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Objective: This study aimed to describe the effects of the various climate parameters on emergency room (ER) visits due to acute urinary retention (AUR). Patients and methods: This was a single-center retrospective analysis of the ER data of visits due to AUR in males and females between 2010 and 2017. We incorporated ER registries with data from the national meteorological service. Using multivariable logistic regression analyses, we assessed associations between climate parameters and the incidence of AUR. Results: A total of 1917 patients were admitted to the ER due to AUR during the study period, of whom 1706 (89%) were males and211 (11%) were females. Most AURs occurred in patients >70 years of age, with males on average being older than women (72.8 vs. 70.1 years old, p=0.01). Multivariable logistic regression analyses demonstrated that females had more AURs than men (odds ratio (OR)=1.3, 95% confidence interval (CI) 1.1–1.9, p=0.04) in spring. In all seasons except winter, a higher maximal temperature was associated with an increased risk of AUR, while in winter, a lower temperature was associated with an increased risk (OR=0.654, 95% CI 0.602–0.711, pConclusions: Our data suggest that weather parameters might be associated with an increased AUR incidence in a Mediterranean coastline area, with maximal ambient temperature, wind speed, heat index, and precipitation playing a potential role. Level of evidence: 6.

INTRODUCTION AND OBJECTIVE:The etiology of kidney stones is multi-factorial, with observed geographic and seasonal differences affecting the rate of stone formation. Multiple studies have reported ...

Numerical Weather Prediction (NWP) models with coarser resolution than ~4 km use convection parametrization to describe both deep and shallow convection. Convection permitting models with grid spacing below ~4 km usually describe deep convection on grid scale, but still parametrize the shallow convection, being sub-grid scale process. Many of these parametrizations are based on the mass-flux approach. The artificial combination of resolved and parametrized convection might deteriorate the model forecast skill, particularly precipitation. In this study, we are using the COSMO 2.5 km resolution limited area NWP model over the eastern Mediterranean region to analyze the effect of the mass-flux shallow convection parametrization (SCP) on the forecasts skill. We show that SCP entrainment rate, as well as restrictions on the shallow convection development height and maximum updraft speed, have a crucial effect on the forecasts of precipitation, temperature and moisture. Physically motivated tuning of these parameters can improve the model forecasts significantly. Finally, we estimate the climatic zones and seasons where SCP is expected to be particularly important for NWP.

Global climate changes affect health and present new challenges to healthcare systems. The aim of the present study was to analyze the pattern of visits to the medical wing of emergency rooms (ERs) in public hospitals during warm seasons, and to develop a predictive model that will forecast the number of visits to ERs 2 days ahead. Data on daily visits to the ERs of the four largest medical centers in the Tel-Aviv metropolitan area during the warm months of the year (April–October, 2001–2004), the corresponding daily meteorological data, daily electrical power consumption (a surrogate marker for air-conditioning), air-pollution parameters, and calendar information were obtained and used in the analyses. The predictive model employed a time series analysis with transitional Poisson regression. The concise multivariable model was highly accurate (r 2 = 0.819). The contribution of mean daily temperature was small but significant: an increase of 1°C in ambient temperature was associated with a 1.47% increase in the number of ER visits (P