Neural networks analysis of spontaneous pneumothorax development

Luca Bertolaccini, Lucia Boschetto, Claudio Cassardo, Andrea Viti1,Alberto Terzi

Author address: 

Thoracic Surgery, S. Croce e Carle Hospital, Cuneo, Italy

Abstract: 

Spontaneous pneumothoraces (SP) tend to cluster. Correlations between SP and atmospheric variations were reported by previous studies. In our work SP correlation with meteo variables and air pollutants in Cuneo County was analyzed. 2004-2010, 451 SP patients were prospectively evaluated. For each day of analyzed period, meteo parameters and pollutants were recorded. Statistics on SP evaluated distribution characteristics, spectral autocorrelation and spectral analysis; multivariate regression techniques were performed using artificial neural networks. Analysis of seasonal distributions showed no significant correlation. Spectral analysis showed that SP events were not random. Correlations between meteoenvironmental variables were analyzed through linear tests. SP occurrence significantly increases in warm windy days with high atmospheric pressure and high NO2 concentration. These data don’t affect SP treatment; nevertheless, they add information on SP tendency to cluster.
2012

abstract No: 

183

Full conference title: 

European Respiratory Society Annual Congress
    • ERS 22nd (2012)