ABSTRACT
Introduction: Asthma is a chronic inflammatory airway disorder that is distinguished by coughing, wheezing, and dyspnea. It is the most common chronic disease among children. Epidemiological trials have suggested that there may be a correlation between vitamin C intake and the incidence of asthma. Specifically, according to these studies, a rapid increase in the occurrence of asthma may be caused by a decreased intake of dietary antioxidants and various vitamins such as vitamin C. A systematic review was performed to determine the role that vitamin C, in terms of both dietary intake and serum levels, had on asthma in children
Methods: PubMed and Scopus databases were searched for studies that provide information on the effects of vitamin C on asthma in children aged between 1 and 17 years. The inclusion criteria specified that the studies involved needed to be cohort and case series involving at least ten patients. Exclusion criteria were non-English articles, case reports, and articles involving children who were aged below or above the age 1 and 17 respectively
Result: A total of 13 studies involving 6503 patients met the inclusion criteria. Dietary vitamin C intake was lower in people with asthma than in those without asthma. Lower quantity dietary intakes and serum levels of vitamin C were also associated with increased incidents of asthma
Conclusion: According to the extracted data, a relatively low dietary intake of vitamin C is associated with an increased risk of asthma and wheezing. Moreover, asthmatic patients who consumed vitamin C exhibited an improvement in their diseases
ABSTRACT
Introduction: The aim of this study was to determine the performance of data mining techniques for predicting the causes of traumatic brain injuries in Khatamolanbya hospital, Zahdan city
Method: In this cross-sectional, the study population included all patients who died of brain injury. Data were collected by the use of a researcher- made check list, provided under the direct observation of authorities in this area and analyzed by the data mining software of Clementine 12.0
Results: According to the results of this algorithm, C5.0 decision tree algorithm has an accuracy of 81.4 percent, the highest precision; then, the algorithm is C and R[The Classification and Regression] with 77.8 percent
Conclusion: Overall, it can be concluded from the decision tree algorithm that age is one of the leading causes of traumatic brain injuries . The results showed that all the cases involving traumatic lesions of the brain lead to the patient's death.. Although in some algorithms, some of the variables are important, they cannot be used alone as the main variable to be taken into account for the death of the patient