Background and Purpose Primary spontaneous pneumothorax (PSP) tends to cluster. Previous studies have found a correlation between PSP and atmospheric pressure variations or thunderstorms. We conducted this study to analyze the PSP correlations with meteorological variables and the concentrations of air pollutants in the city of Cuneo in Italy (IT). Methods We evaluated prospectively 451 consecutive PSP patients treated between 2004 and 2010. For each day within the period analyzed, the meteorological parameters and pollutants data were recorded. Statistical analyses on PSP were done for distribution characteristics, spectral autocorrelation, and spectral analysis. Multivariate regression analyses were performed using artificial neural networks. Results Analysis of annual, seasonal, and monthly distributions showed no significant correlation between PSP and the time series. The spectral analysis showed that PSP events were not random. Correlations between meteorological and environmental variables confirmed that PSP was significantly more likely to occur on warm windy days with high atmospheric pressure and high mean nitrogen dioxide concentration. Conclusions Meteorological parameters and atmospheric pollutants might explain the cluster onset of PSP.
Analysis of spontaneous pneumothorax in the city of Cuneo: environmental correlations with meteorological and air pollutant variables
BERTOLACCINI, Luca;CASSARDO, Claudio
2015-01-01
Abstract
Background and Purpose Primary spontaneous pneumothorax (PSP) tends to cluster. Previous studies have found a correlation between PSP and atmospheric pressure variations or thunderstorms. We conducted this study to analyze the PSP correlations with meteorological variables and the concentrations of air pollutants in the city of Cuneo in Italy (IT). Methods We evaluated prospectively 451 consecutive PSP patients treated between 2004 and 2010. For each day within the period analyzed, the meteorological parameters and pollutants data were recorded. Statistical analyses on PSP were done for distribution characteristics, spectral autocorrelation, and spectral analysis. Multivariate regression analyses were performed using artificial neural networks. Results Analysis of annual, seasonal, and monthly distributions showed no significant correlation between PSP and the time series. The spectral analysis showed that PSP events were not random. Correlations between meteorological and environmental variables confirmed that PSP was significantly more likely to occur on warm windy days with high atmospheric pressure and high mean nitrogen dioxide concentration. Conclusions Meteorological parameters and atmospheric pollutants might explain the cluster onset of PSP.File | Dimensione | Formato | |
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