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Showing 29 results for Diabetes Mellitus
Khalili D, Hadaegh F, Tohidi M, Fahimfar N, Eskandari F, Azizi F,
Volume 67, Issue 11 (2-2010)
Volume 67, Issue 11 (2-2010)
Abstract
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Background: Diabetes and dysglycemia have a high prevalence in
Iranian population but the information about their impact on the cardiovascular
disease (CVD) risk is scarce in this population. This study aimed
to determine the risk of CVD according to glucose tolerance status.
Methods: We ascertained cases with incident CVD in a
population of 1752 men and 2273 women, 40 years old and over and free of CVD at the
beginning of study, during a follow up with a median of 7.6 years. To
calculate hazard ratio (HR) for CVD, we controlled traditional risk factors, including
age, body mass index, waist, total cholesterol, HDL-cholesterol, triglycerides,
systolic blood pressure, diastolic blood pressure, education, smoking,
hypertension medication, lipid lowering medication and family history of
premature CVD and diabetes.
Results: Cardiovascular events
occurred in 197 men and 143 women. Its incidence density was 11.8 per 1000 person-years
(95%
confidence interval: 10.6 to 13.1) totally. Multiple adjusted HR in women with
known diabetes was 3.88 (95%CI: 2.40 to 6.27) and with newly diagnosed was 2.34 (95%CI: 1.39 to 3.95) and the
corresponding values for men were 1.72 (95%CI: 1.00- 2.95) and 1.52 (95%CI: 1.01- 2.31) respectively. Impaired fasting glucose and impaired
glucose tolerance increased 56% the risk of CVD in women (HR:
1.56 with 95% CI, 1.00 to 2.45), just in
the age adjusted model.
Conclusion: All diabetic patients should receive primary
prevention for CVD
intensively, regardless of whether they are newly diagnosed or are known cases
specially, females who have abnormal glucose metabolism.
Parisa Hasanein, Siamak Shahidi,
Volume 68, Issue 1 (4-2010)
Volume 68, Issue 1 (4-2010)
Abstract
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Background: Ascorbic
acid improves cognitive impairments in several experimental models. Diabetes
causes learning and memory deficits. In this study we hypothesized that chronic
treatment with ascorbic acid (100mg/kg, p.o) would affect on the passive avoidance
learning (PAL) and memory in control and streptozocin-induced
diabetic rats.
Methods: Diabetes was induced by a single i.p. injection of STZ (60mg/kg). The
rats were considered diabetic if plasma glucose levels exceeded 250mg/dl on three
days after STZ injection. Treatment was begun at the onset of
hyperglycemia. PAL was assessed 30 days later. Retention test was done 24 h after
training. At the end, animals were weighted and blood samples were drawn for
plasma glucose measurement.
Results: Diabetes caused impairment in acquisition and
retrieval processes of PAL and memory in rats. Ascorbic acid treatment improved
learning and memory in control rats and reversed learning and memory deficits
in diabetic rats. Ascorbic acid administration also improved the body weight
loss and hyperglycemia of diabetics. Hypoglycemic and antioxidant properties of
the vitamin may be involved in the memory improving effects of such treatment.
Conclusion: These results show that ascorbic acid administration
to rats for 30
days from onset of diabetes alleviated the negative influence of diabetes on
learning and memory. Comparing with other nootropic drugs, vitamins have fewer
side effects. Therefore, this regimen may provide a new potential alternative
for prevention of the impaired cognitive functions associated with diabetes
after confirming by clinical trials.
Etaati Z, Moazzami Godarzi R, Kalhori F, Sobhani Sa, Solati M, Alavi A, Tashnizi Sh, Naderi N,
Volume 70, Issue 1 (4-2012)
Volume 70, Issue 1 (4-2012)
Abstract
Background: Diabetes mellitus (DM) is a group of metabolic disorders such as DM I, DM II, secondary causes of DM and gestational diabetes mellitus characterized by hyperglycemic phonotype. The etiology of gestational diabetes mellitus is unknown. Recent studies address the chronic activity of immune system against infections (not autoimmunity) as an important cause of gestational diabetes mellitus. This study aimed to compare T-helper cells 1 and 2 cytokines and associated antibodies in patients with gestational diabetes mellitus and normal pregnant women.
Methods: This cross-sectional study was performed on 45 female patients with GDM and 45 healthy pregnant women in Bandar Abbas, Iran, from 2008- 2009. The exclusion criteria were presence of any infectious diseases or autoimmune disorders such as SLE or RA. Present and past medical histories were taken from the participants thorough physical examination. Blood samples (10 mL) were drawn and sent to laboratory for measuring serum IgE, IgG1, IgG2, IgG3, IgG4, interleukin-10 (IL-10), interleukin-12 (IL-12), transforming growth factor-beta (TGF1), and interferon-gamma (IFN) measurements. T-test and Kolmogorov-Smirnov test were used for data analysis.
Results: The mean age of the patients with GDM and healthy pregnant women was 32.5 and 27.9 yrs, respectively. T-helper 1 and 2 associated antibodies and cytokines had no significant differences between the case and control groups.
Conclusion: The changes in T-helper 1 and 2 associated antibodies and cytokines are not associated with gestational diabetes mellitus and could not be considered as a predictor for gestational diabetes mellitus.
Biranvand E, Abediankenari S, Khalilian A, Biranvand B,
Volume 70, Issue 5 (8-2012)
Volume 70, Issue 5 (8-2012)
Abstract
Background: Tuberculosis is one of the most important diseases with annually 8 million new cases worldwide. The purpose of this study was to investigate the risk factors for tuberculosis (TB) infection.
Methods: In this descriptive study performed in Health center of Maznadaran province during 2010-2011, 183 patients with pulmonary and extrapulmonary TB infection were recruited. After measuring fasting blood sugar, and human immunodeficiency virus (HIV) antibodies, history of smoking was taken by using a questionnaire.
Results: The mean age of the participants was 46.8±19.8 years. The most common risk factor was diabetes and the lowest was HIV infection. Moreover, the prevalence of diabetes in women compared with that of men (OR=0.19, 95% CI=0.07±0.46) and smoking in men compared with women (OR=12.4, 95% CI=2.8±54.4, P<0.05) had statistically significant differences (P<0.05).
Conclusion: The results of this research show that diabetes and smoking could be risk factors for tuberculosis infection. It is concluded that, in case of respiratory symptoms in patients with diabetes and smoking, tuberculosis can be considered as an important differential diagnosis.
Sabeti M, Naser Moghadasi A, Aloosh M, Paknejad Sm, Toghae M,
Volume 70, Issue 7 (10-2012)
Volume 70, Issue 7 (10-2012)
Abstract
Background: Finding an acute brain lesion by diffusion-weighted (DW) MRI upon an episode of transient ischemic attack (TIA) is a predictor of imminent stroke in the near future. Therefore, exploring risk factors associated with lesions in DW-MRI of the brain is important in adopting an approach to TIA management. In the current study, we tried to determine the risk factors associated with lesions in DW-MRI of the brain in patients experiencing TIA episodes.
Methods: Fifty patients with TIA were recruited consecutively in Sina Hospital, Tehran, Iran, over a 6-month period between July 2008 and January 2009. All of the patients underwent a complete neurological examination and laboratory tests. Brain DW-MRIs were performed for all the patients within 72 hours of a TIA episode.
Results: DW-MRI revealed an acute lesion in 16% of the participants. There was a significant correlation between presence of an acute lesion in DW-MRI and TIA duration, history of diabetes mellitus and presence of unilateral facial palsy (P=0.0003, P=0.02 and P=0.008, respectively). Other variables such as age, hypertension, hyperlipidemia, past history of TIA, headache, vertigo, and sensory or visual disturbances had no significant relation with the presence of an acute lesion in DW-MRI.
Conclusion: Duration of TIA, presence of diabetes mellitus and unilateral facial palsy are risk factors for an acute lesion in DW-MRI, meaning that patients with such risk factors are at risk for stroke in the near future.
Davari S, Talaei Sa, Soltani M, Alaei H, Salami M,
Volume 70, Issue 9 (12-2012)
Volume 70, Issue 9 (12-2012)
Abstract
Background: Diabetes mellitus affects numerous intracellular metabolic processes, which are reflected by changes in the concentration of some plasma constituents. Particularly, the disease may indirectly undermine some functions of the nervous system including learning and memory through altering oxidative stress status. On the other hand, probiotics can enhance the antioxidant capacity. This study was designed to evaluate the effects of probiotics on spatial memory, maze learning and indices of oxidative stress in diabetic rats.
Methods: In this experimental study, 40 male Wistar rats were randomly allocated to 4 groups (n=10 for each): Control (CO), Control probiotic (CP), Control diabetic (DC), and Diabetic probiotic (DP). The probiotic supplement, including Lactobacillus acidophilus, Lactobacillus fermentum, Bifidobacterium lactis (334 mg of each with a CFU of ~1010), was administered through drinking water every 12 hours for 8 weeks. Using morris water maze (MWM), spatial learning and memory were evaluated. Serum insulin and oxidative stress indices, including superoxide dismutase (SOD) and 8-hydroxy-2'-deoxyguanosine (8-OHdG), were measured by standard laboratory kits.
Results: Oral administration of probiotics improved impairment of spatial learning (P=0.008) and consolidated memory (P=0.01) in the rats. Moreover, probiotic treatment increased serum insulin (P<0.0001) and serum superoxide dismutase activity (P=0.007) while it decreased their blood glucose (P=0.006) and 8-OHdG (P<0.0001).
Conclusion: Probiotic supplementation reversed the serum concentrations of insulin and glucose along with an increase in antioxidant capacity in diabetic rats. It also improved spatial learning and memory in the animals. Relevancy of the metabolic changes and behavioral functions need to be further studied.
Hossein Fakhrzadeh , Farshad Sharifi , Neda Mehrdad , Fatemeh Jafaraghaeii , Zohreh Badamchizadeh , Neda Nazari ,
Volume 71, Issue 7 (10-2013)
Volume 71, Issue 7 (10-2013)
Abstract
Background: The aim of this study was to assess the association of serum adiponectin and a set of traditional cardiovascular risk factors with carotid artery intimal-medial thickness (CIMT) and coronary artery calcium score (CACS), as markers of subclinical atherosclerosis in subjects with early type 2 diabetes mellitus.
Methods: Carotid artery intima- media thickness (measured by B-mode ultrsonography), coronary artery calcium score (determined by high resolution computed tomography), serum adiponectin, Fasting blood sugar, serum lipids, body mass index (BMI), systolic blood pressure, diastolic blood pressure and mean arterial pressure were measured in 123 asymptomatic newly diagnosed cases of type 2 diabetes mellituss and 152 age and sex matched healthy control subjects.
Results: Serum adiponectin and lipids were significantly lower in those with type 2 diabetes mellitus (P<0.01). Left, right and mean carotid artery intima- media thickness, coronary artery calcium score, fasting blood sugar, systolic blood pressure, diastolic blood pressure and mean arterial pressure were significantly higher among diabetic patients compared to healthy controls (P<0.05). Mean carotid artery intima- media thickness was positively and independently related to age (P<0.001) and triglyceride (P=0.01) in diabetic group. Coronary artery calcium score was associated positively with age (P=0.004) and inversely with high density lipoprotein (HDL) cholesterol (P=0.002) among diabetics.
Conclusion: Although adiponectin was lower in diabetics compared to controls, it had no significant association with carotid artery intima- media thickness and coronary artery calcium score as markers of subclinical atherosclerosis. In patients with type 2 diabetes in addition to age, serum triglyceride levels are correlated with carotid artery intima- media thickness, while HDL cholesterol is inversely correlated with coronary artery calcium score.
Fariba Jafari , Mohammad-Ali Nilforooshzade , Samane Porajam , Motahar Heidari-Beni ,
Volume 72, Issue 6 (9-2014)
Volume 72, Issue 6 (9-2014)
Abstract
Background: Insulin resistant is important risk factors of diabetes and leads to development of chronic diseases such as diabetes and cardiovascular disease. Recent studies showed association between androgenic alopecia and insulin resistant. However, findings are controversial. Alopecia in women is a common heritable hair loss in central part of head. Aim of this study was investigation of androgenic alopecia distribution in type II diabetes and healthy women and hypothesis testing of relationship between diabetes and androgenic alopecia. Methods: This is a case-control study. Case and control groups were selected from type II diabetes and healthy women respectively that were refered to clinics of Alzahra, Noor and Amin Hospitals in Isfahan City, Iran in 2011. Participants were selected based on random sampling. Sample size was estimated 141 subjects in each group. Participants were visited by doctor and severity of androgenic alopecia was determined based on Ludwish criteria. Data were analyzed with SPSS software and 2 test. P<0.05 was considered as significant. Results: Mean age and body mass index were 58.96±12.8 year and 25.6±4.15 kg/m2 respectively in whole population. Findings not show any significant association between type II diabetes and androgenic alopecia (P<0.05). Comparison of distribution of alopecia severity according to Ludwish criteria separately showed similar result. In addition to, there was not any significant relationship between diabetes and alopecia after adjusting with body mass index as confounding factor (P<0.05). Conclusion: In the present study, there was not any significant relationship between type II diabetes and androgenic alopecia among diabetes and healthy women. However, more researches need to investigate this relationship in both gender and assess insulin resistant indices as homeostasis model assessment-estimated insulin resistance and androgenic alopecia.
Mahboubeh Haji Abdolbaghi , Mohammadreza Pourmand , Solmaz Taghizadegan ,
Volume 73, Issue 3 (6-2015)
Volume 73, Issue 3 (6-2015)
Abstract
Background: Diabetic foot infections a common complication of diabetes. Staphylococcus aureus is most common pathogen associated with diabetic foot infection. Frequency of methicillin-resistant Staphylococcus aureus (MRSA) associated with diabetic foot infection at other country is 15-30% and important cause at hospital acquired infection. The aim of this study was to evaluate the prevalence of pathogenic organisms and the prevalence and contributing factors of MRSA in patients with diabetic foot infection. Methods: A cross-sectional study from 70 diabetic foot infection at Imam Khomeini Hospital, Tehran, Iran from March 2013 to September 2014. A retrospective analysis of wound swabs taken from infected foot ulcers in diabetic patient, selected from an outpatient diabetic foot. Swabs were used to obtain tissue fluid from the base after debriding the ulcer with a sterile scalpel. Sixty patients with positive wound swabs were included. Size of ulcer and ulcer grade were measured in all patients. Results: A total of 61 microorganisms were isolated. The mean number of isolate was 0/87. Corynebacterium spp were the sole pathogen in three cases than taked into normal flora. There wasn’t significant P-value between demographic subjects and MRSA frequency. In this study, P= 0/05, CI:95% were considered statistically significant. Gram-positive aerobic bacteria were the most common micro-organism isolated (52.54%) followed by gram-negative aerobic bacteria (44.26%). among the gram-positive aerobic organisms, Staphylococcus aureus was found most frequently and 10% were MRSA that confirmed by E-test. There wasn’t significantly different in measurement of the MRSA positive patients compared to MRSA negative patients (P> 0.05). Conclusion: In this study, MRSA prevalence was similar to other Asian studies and different from west countries study. There wasn't significant difference between gram-positive and gram-negative microorganisms that look out to change of microbiological profile in diabetic foot infections and creation multi-drug resistant bacteria. MRSA infections and other multi drug resistant organisms is a serious problem and increasing problem in diabetic foot infections. Further studies are required to assess the need for antibiotics in treating foot ulcers in diabetes and to assess the optimal therapeutic management.
Mahdi Safarpour , Ahmad Ebrahimi , Maryam Sadat Daneshpour ,
Volume 73, Issue 9 (12-2015)
Volume 73, Issue 9 (12-2015)
Abstract
Despite the valuable results achieved in identification of genes and genetic changes associated with type 2 diabetes (T2D), lack of consistency and reproducibility of these results in different populations is one of the challenges lie ahead in introduction of T2D candidate genes. Therefore, the present review article aimed to provide an overview of the most important genes and genetic variations associated with development of T2D based on a systematic search in well-known genetic databases. For this purpose, the National Center for Biotechnology Information, Database of Genotypes and Phenotypes (NCBI dbGaP) and Human Genome Epidemiology Network (HuGENet) database were searched to find the most important genes associated with T2D. In addition, a gray literature search was conducted to collect any available information released by laboratories offering genetic tests such as deCODE genetics and 23andMe. Candidate genes were selected among the results of all databases based on the highest level of similarity. Subsequently, without any time restriction, PubMed, Scopus and Google scholar databases were searched using relevant Medical Subject Headings (MeSH) terms to access related articles. The relevant articles were screened to make a conclusion about the genes and genetic variations associated with T2D. The results revealed that four selected candidate genes, in order of importance, were TCF7L2, CDKAL1, KCNJ11, and FTO. The most significant single nucleotide polymorphism (SNP) associated with T2D in the TCF7L2 gene was rs7903146 however, the results showed a wide range of variation from slight association in the Amish (P= 5.0×10-2) to strong association in European descent populations (P= 2.0×10-51). Then, rs10440833 mapping to the intronic region of the CDKAL1 gene showed significant association with T2D (P= 2.0×10-22). In the KCNJ11 gene, a missense variation (rs5215) in exon one was found to have the highest association with T2D compared with other SNPs discovered in this gene (P= 5.0×10-11). Finally, rs8050136 located in the first intron of the FTO gene had the strongest association with T2D (P= 2.0×10-17). On the basis of these results, it can be concluded that the current study can be introduced as a model for achieving well-documented results among spectrum of information available in genetic databases based on a systematic search strategy. The candidate genes and genetic variations presented in this review article might be applied for early diagnosis, prevention, and treatment of T2D.
Hoda Rezaie , Ahmad Naghibzadeh-Tahami, Mohammad Mehdi Bagheri ,
Volume 75, Issue 6 (9-2017)
Volume 75, Issue 6 (9-2017)
Abstract
Background: The prevalence of gestational diabetes is increasing among pregnant women. It is associated with an increased risk of congenital heart disease, including hypertrophic cardiomyopathy. The aim of this study was to evaluate the effect of maternal diabetes control (based on HbA1c) on their hypertrophic cardiomyopathy in newborns.
Methods: This case-control study was performed on 60 neonates born in Afzalipour Hospital (Kerman University of Medical Sciences) from May to November 2014 in two groups of eligible infants using the convenience sampling method. Information about the age, sex, weight, gestational age, maternal age, obstetric history, gestational diabetes through the checklist were collected. Then Doppler echocardiography, M- Mode, Doppler tissue was conducted on two groups. Echocardiographic criteria including ventricular septal thickness and blood HbA1c mothers in both groups were compared. To compare quantitative and qualitative variables between the two groups’ Independent samples t‐test and Chi-square test was used. A significant level of 0.05 was considered in all of the statistical samples and SPSS software, ver. 20 (IBM, Armonk, NY, USA) was used to analyze the data.
Methods: This case-control study was performed on 60 neonates born in Afzalipour Hospital (Kerman University of Medical Sciences) from May to November 2014 in two groups of eligible infants using the convenience sampling method. Information about the age, sex, weight, gestational age, maternal age, obstetric history, gestational diabetes through the checklist were collected. Then Doppler echocardiography, M- Mode, Doppler tissue was conducted on two groups. Echocardiographic criteria including ventricular septal thickness and blood HbA1c mothers in both groups were compared. To compare quantitative and qualitative variables between the two groups’ Independent samples t‐test and Chi-square test was used. A significant level of 0.05 was considered in all of the statistical samples and SPSS software, ver. 20 (IBM, Armonk, NY, USA) was used to analyze the data.
| Results: In this study, the birth weight of infants and the age of mothers did not differ between two groups (Respectively P=0.56, P=0.08) However, HbA1c was significantly higher in the infants of mothers with impaired glucose tolerance test (GTT) (P<0.001). In infants of mothers with impaired GTT, ventricular septal thickness was significantly higher than the healthy controls (P=0.03), Also there was a significant difference between two groups in tissue Doppler criteria (Ea) (P=0.04), In other echocardiographic criteria, no significant differences were reported (The LA/AO, LVPWT, LVEF, LVEF, LVFS, LVFS, LVEDd, LVESd, Sa and Aa, All P-values were ≥ 0.05). Conclusion: Diabetes mellitus of mothers causes several complications in their infants. The prevalence of cardiomyopathy hypertrophy is higher in babies whose mothers have higher levels of HbA1c and a sign of poor control of blodd glucose level during pregnancy. |
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.
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.
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.
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.
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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. |
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.
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. |
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