A survey study on antibiotic prescription practices for acute asthma exacerbations: An European academy of allergy and clinical immunology task force report.

INTRODUCTION: Guidelines recommend treating asthma exacerbations (AAEs) with bronchodilators combined with inhaled and/or systemic corticosteroids. Indications for antibiotic prescriptions for AAEs are usually not incorporated although the literature shows antibiotics are frequently prescribed. AIM: To investigate the antibiotic prescription rates in AAEs and explore the possible determining factors of those practices. METHODS: A digital survey was created to determine the antibiotic prescription rates in AAEs and the influencing factors for the prescription practices. The survey was distributed among European academy of allergy and clinical immunology (EAACI) members by mass emailing and through regional/national societies in the Netherlands, Italy, Greece, and Poland. Furthermore, we retrieved local antibiotic prescription rates. RESULTS: In total, 252 participants completed the survey. Respondents stated that there is a lack of guidelines to prescribe antibiotics in AAEs. The median antibiotic prescription rate in this study was 19% [IQR: 0%-40%] and was significantly different between 4 professions: paediatrics 0% [IQR: 0%-37%], pulmonologists 25% [IQR: 10%-50%], general practitioners 25% [IQR: 0%-50%], and allergologists 17% [IQR: 0%-33%]) (p = 0.046). Additional diagnostic tests were performed in 71.4% of patients before prescription and the most common antibiotic classes prescribed were macrolides (46.0%) and penicillin (42.9%). Important clinical factors for health care providers to prescribe antibiotics were colorised/purulent sputum, abnormal lung sounds during auscultation, fever, and presence of comorbidities. CONCLUSION: In 19% of patients with AAEs, antibiotics were prescribed in various classes with a broad range among different subspecialities. This study stresses the urgency to compose evidence-based guidelines to aim for more rational antibiotic prescriptions for AAE.

Very high concentrations of birch pollen in the air of selected Polish cities in 2022 - clinical implications.

INTRODUCTION: In the Polish population, the most common cause of allergic rhinitis (AR) in the spring is birch pollen. AIM: The aim of this study was to assess the basic characteristics of the birch pollen season in selected cities in central and northern Poland including Warsaw, Piotrkow Trybunalski, and Bydgoszcz in 2022, considering their clinical implications. MATERIAL AND METHOD: Pollen monitoring was conducted using the volumetric method with the Hirst-type continuous volumetric sampler. Measurements were taken in 7-day cycles, and the microscopic analysis was performed for each 24-hour period. Results During the studied period, birch pollen posed a threat in the 2nd and 3rd decades of April and the 1st and 2nd decades of May. The birch pollination intensity was reflected by the very high values of maximum average daily pollen concentration 4102 pollen/m3 in Warsaw, 4389 pollen/m3 in Piotrkow Trybunalski, 3832 pollen/m3 in Bydgoszcz and the sum of the average daily pollen concentrations (i.e. Annual Pollen Integral, APIn) from 32439 in Bydgoszcz to 37638 in Warsaw, and long periods of exposure to high concentrations (2930 days). CONCLUSIONS: The pollen season 2022 is part of an alternating 2-year cycle of the birch pollen season intensity. The variability of parameters describing the dynamics of pollen seasons over years makes it necessary to monitor information on the pollen concentration in the air during the pollen season, both by the patients with inhalant allergy and their physicians.

The impact of data assimilation into the meteorological WRF model on birch pollen modelling.

We analyse the impact of ground-based data assimilation to the Weather Research and Forecasting (WRF) meteorological model on parameters relevant for birch pollen emission calculations. Then, we use two different emission databases (BASE - no data assimilation, OBSNUD - data assimilation for the meteorological model) in the chemical transport model and evaluate birch pollen concentrations. Finally, we apply a scaling factor for the emissions (BASE and OBSNUD), based on the ratio between simulated and observed seasonal pollen integral (SPIn) to analyse its impact on birch concentrations over Central Europe. Assimilation of observational data significantly reduces model overestimation of air temperature, which is the main parameter responsible for the start of pollen emission and amount of released pollen. The results also show that a relatively small bias in air temperature from the model can lead to significant differences in heating degree days (HDD) value. This may cause the HDD threshold to be attained several days earlier/later than indicated from observational data which has further impact on the start of pollen emission. Even though the bias for air temperature was reduced for OBSNUD, the model indicates a start for the birch pollen season that is too early compared to observations. The start date of the season was improved at two of the 11 stations in Poland. Data assimilation does not have a significant impact on the season's end or SPIn value. The application of the SPIn factor for the emissions results in a much closer birch pollen concentration level to observations even though the factor does not improve the start or end of the pollen season. The post-processing of modelled meteorological fields, such as the application of bias correction, can be considered as a way to further improve the pollen emission modelling.

Extension of WRF-Chem for birch pollen modelling-a case study for Poland.

In recent years, allergies due to airborne pollen allergens have shown an increasing trend, along with the severity of allergic symptoms in most industrialized countries, while synergism with other common atmospheric pollutants has also been identified as affecting the overall quality of citizenly life. In this study, we propose the state-of-the-art WRF-Chem model, which is a complex Eulerian meteorological model integrated on-line with atmospheric chemistry. We used a combination of the WRF-Chem extended towards birch pollen, and the emission module based on heating degree days, which has not been tested before. The simulations were run for the moderate season in terms of birch pollen concentrations (year 2015) and high season (year 2016) over Central Europe, which were validated against 11 observational stations located in Poland. The results show that there is a big difference in the model's performance for the two modelled years. In general, the model overestimates birch pollen concentrations for the moderate season and highly underestimates birch pollen concentrations for the year 2016. The model was able to predict birch pollen concentrations for first allergy symptoms (above 20 pollen m-3) as well as for severe symptoms (above 90 pollen m-3) with probability of detection at 0.78 and 0.68 and success ratio at 0.75 and 0.57, respectively for the year 2015. However, the model failed to reproduce these parameters for the year 2016. The results indicate the potential role of correcting the total seasonal pollen emission in improving the model's performance, especially for specific years in terms of pollen productivity. The application of chemical transport models such as WRF-Chem for pollen modelling provides a great opportunity for simultaneous simulations of chemical air pollution and allergic pollen with one goal, which is a step forward for studying and understanding the co-exposure of these particles in the air.