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.
Asthma control, severity and lung function impairment through network analysis in children
Giovanna Cilluffo;Laura Montalbano;Velia Malizia;Stefania La Grutta
2015
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
