Emmanouil Paraskakis

The effect of obesity on pulmonary lung function of school aged children in Greece

Obesity impacts on many issues of pulmonary medicine, where it is debated if obesity is linked to asthma, atopy or altered lung function tests. Our study aimed to investigate primarily the effect of obesity on the lung function tests and secondary the possible link of obesity with atopy and asthma in a large cohort of children in Greece.

G894T polymorphism of eNOS gene is a predictor of response to combination of inhaled corticosteroids with long-lasting β2-agonists in asthmatic children

AIM Nitric oxide synthase enzymes have an important role in airway inflammation in asthmatic children. In the present study, the association between eNOS gene polymorphisms and response to inhaled corticosteroids (ICS) and long-lasting β(2)-agonists (LABAs) was investigated. PATIENTS & METHODS A total of 81 asthmatic children treated with ICS plus LABAs and 96 healthy controls were genotyped for eNOS G894T and -786T/C polymorphisms and their haplotypes using the PCR-RFLP method. RESULTS G894T and -786T/C polymorphisms were not associated with asthma susceptibility. Among asthmatic children, 894TT carriers had higher change in forced expiratory volume in 1 s (FEV(1)) in response to ICS plus LABAs compared with 894GG carriers (21.9 ± 3.8 vs 1.6 ± 1.9%; p < 0.001). In responders (FEV(1) change ≥7.5%), frequency of 894TT genotype was significantly higher than in nonresponders (26.2 vs 2.6%, p < 0.001). Results for the -786T/C polymorphism alone were less clear and in most cases nonsignificant. CONCLUSION The G894T polymorphism was associated with response to ICS and may serve as a useful pharmacogenetic marker of response to ICS plus LABAs in asthmatic children.

Current evidence for the management of paediatric parapneumonic effusions

Abstract Background: Parapneumonic effusions (PPE) and empyema, secondary to bacterial pneumonia, are relatively uncommon but their prevalence is increasing lately. Even if their prognosis is generally good, they may still cause significant morbidity. The traditional treatment of PPE has been intravenous antibiotics and, when necessary, chest tube drainage. Open thoracotomy with decortication has usually been applied in case of failure of the traditional approach. Lately, the use of fibrinolysis and/or video-assisted thoracoscopic surgery (VATS) are utilized in the management of PPE; however, there is still little consensus on the most effective primary treatment. Scope: In this article our goal was to summarize, based on up-to-date evidence, all the management options for PPE available to physicians and weigh the benefits and risks of the most popular ones, in an effort to figure out which one is superior as a first-line approach in children. Findings: A literature search of randomized and retrospective studies that pinpoint methods of evaluation and treatment of PPE was carried out in Medline and Scopus databases. Chest X-ray, ultrasound as well as microbiology and biochemical characteristics of the pleural fluid will facilitate decision-making. Small uncomplicated effusions resolve with antibiotics alone, larger ones require small-bore chest tube drainage and in case of complicated loculated PPE, fibrinolysis or VATS should be considered. Both methods promote faster drainage, reduce hospital stay and obviate the need for further interventions when used as first-line approach. However, primary treatment with VATS is not advised by the majority of studies as a first choice intervention, unless medical treatment has failed. Conclusion: The main steps in treatment are diagnostic thoracocentesis and imaging, small percutaneous drainage, and considering fibrinolysis in complicated PPE. In case of failure, VATS should be the surgical method to be applied.

An Intelligent System Approach for Asthma Prediction in Symptomatic Preschool Children

Objectives. In this study a new method for asthma outcome prediction, which is based on Principal Component Analysis and Least Square Support Vector Machine Classifier, is presented. Most of the asthma cases appear during the first years of life. Thus, the early identification of young children being at high risk of developing persistent symptoms of the disease throughout childhood is an important public health priority. Methods. The proposed intelligent system consists of three stages. At the first stage, Principal Component Analysis is used for feature extraction and dimension reduction. At the second stage, the pattern classification is achieved by using Least Square Support Vector Machine Classifier. Finally, at the third stage the performance evaluation of the system is estimated by using classification accuracy and 10-fold cross-validation. Results. The proposed prediction system can be used in asthma outcome prediction with 95.54 % success as shown in the experimental results. Conclusions. This study indicates that the proposed system is a potentially useful decision support tool for predicting asthma outcome and that some risk factors enhance its predictive ability.

Chromosome Instability on Children with Asthma

Background. Asthma is a complex disease with multiple interactions between genetic and environmental factors. Objective. The aim of our study was to investigate the possible genetic instability in asthmatic patients (AP) with asthma in human cultured peripheral blood lymphocytes. Furthermore, the presence of either cytostaticity or cytotoxicity was demonstrated. Methods. Human peripheral blood lymphocytes were cultured from 18 admitted children to the Pediatric Clinic of the University Hospital of Alexandroupolis (average age 7.2 years), and 9 healthy blood donors were used as control subjects (average age 6.5 years), none of whom was receiving drugs for medical or other reasons. Results. A significant (p < 0.05) increase in spontaneous sister chromatid exchanges (SCEs) frequency in asthmatic patients compared with control subjects was observed. No statistically significant modification in the spontaneous proliferation rate index (PRI) in AP compared with the controls was demonstrated. Finally, MMC induced a statistically significant increase in SCEs frequency both to controls and to AP, with the MMC-induced SCEs rates in AP being statistically (p < 0.01) higher compared to the MMC-induced SCEs in controls. Conclusion. We try to improve a new diagnostic process of possible genetic instability by a combination of genotoxic, cytostatic and cytotoxic effects of asthma on human peripheral lymphocytes.

An Artificial intelligence technique for the prediction of persistent asthma in children

The prediction of asthma that persists throughout childhood and into adulthood, in early life of a child has practical, clinical and prognostic implications and sets the basis for the future prevention. Artificial Neural Networks (ANNs) seems to be a superior tool for analyzing data sets where nonlinear relationships are existing between the input data and the predicted output. This study presents an effective machine-learning approach based on Multi-Layer Perceptron (MLP) neural networks, for the prediction of persistent asthma in children. Through a feature reduction, 10 high importance prognostic factors correlated to persistent asthma have been discovered. The feature selection approach results in 89.8% reduction of the initial number of features. Afterwards, a feature reduced classifier is constructed, which achieves 100% accuracy on the training and test data sets. Experimental results are presenting and verify this statement.

Asthma phenotypes in children and stratified pharmacological treatment regimens

ABSTRACT Introduction: Asthma is the most common inflammatory disease in childhood. The interaction of genetic, environmental and host factors may contribute to the development of childhood asthma and defines its progress, including persistence and severity. Until now, various classifications of childhood asthma phenotypes have been suggested based on patient’s age during onset of symptoms, type of inflammatory cells, response to treatment and disease severity. Many efforts have been carried out to identify childhood asthma phenotypes and to clarify which are the risk factors that define asthma prediction and the response to therapy. The identification of asthma phenotypes has not only prognostic but also therapeutic role. However, the classification of asthma phenotypes is complex due to the heterogeneity of the disease. Areas covered: The current childhood asthma phenotypes and the new therapeutic strategies for each phenotype are reviewed. Expert commentary: There are multiple phenotypes in childhood asthma and it is crucial to define them before the initiation of personalized treatment. Both the therapeutic strategy and monitoring should follow the recent guidelines.

Diagnosis of Asthma Severity Using Artificial Neural Networks

During the last years, neural networks have become a very important method in the field of medical diagnostic. In this work, a technique is proposed that involves training a Multi-Layer Perceptron with back-propagation learning algorithm, in order to recognize three classes of asthma severity, through the results of breathing tests. The breathing test parameters and the diagnosis of physicians for 200 cases of children- patients, aged 10-12 years from Alexandroupolis Hospital in Greece, are used in the supervised training method to update the network parameters. This method was implemented to diagnose three asthma cases according to their severity: mild, moderate and severe asthma. Results obtained by using Neural Network Toolbox of Matlab, show that the proposed ANN can be used in asthma diagnosis with 98% success. This research work improves the asthma diagnosis accuracy with higher consistency in order to specify the seriousness of the condition of a patient and the appropriate course of medical treatment.

Acquired somatic mutations in the microsatellite DNA, in children with bronchial asthma †

High incidence of genetic alterations at the microsatellite (MS) DNA level has been reported in asthmatic adults.

The Role of Flow-Independent Exhaled Nitric Oxide Parameters in the Assessment of Airway Diseases

Nitric oxide (NO), the first gas known to act as a biological messenger, is one of the most widely studied free radical/gas in medicine, both for its biological function and therapeutic applications. The measurement of endogenous NO in exhaled air is widely used in the evaluation of lung disorders. Partitioning of exhaled nitric oxide (eNO) is of increasing interest because of the additional information about lung pathology and distal lung inflammation that can be obtained. Specifically, measuring exhaled NO at multiple flow rates allows assessment of the flow-independent NO parameters: alveolar NO concentration (CalvNO), bronchial NO flux (JNO), bronchial wall NO concentration (CWNO), and bronchial diffusing capacity of NO (DNO). Several studies have reported that there were different patterns of those parameters in different airway diseases and/or in different severities of the same disease, mostly in asthma. Specifically, while JNO seems to provide the same information as FeNO50, alveolar NO concentration appears to be an independent parameter that is putatively associated with increased distal lung inflammation and more severe disease. However, despite much research interest in partitioning exhaled NO, clinical usefulness has yet to be established.