مجله غدد درون ریز و متابولیسم ایران
سال بیست و چهارم شماره 1 (پیاپی 121، فروردین و اردیبهشت 1401)

Gestational diabetes is associated with many short-term and long-term complications in mothers and newborns; hence, the detection of its risk factors can contribute to the timely diagnosis and prevention of relevant complications. The present study aimed to design and compare Gestational diabetes mellitus (GDM) prediction models using artificial intelligence algorithms.

In this study, Decision Tree and Artificial Neural Network algorithms were used to predict GDM. The research population encompassed 1270 pregnant women referred for primary care at urban healthcare centers in Ahvaz, of whom 816 persons were healthy, and 454 individuals were diagnosed with GDM. To evaluate the effectiveness of the GDM prediction models, their sensitivity, specificity, precision, and accuracy were calculated and compared. Finally, the AdaBoost classification algorithm was used to boost the two proposed models.

Following the Principal Component Analysis (PCA), nine cases were selected for primary modeling. In the Artificial Neural Network model, the area under the ROC curve and sensitivity were 83.2 and 85.1%, respectively, and the area under the ROC curve and sensitivity for the Decision Tree model were 0.826 and 84%, respectively. After removing variables with lower weights and reinforcing the proposed model, the level under the rock curve and sensitivity increased by 0.861 and 92.1%, respectively. In this regard, fasting blood sugar at the first pregnancy visit, history of gestational diabetes in previous pregnancies, body mass index, mothers’ age, and family history of diabetes had the highest accuracy in predicting GDM.

The findings of this study indicate that artificial intelligence algorithms are accurate and effective for the early prediction of gestational diabetes.

This study aimed to determine the effect of a web-based educational intervention according to the Health Belief Model (HBM) on adherence to preventive behaviors of type-2 diabetes (nutrition and physical activity) and blood sugar control in pre-diabetic patients in Bushehr.

This quasi-experimental study with two intervention and control groups encompassed 92 pre-diabetic patients in Comprehensive Health Service Centers affiliated with the Bushehr University of Medical Sciences, who were randomly assigned to intervention and control groups. The intervention group received multimedia training based on the HBM constructs from a specific web-based platform. The collected data were collected using a specific questionnaire before, two weeks after, and three months after the intervention. Blood glucose was also assessed using laboratory tests before and three months after the intervention. The collected data were analyzed with SPSS software version 24.

According to the results, there were statistically significant differences between the two groups in terms of Knowledge (p<0.001) and health belief model constructs including perceived sensitivity (p<0.001), perceived intensity (p<0.001), self-efficacy (p<0.001) ,and the perceived benefits (p<0.001) during the research period . Accordingly, the mean score of knowledge and all constructs in the intervention group increased significantly, and the perceived barriers decreased significantly. Moreover, after the educational intervention in the intervention group, their adherence to diabetes preventive behaviors (physical activity and nutrition) improved (p<0.001), and their fasting blood sugar level decreased (p<0.001).

The findings revealed that educational intervention based on the HBM and multimedia on the web is effective in improving healthy behaviors and lowering blood sugar in pre-diabetic patients. Accordingly, the use of these strategies during the treatment and blood sugar control programs in prediabetic patients is recommended .

Serum levels of cardiac troponin (CTnI) and creatine kinase (CK-MB) are two indicators of cardiac cell damage. The present study aimedto investigate the effect of different volumes of a high-intensity interval training (HIIT) course on serum CTnI and CK-MB levels in cardiac patients after myocardial infarction (MI).

In this semi-experimental study with pretest–posttest design, thirty patients (50.03±4.32 years) with documented MI were selected voluntarily. Regarding the researchcriteria, all participants were randomly assigned into three groups (n=10 per group): Acontrol group and two high-volume HIIT training (HV-HIIT) and low-volume HIIT training (LV-HIIT)groups.The HV-HIIT group did exercisesthree days a week for 40 minutes, and the LV-HIIT group didexercises three days a week for 20 minutes.Blood samples were taken before and after the 12-week intervention. Statistical analysis of the variables was performedusingpaired t-tests, one-way analysis of variance, and Tukey's post hoc test.

At the end of the intervention, CTnI in the LV-HIIT and HV-HIIT groups decreased significantly (70% and 50%, respectively); however, no significant change was observed in the control group. CK-MB levels showed a significant decrease (26%)only in the LV-HIIT group. In the serum levels of CTnI, a significant difference was observed amongthe three groups (p=0.035), and the results of Tukey's post hoc test showed a significant difference between the control and LV-HIIT groupsin terms ofdecreasedCTnI levels(p=0.012).

LV-HIIT training as an exercise strategy for cardiac rehabilitation programs after MI can improve cardiac injury indices more effectively than HV-HIIT and is associated with less cardiac damage and fatigue.

The potential relationship between thyroid dysfunction with common psychological problems (i.e., depression, anxiety, and stress), and health-related quality of life (HRQoL) has been discussed in the literatures. However, previous studies have mostly addressed overt hypo-hyper thyroid patients, and it has been limited to hypothyroidism in Iranian population. The novelty of this study is investigating the same relationship using the most up-to-date and reliable questionnaires among Iranian adults with overt and subclinical hypo- and hyper- thyroid dysfunctions compared to euthyroid individuals.

In this cross-sectional study, the participants were selected randomly from patients referred to the endocrinology clinic. In this regard, 212 patients were selected regarding inclusion and exclusion criteria and categorized into hypofunctional (subclinical and overt hypothyroidism), hyperfunctional (subclinical and overt hyperthyroidism), and euthyroid groups. The participants’ emotional states and HRQoL were assessed using the 21-item Depression, Anxiety, and Stress Scale (DASS-21) and the Short-Form 12-point Health Survey Version 2 (SF-12v2). The collected data was analyzed with the SPSS software version 22.

 The results indicated that those with thyroid dysfunction in both hypofunctional and hyperfunctional groups had significantly higher levels of depression, anxiety, and stress symptoms (p<0.05) and lower HRQoL than their euthyroid counterparts. However, a more detailed analysis showed that the physical and mental domains of HRQoL were mainly affected in the participants with hyper- and hypo-functional dysfunction, respectively.

 The present findings revealed that thyroid dysfunction could lead to negative emotional states in adult populations. Similar findings have been achieved for HRQoL in different aspects.

Exercise is one of the lifestyle interventions recommended to reduce liver damage and improve health. The present study aimed to investigate the relationship between physical activity and physical fitness with the liver enzymes of COVID-19 patients.

Four hundred patients infected with COVID-19 (57.6±14.6, body mass 28.1±4.7 kg/m2) admitted to the Masih Daneshvari Hospital in Tehran participated in the present study. After Introducing with the work procedure, Beck and Stanford’s questionnaires were used to check their physical activity. Each participant filled out the physical fitness self-assessment questionnaire to self-report his/her physical fitness. Fasting blood samples were taken to measure aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, and lactate dehydrogenase.

The statistical analysis of the collected data revealed a significant correlation between physical activity with aspartate aminotransferase (p=0.035) and alanine aminotransferase (P=0.001), and there was a difference between different levels of physical activity. The results also showed is no significant relationship between alanine (p=0.068) and aspartate aminotransferase (p=0.375) with physical fitness. However, there was no significant relationship between physical activity and physical fitness with alkaline phosphatase (p =0.271) and lactate dehydrogenase (p =0.311).

According to the findings, it can be concluded that regular physical activity prior to COVID-19 infection is associated with high levels of liver alanine aminotransferase and aspartate aminotransferase.

Metabolic syndrome is associated with an increase in chronic inflammation, in which exercise training may be an effective intervention for the improvement of inflammatory markers. Accordingly, this study aimed to investigate the effect of exercise training on the inflammatory markers of interleukin 6 (IL-6), tumor necrosis factor alpha (TNF-α), and C-reactive protein (CRP) in patients with metabolic syndrome.

In this study, the PubMed, Scopus, and Web of Science databases were searched during June 2022 for studies addressing the effects of exercise training versus control on inflammatory factors, including IL-6, TNF-α, and CRP. The search keywords were exercise training, inflammation, and metabolic syndrome. Standardized mean difference (SMD) and 95% confidence interval were used to determine the effect size using CMA2.

Twenty-two studies including 779 subjects with metabolic syndrome were included in the meta-analysis. Exercise training significantly decreased TNF-α [-0.74 (CI: -0.24 to -1.24), p=0.003] and CRP [-0.56 (CI: -0.25 to 0.87, p=0.001); however, the effect of exercise training on the decrease of IL-6 was not significant [-0.32 (CI: 0.20 to -0.85), p=0.22].

Exercise training decreases inflammatory markers in patients with metabolic syndrome, which may be a reason for the positive effects of exercise training on improving the metabolic status and cardiovascular health in such patients.