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Mineral dust plays an important role in Earth system models and is linked to many components, including atmospheric wind speed, precipitation and radiation, surface vegetation cover and soil properties and oceanic biogeochemical systems. In this paper, the dust scheme in the first configuration of the United Kingdom Earth System Model UKESM1 is described, and simulations of dust and its radiative effects are presented and compared with results from the parallel coupled atmosphere–ocean general circulation model (GCM) HadGEM3-GC3.1. Not only changes in the driving model fields but also changes in the dust size distribution are shown to lead to considerable differences to the present-day dust simulations and to projected future changes. UKESM1 simulations produce a present-day, top-of-the-atmosphere (ToA) dust direct radiative effect (DRE – defined as the change in downward net flux directly due to the presence of dust) of 0.086 W m−2 from a dust load of 19.5 Tg. Under climate change pathways these values decrease considerably. In the 2081–2100 mean of the Shared Socioeconomic Pathway SSP5–8.45 ToA DRE reaches 0.048 W m−2 from a load of 15.1 Tg. In contrast, in HadGEM3-GC3.1 the present-day values of −0.296 W m−2 and 15.0 Tg are almost unchanged at −0.289 W m−2 and 14.5 Tg in the 2081–2100 mean. The primary mechanism causing the differences in future dust projections is shown to be the vegetation response, which dominates over the direct effects of warming in our models. Though there are considerable uncertainties associated with any such estimates, the results presented demonstrate both the importance of the size distribution for dust modelling and also the necessity of including Earth system processes such as interactive vegetation in dust simulations for climate change studies.

Theoretical models of the below-cloud scavenging (BCS) of aerosol by rain yield scavenging rates that are 1–2 orders of magnitude smaller than observations and associated empirical schemes for submicron-sized aerosol. Even when augmented with processes which may explain this disparity, such as phoresis and rear capture in the raindrop wake, the theoretical BCS rates remain an order of magnitude less than observations. Despite this disparity, both theoretical and empirical BCS schemes remain in wide use within numerical aerosol models. BCS is an important sink for atmospheric aerosol, in particular for insoluble aerosol such as mineral dust, which is less likely to be scavenged by in-cloud processes than purely soluble aerosol. In this paper, various widely used theoretical and empirical BCS models are detailed and then applied to mineral dust in climate simulations with the Met Office's Unified Model in order the gauge the sensitivity of aerosol removal to the choice of BCS scheme. We show that the simulated accumulation-mode dust lifetime ranges from 5.4 d in using an empirical BCS scheme based on observations to 43.8 d using a theoretical scheme, while the coarse-mode dust lifetime ranges from 0.9 to 4 d, which highlights the high sensitivity of dust concentrations to BCS scheme. We also show that neglecting the processes of rear capture and phoresis may overestimate submicron-sized dust burdens by 83 %, while accounting for modal widths and mode merging in modal aerosol models alongside BCS is important for accurately reproducing observed aerosol size distributions and burdens. This study provides a new parameterisation for the rear capture of aerosol by rain and is the first to explicitly incorporate the rear-capture mechanism in climate model simulations. Additionally, we answer many outstanding questions pertaining to the numerical modelling of BCS of aerosol by rain and provide a computationally inexpensive BCS algorithm that can be readily incorporated into other aerosol models.

Theoretical models of the below-cloud scavenging (BCS) of aerosol by rain yield scavenging rates that are 1–2 orders of magnitude smaller than observations and associated empirical schemes for submicron-sized aerosol. Even when augmented with processes which may explain this disparity, such as phoresis and rear-capture in the raindrop wake, the theoretical BCS rates remain an order of magnitude less than observations. Despite this disparity, both theoretical and empirical BCS schemes remain in wide use within numerical aerosol models. BCS is an important sink for atmospheric aerosol, in particular for insoluble aerosol such as mineral dust which is less likely to be scavenged by in-cloud processes than purely soluble aerosol. In this paper, various widely used theoretical and empirical BCS models are detailed and then applied to mineral dust in climate simulations with the Met Office’s Unified Model in order the gauge the sensitivity of aerosol removal to the choice of BCS scheme. We show that the simulated accumulation mode dust lifetime ranges from 5.4 days in using an empirical BCS scheme based on observations to 43.8 days using a theoretical scheme while the coarse mode dust lifetime ranges from 0.9 to 4 days, which highlights the high sensitivity of dust concentrations to BCS scheme. We also show that neglecting the processes of rear-capture and phoresis may overestimate submicron-sized dust burdens by 83 %, while accounting for modal widths and mode-merging in modal aerosol models alongside BCS is important for accurately reproducing observed aerosol size distributions and burdens. This study provides a new parameterisation for the rear-capture of aerosol by rain and is the first to explicitly incorporate the rear-capture mechanism in climate model simulations. Additionally, we answer many outstanding questions pertaining to the numerical modelling of BCS of aerosol by rain and provide a computationally inexpensive BCS algorithm that can be readily incorporated in other aerosol models.

INTRODUCTION: Albuterol can trigger supraventricular tachycardia (SVT). The clinical characteristics, incidence, and risk factors of SVT after inhaled SABA treatment in children are currently unknown. Through review of regional care delivery, we will describe cases of SVT during asthma treatment in hospital-based settings, define the incidence of SVT in our population, and evaluate risk factors of SABA-induced SVT. METHODS: We identified hospital-based care episodes of children 0–18 years old between 2006 and 2015 recorded in the Intermountain Healthcare EDW with either 1) diagnosis codes for both asthma and SVT or 2) both SABA and adenosine listed as billed medications. Controls were matched with cases by age and sex to determine risk factors for SVT after SABA using conditional logistic regression. RESULTS: Of 93 care episodes meeting criteria, we found 7 cases of SVT after SABA treatment in 6 patients over 10 years. In our population, the incidence of SVT is 3.9 per 10,000 episodes of SABA treatment, and 5.1 per 10,000 children with asthma receiving hospital-based asthma care. Two episodes of SVT followed treatment with only levalbuterol, three after only albuterol, and two after both albuterol and levalbuterol treatment. Five cases of SVT were converted to sinus rhythm with adenosine, one converted with synchronized electrical cardioversion, and one resolved spontaneously. No cases of SVT led to death. No examined variables were associated with SABA-induced SVT. CONCLUSIONS: SVT is rare during hospital-based treatment for acute asthma using inhaled SABAs and has low morbidity and mortality.

Previous studies have examined and identified demographic group score differences on United States Medical Licensing Examination (USMLE) Step examinations. It is necessary to explore potential etiologies of such differences to ensure fairness of examination use. Although score differences are largely explained by preceding academic variables, one potential concern is that item-level bias may be associated with remaining group score differences. The purpose of this 2019-2020 study was to statistically identify and qualitatively review USMLE Step 1 exam questions (items) using differential item functioning (DIF) methodology.Logistic regression DIF was used to identify and classify the effect size of DIF on Step 1 items meeting minimum sample size criteria. After using DIF to flag items statistically, subject matter expert (SME) review was used to identify potential reasons why items may have performed differently between racial and gender groups, including characteristics such as content, format, wording, context, or stimulus materials. USMLE SMEs reviewed items to identify the group difference they believed was present, if any; articulate a rationale behind the group difference; and determine whether that rationale would be considered construct relevant or construct irrelevant.All identified DIF rationales were relevant to the constructs being assessed and therefore did not reflect item bias. Where SME-generated rationales aligned with statistical differences (flags), they favored self-identified women on items tagged to women's health content categories and were judged to be construct relevant.This study did not find evidence to support the hypothesis that group-level performance differences beyond those explained by prior academic performance variables are driven by item-level bias. Health professions examination programs have an obligation to assess for group differences, and when present, investigate to what extent, if any, measurement bias plays a role.

Background The Infectious Diseases Society of America In-Training Examination (IDSA ITE) is a feedback tool used to help fellows track their knowledge acquisition during fellowship training. We determined whether the scores on the IDSA ITE and from other major medical knowledge assessments predict performance on the American Board of Internal Medicine (ABIM) Infectious Disease Certification Examination. Methods The sample was 1021 second-year fellows who took the IDSA ITE and ABIM Infectious Disease Certification Examination from 2008 to 2012. Multiple regression analysis was used to determine if ABIM Infectious Disease Certification Examination scores were predicted by IDSA ITE scores, prior United States Medical Licensing Examination (USMLE) scores, ABIM Internal Medicine Certification Examination scores, fellowship director ratings of medical knowledge, and demographic variables. Logistic regression was used to evaluate if these same assessments predicted a passing outcome on the certification examination. Results IDSA ITE scores were the strongest predictor of ABIM Infectious Disease Certification Examination scores (β = .319), followed by prior ABIM Internal Medicine Certification Examination scores (β = .258), USMLE Step 1 scores (β = .202), USMLE Step 3 scores (β = .130), and fellowship directors' medical knowledge ratings (β = .063). IDSA ITE scores were also a significant predictor of passing the Infectious Disease Certification Examination (odds ratio, 1.017 [95% confidence interval, 1.013-1.021]). Conclusions The significant relationship between the IDSA ITE score and performance on the ABIM Infectious Disease Certification Examination supports the use of the ITE as a valid feedback tool in fellowship training.

Provide counsel and support to women after a spontaneous abortion. Research indicates that many women will talk with their physician about their emotional distress and that physicians provide good information after the spontaneous abortion. Evaluate women for acute stress disorder (ASD) after a spontaneous abortion. Research found that women reporting physical, emotional, or sexual abuse are more likely to experience ASD. Patients should be assessed for post-traumatic stress disorder in follow-up visits 1 month after the initial visit. Research has found that up to 25% of women meet criteria for PTSD 1 month post the spontaneous abortion and 7% met criteria at 4 months. Physicians should refer women who are experiencing traumatic stress to a behavioral health professional.