Background: Skin diseases are a significant public health concern that affects a considerable percentage of children, causing discomfort and disabilities. Objective: The focus of this research was to determine the most frequent skin diseases among children in the Dermatology Department of the Tropical Disease Teaching Hospital. Methodology: This is a retrospective hospital-based research that took place from January to December 2021 at the Tropical Disease Teaching Hospital. Results: One hundred and eighty patients, ranging in age from one to eighteen years old, were included in this study, with males accounting for 60.7 % of the total (n=68). The overwhelming majority of the patients (90.2%, n=101) were from Khartoum state. In the majority of cases (92.9 % - n=104), the patients' residential situations were a risk factor; there was no crowd in their households, and 83.9 % (94) of the participants had no animals in their homes. In terms of water supply, 85.7 % (96) of the patients used tap water. The majority of patients (90.2 % - n=101) had no seasonality skin condition, and none of the patients have any chronic disorders, according to their clinical data. Skin diseases are prevalent among the patients. Throughout study, contagious skin disease affected more than half of the patients (57.1 %, n =64). Furthermore, fungal infection was found in 62.5 % (40) of patients. The great majority of patients (96.4 %, n=108) responded well to therapy. Conclusion: The sex distribution revealed a significant disparity between males and females, with females outweighing males. The majority of the patients were under the age of five. The preponderance of the incidents was linked to housing situations. There is no seasonal variation in the occurrence of illness. Skin disease was evident in more than half of the individuals. A statistical correlation was revealed between the type of skin condition and a family history of similar condition, as well as the duration of treatment.
Objectives: It was previously thought that adiponectin influenced insulin activity in tissues. Insulin resistance caused by obesity is associated to reduced plasma adiponectin levels. Researchers may be able to better understand the role of adiponectin in insulin resistance and type 2 diabetes by comparing adiponectin levels in T2DM patients to non-diabetic patients, as well as its connection with BMI and WC. Method: A case-control study was conducted at the Abu A'gla Health Care Center for diabetes care in Wad Madani, Gezira State, Sudan, between April 2012 and March 2013. The study involved a total of 181 participants. To measure adiponectin, FPG, and HbA1C levels, patients were divided into diabetes and non-diabetic groups. The body mass index (BMI) was calculated, and the waist circumference (WC) was measured. Personal information (age and gender) were obtained. Samples were analyzed for many biochemical parameters using the A15, a random-access auto-analyzer bio system. To quantify adiponectin, ELIZA employed the techniques of a human adiponectin ELISA kit. A statistical software for social sciences was used to conduct the statistical analysis (SPSS version 16, Chicago, IL, USA). Result: The mean BMI (29.007) increased significantly between diabetic and non-diabetic groups (p=0.001) indicating that the study participants were overweight. There was significant increased (p<0.0001) in FPG (160.10) and HbA1C (6.9813) and non- significant decreased in adiponectin mean (1.567) concentration. SBP and DBP mean (116.52) and (75.51) were significantly low (p=0.006) and (0.054), respectively. Conclusion: Adiponectin levels were lower in diabetic and non-diabetic patients. Only two diabetics had excessive quantities. Adiponectin and BMI were thought to have an inverse relationship, with no association between adiponectin and WC.
Objectives: To measure blood glucose, lipid profile levels, and blood pressure in diabetic hypertensive patients in order to identify the association between the parameters measured and an increased risk of cardiovascular risk in the Sudanese diabetic hypertensive patients. Material and methods: During the months of April 2012 and March 2013, a case-control study was employed in Gezira State, Sudan. The study enrolled 200 patient who met the participation criteria, with respondents divided into diabetic hypertensive and non-diabetic categories to estimate fasting blood glucose levels (FBG), Glycosylated hemoglobin (HbA1C) and lipid profile which include; total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) and triglycerides (TG). The random access auto-analyzer bio system, A15 was used to test samples for various biochemical parameters. Individual information, as well as anthropometric and biochemical measurements were collected on a questionnaire. After each participant gave verbal consent, venous blood samples were drawn after an overnight fast. The statistical evaluation was achieved with the aid of a statistical package for social sciences (SPSS version 16, Chicago, IL, USA). Result: The WC and BMI both increased significantly by (p=<0.0001), according to the analysis of variance (ANOVA). FBG and HbA1C levels were significantly elevated by (p=<0.0001). The increase in systolic blood pressure (SBP) was significant by (p=<0.0001). The mean HDL-C level was at high risk (49.73) with a significant increase by (p=0.009). The mean LDL-C concentration was above the optimum level (109.03) with a non-significant increase (p=0.697). Conclusion: WC, BMI, DBP, FBG, and HDL-C all increased significantly. Diabetic- hypertensive participants were at a high risk of develops dyslipidemia and cardiovascular disease.
We present in this paper a discrete analogue of the continuous generalized inverted exponential distribution denoted by discrete generalized inverted exponential (DGIE) distribution. Since, it is cumbersome or difficult to measure a large number of observations in reality on a continuous scale in the area of reliability analysis. Yet, there are a number of discrete distributions in the literature; however, these distributions have certain difficulties in properly fitting a large amount of data in a variety of fields. The presented DGIE β , θ has shown the efficiency in fitting data better than some existing distribution. In this study, some basic distributional properties, moments, probability function, reliability indices, characteristic function, and the order statistics of the new DGIE are discussed. Estimation of the parameters is illustrated using the moment's method as well as the maximum likelihood method. Simulations are used to show the performance of the estimated parameters. The model with two real data sets is also examined. In addition, the developed DGIE is applied as color image segmentation which aims to cluster the pixels into their groups. To evaluate the performance of DGIE, a set of six color images is used, as well as it is compared with other image segmentation methods including Gaussian mixture model, K-means, and Fuzzy subspace clustering. The DGIE provides higher performance than other competitive methods.
Objectives: To find out the association of type 2 diabetes mellitus (T2DM) with increased risk of dyslipidemia and cardiovascular disease in Sudanese population, glucose, lipid profile as well as blood pressure were measured. Materials and Method: A case-control study was made at Gezira State, Sudan, during the period of April 2012-March 2013. A total of two hundred matching inclusion criteria were enrolled in the study, participants divided into diabetic and non-diabetic groups to estimate the levels of FPG, Glycosylated hemoglobin HbA1c and lipid profile (TC, HDL-C, LDL-C, and TG). Samples were analyzed for different biochemical parameters, using A15, a random access auto-analyzer bio system. A questionnaire including personal information was filled as well as anthropometric and biochemical measures. Verbal consent obtain from each respondent then venous blood was collected after an overnight fast. Statistical analysis was carried-out using statistical package for social sciences (SPSS version 16, Chicago, IL, USA). Result: Tukey- HSD test showed that BMI, SBP and DBP increased significantly by (0.001), (0.017) and (0.032) respectively. FPG and HbA1c were increased with highly significant (p=>0.0001). TC, HDL-C and LDL-C showed non-significant increase in their mean concentrations (196.28), (54.28) and (105.75) respectively. TG mean concentration was (158.86) had increased significant (0.057). Conclusion: Study showed significant increase in BMI. Lipid profile of study participants showed no differences in TC and LDL-C and HDL-C, but TG showed significant increased. Systolic (SBP) and diastolic (DBP) blood pressure showed significant increase in all study participants. Study population with T2DM was at high risk to develop metabolic syndrome.
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