  Pulmonary embolism (PE) and deep vein thrombosis (DVT) are gathered in venous
thromboembolism (VTE) and represent the third cause of cardiovascular diseases.
Recent studies suggest that meteorological parameters as atmospheric pressure,
temperature, and humidity could affect PE incidence but, nowadays, the
relationship between these two phenomena is debated and the evidence is not
completely explained. The clinical experience of the Department of Emergency
Medicine at AOUC Hospital suggests the possibility that a relationship
effectively exists. We have collected data concerning the Emergency Medicine
Unit admissions of PE patients to confirm our hypothesis. At the same time,
atmospheric parameters are collected from the Lamma Consortium of Tuscany
region. We have implemented new IT models and statistic tools by using
semi-hourly records of weather time high resolution data to process the
dataset. We have carried out tools from econometrics, like mobile means, and we
have studied anomalies through the search for peaks and possible patterns. We
have created a framework in Python to represent and study time series and to
analyze data and plot graphs. The project has been uploaded on GitHub. Our
analyses highlighted a strong correlation between the moving averages of
atmospheric pressure and those of the hospitalizations number (R= -0.9468,
p<0,001) although causality is still unknown. The existence of an increase in
the number of hospitalizations in the days following short-to-medium periods of
time characterized by a high number of half-hourly pressure changes is also
detected. The spectrograms studies obtained by the Fourier transform requires
to increase the dataset. The analyzed data (especially hospitalization data)
were too few to carry out this kind of analyses.
