterm infants with mothers with diabetes, hypertension, preeclampsia, hypothyroidism and epilepsy. This study was done in Ghaem Hospital of Mashhad from March 2015 to April 2021 with available sampling. The data collection tool was a researcher-made checklist including infant (gestational age, Apgar score of the first minute, Apgar score of the fifth minute) and maternal (mode of delivery, prenatal care, premature rupture of the membranes) characteristics. Neonatal prognosis was compared at birth. All clinical and diagnostic examinations of newborns were performed by a neonatologist. Neonatal and maternal data in the group of newborns with normal mothers and newborns with maternal diseases were analyzed by Kolmogorov-Smirnov and Chi-square tests. The significance level was considered p≤0.05 in all cases.
Methods: This study was a cross-sectional study. The present study was performed on 600 preterm infants with mothers with diabetes, hypertension, preeclampsia, hypothyroidism and epilepsy. This study was done in Ghaem Hospital of Mashhad from March 2015 to April 2021 with available sampling. The data collection tool was a researcher-made checklist including infant (gestational age, Apgar score of the first minute, Apgar score of the fifth minute) and maternal (mode of delivery, prenatal care, premature rupture of the membranes) characteristics. Neonatal prognosis was compared at birth. All clinical and diagnostic examinations of newborns were performed by a neonatologist. Neonatal and maternal data in the group of newborns with normal mothers and newborns with maternal diseases were analyzed by Kolmogorov-Smirnov and Chi-square tests. The significance level was considered p≤0.05 in all cases.
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Results: The results show that 161 newborns (28.90%) had normal mothers, 89 newborns (15.98%) had diabetic mothers, 117 newborns (21.01%) had hypertensive mothers, and 50 newborns (8.98%) had hypothyroid mothers. One hundred tweny newborns (21.72%) had mothers with preeclampsia, 19 newborns (3.41%) had mothers with epilepsy. Newborns with mothers with epilepsy had the lowest Apgar score of the first minute and the lowest gestational age and newborns with mothers with diabetes had the lowest Apgar score of the fifth minute. Mothers with hypothyroidism had the highest rate of premature rupture of the membranes and mothers with hypertension and preeclampsia had the highest incidence of cesarean section.
Conclusion: Maternal diseases including diabetes, hypertension, preeclampsia, hypothyroidism and epilepsy affect the prognosis of neonates in terms of the severity of prematurity, premature rupture of the membranes, type of delivery, Apgar scores of the first and fifth minutes. Therefore, proper control and treatment of these diseases may improve neonatal prognosis. |
Negar Heidari , Fatemeh Rajati , Mojgan Rajati, Paria Heidari,
Volume 81, Issue 11 (1-2024)
Volume 81, Issue 11 (1-2024)
Abstract
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Elena Lak , Eskandar Hajiani, Jalal Sayyah , Zeynab Hosseinpour , Alireza Sedaghat,
Volume 81, Issue 11 (1-2024)
Volume 81, Issue 11 (1-2024)
Abstract
Background: Diabetes is known to be linked with a high risk of liver stiffness in non-alcoholic fatty liver patients. Previous studies have faced challenges in examining the association between prediabetes and liver stiffness. This study aimed to compare liver fibrosis in diabetes and prediabetes patients.
Methods: This cross-sectional descriptive study was conducted on patients with diabetes and prediabetes who were referred to Imam Khomeini Hospital in Ahvaz from March 2022 to March 2023. The study aimed to clear the relationship between liver stiffness and age, gender, BMI, AST, ALT, ALKP, Bilirubin, and the type of treatment. The normality of quantitative variables was checked using the Kolmogorov-Smirnov test. The chi-square test examined two qualitative variables with more than two levels.
Methods: This cross-sectional descriptive study was conducted on patients with diabetes and prediabetes who were referred to Imam Khomeini Hospital in Ahvaz from March 2022 to March 2023. The study aimed to clear the relationship between liver stiffness and age, gender, BMI, AST, ALT, ALKP, Bilirubin, and the type of treatment. The normality of quantitative variables was checked using the Kolmogorov-Smirnov test. The chi-square test examined two qualitative variables with more than two levels.
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Results: Out of the total participants, 53 people (63.9%) had diabetes, while 30 people (36.1%) had prediabetes. There was a significant difference between the mean severity of liver fibrosis in diabetic and pre-diabetic patients (P=0.014). The frequency of liver stiffness in all levels except in the group with mild or no fibrosis (F0-F1) was higher in diabetic than pre-diabetic patients. In both diabetes and prediabetes groups, there was no significant relationship between gender, age, BMI, ALT, and ALKP with liver fibrosis. However, there was a significant direct relationship between HbA1C% and liver fibrosis (P≥0.003) in both groups. In diabetic patients, a significant relationship between FBS and liver fibrosis was observed (P=0.001). In pre-diabetic patients, significant direct relationship was seen between the severity of liver fibrosis and AST levels (P=0.026).
Conclusion: Diabetic patients showed a higher severity of liver fibrosis compared to pre-diabetic patients. No statistically significant relationship was seen between liver fibrosis and age, sex, body mass index, ALT, and ALKP in both groups. Additionally, both diabetes and prediabetes groups showed significant relationship between liver fibrosis and HbA1C (P≥0.003). Prediabetes was also found to be associated with an elevated risk of liver fibrosis. |
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