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.
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http://dx.doi.org/10.1007/s00595-014-1014-1 | DOI Listing |
Eur Heart J Acute Cardiovasc Care
January 2025
Department of Emergency Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen 518035, Guangdong, China.
Background: We aimed to analyze the yet unclear correlation between air pollutant concentrations (AP) and out-of-hospital cardiac arrest (OHCA) in Shenzhen, China.
Methods: A 5-year time series analysis of all OHCA events reported to the Shenzhen Emergency Center was conducted. Quasi-Poisson regression, controlling for meteorological variables (daily mean relative temperature and humidity) with multivariable fractional polynomial and using Fourier series to adjust for long-term trends and account for periodic patterns, was used to assess the association among particulate matter of 2.
Environ Toxicol Chem
January 2025
Department of Environmental Engineering, Faculty of Engineering, Bursa Uludag University, 16059 Nilüfer/Bursa-Türkiye.
This study evaluates atmospheric polycyclic aromatic hydrocarbon (PAH) concentrations in a semi-urban area, Görükle, Turkey, from June 2021 to February 2022. The average concentration of ∑16 PAHs was 24.85 ± 19.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China.
Vegetation assimilation of atmospheric gaseous elemental mercury (GEM) represents the largest dry deposition pathway in global terrestrial ecosystems. This study investigated Hg accumulation mechanisms in deciduous broadleaves and evergreen needles, focusing on how ecophysiological strategies─reflected by δC, δO, leaf mass per area, and leaf dry matter content-mediated Hg accumulation. Results showed that deciduous leaves exhibited higher total Hg (THg) concentrations and accumulation rates (THg), which were 85.
View Article and Find Full Text PDFSci Rep
January 2025
Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany.
The global burden of dengue disease is escalating under the influence of climate change, with India contributing a third of the total. The non-linearity and regional heterogeneity inherent in the climate-dengue relationship and the lack of consistent data makes it difficult to make useful predictions for effective disease prevention. The current study investigates these non-linear climate-dengue links in Pune, a dengue hotspot region in India with a monsoonal climate and presents a model framework for predicting both the near-term and future dengue mortalities.
View Article and Find Full Text PDFJ Biomed Inform
January 2025
Department of Computer Science, University of Idaho, Moscow, ID 83844, United States of America. Electronic address:
Coccidioidomycosis (cocci), or more commonly known as Valley Fever, is a fungal infection caused by Coccidioides species that poses a significant public health challenge, particularly in the semi-arid regions of the Americas, with notable prevalence in California and Arizona. Previous epidemiological studies have established a correlation between cocci incidence and regional weather patterns, indicating that climatic factors influence the fungus's life cycle and subsequent disease transmission. This study hypothesizes that Long Short-Term Memory (LSTM) and extended Long Short-Term Memory (xLSTM) models, known for their ability to capture long-term dependencies in time-series data, can outperform traditional statistical methods in predicting cocci outbreak cases.
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