Tehran University Medical Journal

Background: Tuberculosis (TB) is an important infectious disease with high mortality in the world. None of the countries stay safe from TB. Nowadays, different factors such as Co-morbidities, increase TB incidence. World Health Organization (WHO) last report about Iran's TB status shows rising trend of multidrug-resistant tuberculosis (MDR-TB) and HIV/TB. More than 95% illness and death of TB cases are in developing countries. The most infections are in South East Asia and West Pacific that 56% of them are new cases in the world. The incidence is actually new cases of each year. Incidence prediction is affecting TB prevention, management and control. The purpose of this study is designing and creating a system to predict TB incidence by time series artificial neural networks (ANN) in Iran.
Methods: This study is a retrospective analytic. 10651 TB cases that registered on Iran’s Stop TB System from March 2014 to March 2016, Were analyzed. Most of reliable data used directly, some of them merged together and create new indicators and two columns used to compute a new indicator. At first, effective variables were evaluating with correlation coefficient tests then extracting by linear regression on SPSS statistical software, version 20 (IBM, Armonk, NY, USA). We used different algorithms and number of neurons in hidden layer and delay in time series neural network. R, MSE (mean squared error) and regression graph were used for compare and select the best network. Incidence prediction neural network were designed on MATLAB® software, version R2014a (Mathworks Inc., Natick, MA, USA).
Results: At first, 23 independent variables entered to study. After correlation coefficient and regression, 12 variables with P≤0.01 in Spearman and P≤0.05 in Pearson were selected. We had the best value of R, MSE (mean squared error) and also regression graph in train, validation and tested by Bayesian regularization algorithm with 10 neuron in hidden layer and two delay.
Conclusion: This study showed that artificial neural network had acceptable function to extract knowledge from TB raw data; ANN is beneficial to TB incidence prediction.

Background: The aim of the present study is to determine the accuracy of ultrasound imaging in the diagnosis of metastatic lymph nodes compared to postoperative pathology samples of patients with papillary thyroid cancer.
Methods: This study was carried out using a descriptive and analytical epidemiological method on 103 known patients with papillary thyroid cancer who referred to Imam and Golestan hospitals in Ahvaz for neck ultrasound from September 2021 to August 2022. A total of 103 patients (including 94 women (91.3%) and 9 men (8.7%)) with papillary thyroid cancer with an average age of (39.8±11.9) were included in the study. The average tumor size in these patients was estimated to be (16.8±10mm). The ultrasound results of these patients before surgery were compared with the pathology results of these patients after surgery.

Results: According to the obtained results, metastatic involvement of cervical lymph nodes was diagnosed in 36.6% of patients (38 people). Of these, 30.7% of patients (32 people) were real positive. The results of ultrasound before surgery were shown as false positive in 9.5% of patients (6 people). Lymphatic metastasis was not seen in 58.4% of patients (60 people) before surgery, which was consistent with the pathology result after surgery (true negative). The positive predictive value of examining metastatic lymph nodes by ultrasound was estimated at 84.2% and the negative predictive value at 92.3%. The diagnostic accuracy of ultrasound was 89%, the sensitivity rate was 86%, and the specificity rate was 90% with the area under the curve AUC=0.884 and P<0.001. Ultrasound accuracy is not affected by tumor size, Hashimoto's thyroiditis and metastasis location (P<0.05). In patients with Hashimoto's thyroiditis, the tumor size increases significantly more than 10 mm. Conclusion: Ultrasound alone has an acceptable diagnostic accuracy in detecting metastatic lymph nodes caused by papillary thyroid cancer. However, the incidence of false negative error increases as the tumor size decreases.

Background: The study of the angles between the vertebrae and the curvatures of the spine plays an essential role in the pathogenesis of spinal disorders. Among the essential topics, the cervical sagittal parameters are widely used in evaluating cervical spine disorders and surgery. Measurement of cervical lordosis curves in healthy people is influenced by various factors. This study was conducted in order to investigate the average indexes of the cervical vertebrae in simple graphs in normal people.
Methods: In this descriptive study, using Gunya and Radiant software, radiographic photographs of the lateral view of the cervical region of 50 people (28 men and 22 women) who were referred for purposes other than problems related to neck pain were examined. Patients who were candidates for surgery and congenital disorders of the cervical spine were excluded. The study was conducted between March to April 2022. In this study, 12 cervical indexes were comprehensively measured and the scope of their changes in relation to age and gender was investigated. The measurements were conducted by an experienced radiologist.

Results:  In this study, 50 participants including 28 male (58%) and 22 female (44%) were included in the study. The mean age of participants 38.42 ± 2.1 years. After comparing the two genders, except for C0-C2/C2-C7 ratio index (4.9 in men and 2.6 in women) (P= 0.012), no significant difference was seen for other indexes (P> 0.05). After comparing the two groups, a significant difference was seen only in the T1 slope (T1S) index, which was significantly higher in people over 35 years old than in people under 35 years old (71.15 vs. 69.04) (P=0.049). Conclusion: The evidence from this study shows that T1S increases with age and C0-C2/C2-C7 is significantly less in women than in men. These findings can be used to diagnose pathology or destructive changes in the elderly, to evaluate movement disorders, the effectiveness of treatment, and to determine the outcome.

Background: Increasing the prevalence of non-contagious and chronic disorders such as Non-alcoholic fatty liver disease (NAFLD) takes the attention of researchers. NAFLD recognized by abnormal accumulation in the liver tissue. The aim of present study is investigating the association between liver size liver enzymes and degree of fatty liver in patients with NAFLD.
Methods: Based on the inclusion criteria, 100 Patients were selected from those referred to the radiology and ultrasonography clinic in Golestan Hospital, Ahvaz, for fatty liver evaluation. The study was carried out during May 2022 to April 2023. Liver enzymes, including alanine aminotransaminase (ALT) and Aspartate aminotransferase (AST), were measured. Based on the ultrasonography results, patients were divided into four groups: healthy, mild fatty liver, moderate fatty liver, and severe fatty liver. Ultrasonography was carried out by an experienced expert. All demographic information of patients was collected. Data were analyzed by SPSS (V25).

Results: According to ultrasonography results, the mean of span was 148.4 ± 14.7 cm, which was significantly higher in patients with grade II of NAFLD (P<0.001). Further analysis revealed the highest difference between grades I and II (P<0.001). Also, a significant difference between grades II and III and grades III and I were found  (P<0.001). Our data showed a significant relationship between body mass index (BMI) and NAFLD grades (P<0.001). The mean of BMI in grade I was significantly lower than in grades II and III (P<0.05). Our findings demonstrated that the mean of ALT in grade I was significantly lower than in grades II and III (P<0.05). In this line, the highest AST level was seen in grade III (P<0.001). Conclusion: Our study showed that as NAFLD progresses, the enzymes and size of the liver increase. Based on ultrasound findings, the increasing liver size suggests NAFLD grade II, while the rise in AST and BMI suggests NAFLD grade II -III and progression of cirrhosis.