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Showing 4 results for Asthma
Investigation Of Adiponectin To Leptin Ratio, Insulin Resistance And Pulmonary Function Profile In Obese Chronic Asthmatic Males
Farzad Nazem, Behzad Keshavarz,
Volume 7, Issue 2 (7-2013)
Abstract

Background and Aim: Plasma leptin, adiponectin (as theadipokines) and related obesity – HOMA index in the obese men are introduced as a predictive metabolic indicators for asthmatic individuals. However, under asthma conditions, role of cariometabolic variables interaction for altering clinical pulmonary indexes aren't clear. In the present study, the relationship between plasmatic adiponectin to leptin ratio (adipo/lep) with respiratory capacities & HOMA in the chronic asthmatic males are investigated.

Materials and Methods: Thirty nine obese males with mild to moderate asthma with an average age of 38±2.6 ys and BMI 31.4 ± 1.06 kg/m2 voluntarly participated in this study. Baseline plasmatic leptin, adiponetin, insulin and glucose levels were determined after 10-12 hours fasting overnight. FEV1/FVC, PEF% and FEF 25%-75% were determined by standard method. A pearson correlation test was used to analyse data.

Results: There were no significant correlation between WHR , BMI with metabolic risk factors (P>0.05). Relationship markedly observed among HOMA with adipo/ lep ratio and leptin levels respectively (P<0.05), Also a marked negative correlation between adipokine ratio and leptin level was obtained (P<0.05). From view of respiratory efficiency, FVC% and FEV1/ FVC were maingly corrected with baseline leptin&adiponectin levels (P<0.05).

Conclusion: Inconclusion,it seems that adipo/lep ratio biomarker plays as a clinical diagnosis index for HOMA index than baseline leptin or adiponectin levels. However, these findings showed that FEV1/FVC & adipo/lept ratios are accounted as valuable indicators for evaluating the obesity syndrome and pulmonary efficiency in the asthma disease.


Data Mining And Analysis: Reporting Results For Patients With Asthma
Taha Samad Soltani , Mostafa Langarizadeh, Maryam Zolnoori,
Volume 9, Issue 3 (9-2015)
Abstract
Background and Aim: Data mining is a very important branch in deeper understanding of medical data, which attempts to solve problems in the diagnosis and treatment of diseases. One of the most important data mining applications is to examine the existing data patterns. The present study aims to examine the existing data patterns of patients with asthma. Materials and Methods: This study was performed on 258 patients with respiratory symptoms, who referred to Imam Khomeini and Masih Daneshvari Hospitals in 2009. All records were entered into Excel software, and data mining add-ins were used. Analyses such as key influencers, cluster analysis of patients, and detecting exceptions have been done. Results: The most common clinical sign of asthma among subjects was severe coughing, which was highly affected by thrills. The data were aggregated into 5 clusters for more general analyses. Their common denominator was then identified and the records with exceptional features were determined. Then, following cost analysis and setting the threshold value at 612, a questionnaire was developed based on data features for diagnosis of asthma. Conclusion: The developed framework for data mining and analysis is an appropriate tool for knowledge extraction based on the data and their relationships. Meanwhile, it can identify and fill the existing gap in medical decision- making when using clinical guideline
Asthma Control Level Assessment by Moving from the Current Reactive Care Models into a Preventive Approach based on Fuzzy Clustering and Classification Algorithms
Roghaye Khasha, Mohammad Mahdi Sepehri, Nasrin Taherkhani,
Volume 14, Issue 3 (7-2020)
Abstract
Background and Aim: Asthma is a common and chronic disease of respiratory tracts. The best way to treat Asthma is to control it. Experts of this field suggest the continues monitoring on Asthma symptoms and adjustment of self-care plan with offering the preventive treatment program to have desired control over Asthma. Presenting these plans by the physician is set based on the control level in which the patient is. Therefore, successful recognition and classification of the disease control level can play an important role in presenting the treatment program to the patient and improves the self-care and strengthens the early interventions to alleviate the Asthma symptoms.  
Materials and Methods: Based on this objective, we collected the data of 96 Asthma patients within a 9-month period from a specialized hospital for pulmonary diseases in Tehran. Then we classified the Asthma control level by fuzzy clustering and different types of data mining method within a multivariate dataset with the multi-class response variable.
Results: Our best model resulting from the balancing operations and feature selection on data have yielded the accuracy of 88%.
Conclusion: Our proposed model can be applied in electronic Asthma self-care systems to support the decision in real time and personalized warnings on the possible deterioration of Asthma control. Such tools can centralize the Asthma treatment from the current reactive care models into a preventive approach in which the physician’s decisions and therapeutic actions are resulting from the personal patterns of chronic Asthma control and prevention of acute Asthma.

The Effect of Information Therapy Program of Quitting Smoking in Parents of Children with Asthma by Nicotine Replacement
Sedigheh Mohammadesmaeili, Nahid Ramzanghorbani, Shiba Kianmehr,
Volume 18, Issue 2 (5-2024)
Abstract
Background and Aim: Passive smoking is known to have an impact on the respiratory system of infants and children. The aim of this study is to examine the positive effects of parental smoking cessation programs using nicotine replacement on quality of life in children with asthma at the Children's Medical Center of Tehran University of Medical Sciences.
Materials and Methods: This case-control study included 100 children aged 6-10 years with asthma who had their parents smoking in the Allergy Department of the Children's Medical Center of Tehran University of Medical Sciences. During the 2019-2021 period, this study was conducted using a census as the sampling method. Data were collected using standard questionnaires of the Child Health-Related Quality of Life (HRQoL), standard versions of the Short Form (SF-12) and the St George Respiratory Questionnaire (SGRQ). The two groups were compared using independent t-tests and paired t-tests, and Pearson's correlation coefficient was utilized to examine the correlation between the two questionnaires. Statistical analysis was performed using SPSS software.
Results: Children with asthma who had their parents quit smoking had a mean score lower than those who did not intervene. This indicates that the quality of life in children with asthma whose parents underwent nicotine replacement program improved significantly (P=0.03). Nicotine gum consumption can enhance certain aspects of health-related quality of life for both parents and children, as assessed by SF-12 and SGRQ, according to the results. Physical functioning (P=0.007) and school performance (P=0.002) were the two components most significantly affected.
Conclusion: The physical health and quality of life of parents are can affecte children with asthma, who face many challenges in meeting their daily needs. Smoking cessation using nicotine gum can improve the quality of life of parents and children. To maximize the effectiveness of parental smoking cessation information therapy programs for children with asthma, providing personalized support and advice to parents or caregivers, evidence-based treatments, and educating families on how to manage this disease in children seems essential.

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