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Asthma control, severity and lung function impairment through network analysis in children

Antonio Abbruzzo, Giovanna Cilluffo, Laura Montalbano, Velia Malizia, Giuliana Ferrante, Roberta Antona, Stefania La Grutta
European Respiratory Journal 2015 46: PA4515; DOI: 10.1183/13993003.congress-2015.PA4515
Antonio Abbruzzo
2Economics Business and Statistical Sciences, University of Palermo, Palermo, Italy
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Giovanna Cilluffo
1Institute of Biomedicine and Molecular Immunology, National Research Council, Palermo, Italy
2Economics Business and Statistical Sciences, University of Palermo, Palermo, Italy
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Laura Montalbano
1Institute of Biomedicine and Molecular Immunology, National Research Council, Palermo, Italy
3Psychology, University of Palermo, Palermo, Italy
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Velia Malizia
1Institute of Biomedicine and Molecular Immunology, National Research Council, Palermo, Italy
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Giuliana Ferrante
4Science for Health Promotion of Mother and Child, University of Palermo, Palermo, Italy
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Roberta Antona
1Institute of Biomedicine and Molecular Immunology, National Research Council, Palermo, Italy
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Stefania La Grutta
1Institute of Biomedicine and Molecular Immunology, National Research Council, Palermo, Italy
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Abstract

Background: Achieving and maintaining asthma control in children is the primary goal recommended by current guidelines.

Aim: To identify risk factors associated with Asthma control and severity, as well as their relative weight.

Methods: Within a consecutive series of outpatients visited in a three years period at the IBIM pediatric clinic, we selected 128 persistent asthmatics. A standardized medical interview was carried out to collect information on environmental risk factors, symptoms and comorbidities. Spirometry was performed using Pony FX, Cosmed, Italy; spirometric values were expressed as %pred using GLI-2012equation. Statistical analyses were performed by using R.

Results: The identifies a statistical model in which green nodes indicate response variables and light blue nodes indicate covariates. A link between two nodes suggests a strong relation between the corresponding variables whereas a missing link indicates no statistically significant relationship. To test predictive capacities of nodes we use ROC curves. AUC for GINA asthma control, asthma severity, and FEV1 were 0.68, 0.81 and 0.91, respectively. CONCLUSION Through a network analysis we were able to identify risk factors for asthma control, asthma severity, FEF2575 and FEV1. While Gina Severity, FEF2575 and FEV1 can be predicted quite well, Gina control is more difficult to be predicted to and further investigation seems to be necessary.

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Asthma control, severity and lung function impairment through network analysis in children
Antonio Abbruzzo, Giovanna Cilluffo, Laura Montalbano, Velia Malizia, Giuliana Ferrante, Roberta Antona, Stefania La Grutta
European Respiratory Journal Sep 2015, 46 (suppl 59) PA4515; DOI: 10.1183/13993003.congress-2015.PA4515

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Asthma control, severity and lung function impairment through network analysis in children
Antonio Abbruzzo, Giovanna Cilluffo, Laura Montalbano, Velia Malizia, Giuliana Ferrante, Roberta Antona, Stefania La Grutta
European Respiratory Journal Sep 2015, 46 (suppl 59) PA4515; DOI: 10.1183/13993003.congress-2015.PA4515
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More in this TOC Section

  • Measuring lung function in asthmatic children: A spirometry and forced oscillation technique (FOT) comparison
  • Effective patient selection for PCD diagnostics; the PICADAR score with nasal nitric oxide
  • Factors determining persistence of childhood persistent wheeze into young adulthood
Show more 7.6 Paediatric Respiratory Epidemiology

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