Prevalence of Common Aeroallergens in Patients with Allergic Rhinitis in Gorgan, North of Iran, Based on Skin Prick Test Reactivity

Background Allergic rhinitis is one of the most common types of rhinitis. Allergen avoidance is the most important way of preventing this disease. The present study is carried out to determine the frequency of common aeroallergens in patients with allergic rhinitis in Gorgan city by skin prick test (SPT) reactivity. Materials and Methods  In this cross-sectional study 270 patients referring to the Asthma and Allergic Center in Gorgan city, Iran, were enrolled. Diagnosis of allergic rhinitis was confirmed by specialist asthma and allergy. A questionnaire containing demographic data and patient’s history was completed. Skin prick test containing standard allergen extracts, histamine, and physiologic serum was performed on patients. The data were analyzed using SPSS software version16.0. Results: In the present study, 270 patients (113 males and 157 females) had perennial allergic rhinitis (PAR), seasonal allergic rhinitis (SAR), and mixed allergic rhinitis (MAR) (n=166, 54, 47, receptivity). Out of these patients, the most common aeroallergens was a house dust mite called Dermatophagoides pteronyssinus (43.7%), other common allergen were: weeds (40.7%), Dermatophagoides farinae (40.4%), grasses (32.5%), beetles (30%), trees (22.5%), and molds (16.3%). There was a significant relationship between prevalence of allergy to grasses and gender (P=0.016), weeds and age (

Perancangan Fotografi Esai "Semarang City By The Sea" dengan Pendekatan Edfat

Abstrak Pelabuhan Tanjung Mas Semarang merupakan pelabuhan yang terbesar di Jawa Tengah dan menjadi pusat segala kegiatan ekonomi seperti impor dan ekspor barang dari dalam dan luar neger. Selain berbagai macam perusahaan berada di situ, pelabuhan Tanjung Mas juga menyediakan berbagai macam fasilitas untuk bisnis niaga seperti gudang peti kemas, alat-alat bongkar muat, kapal tandu. Aktifitas buruh yang kompleks itulah yang disajikan dalam karya-karya foto Semarang City by the Sea, fotografi esai nantinya akan menghadirkan dinamika buruh pelabuhan bersama dengan liku-liku yang dihadapinya setiap hari seperti pekerjaan bongkar muat, saat istirahat, saat berkumpul dengan rekan-rekan sesama buruh, rob, dan lain-lain. Berbagai macam fenomena tersebut akan direkam dalam sebuah Karya essai fotografi dengan metode EDFAT yang merupakan metode dasar dalam pengkaryaan fotografi jurnalistik. Kata kunci : Fotografi Esai, Tanjung Mas Semarang, EDFAT   Abstract The Port of Tanjung Mas Semarang is the largest port in Central Java and the center of all economic activities such as import and export of goods from within and abroad, Various companies are located there, the port of Tanjung Mas also provides various facilities for commercial business such as container warehouses, loading and unloading equipment, and ships. The complex worker activity that is presented in the photographs of Semarang City by the Sea. Essay photography will present the dynamics of the harbor worker along with the twists and turns that he faces every day such as loading and unloading work, during breaks, while gathering with fellow workers, floods, etc. Various kinds of phenomena will be recorded in a work of photography essay with EDFAT method which is the basic method in photography journalism Keyword : Essay photography, Tanjung Mas Semarang, EDFA

Cadangan penambahbaikan susun atur ruang perniagaan tingkat bawah di Kompleks Membeli-belah Warta, Bangi

Good facility layout involves preparation of material requirement, arrangement of physical equipment, and use of space in the best way to achieve maximum efficiency and smoothness. This study examines the layout practice of the ground floor area in Warta Shopping Complex in Bandar Baru Bangi and proposes a new layout to overcome the existing problems. Therefore, a number of visits and observations have been made on this facility, and issues and problems related to the layout was collected based on questionnaires distributed to 30 users. Then, a new layout suggestion is proposed and a visualisation environment is developed using the Google SketchUp software. A significant layout problem is related to crowded space that hinder visitors’ movement to shop around. Furthermore, basic facilities for customers such as chairs, information, and sign boards are not in a satisfying level. Facilities for disabled people, such as proper paths for those on wheel chairs and toilets, are not given enough attention by the management. Improvement to overcome these problems is proposed in a virtual environment. In this virtual environment, users could visualise the use of space, evaluate sales units relationship, ensure smoothness of visitors movement, and consider safety issue

What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask

International audienceCoincident with the tsunami of COVID-19–related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field

What every reader should know about studies using electronic health record data but may be afraid to ask

10.2196/22219Journal of Medical Internet Research233e2221

Multinational characterization of neurological phenotypes in patients hospitalized with COVID-19

International audienceAbstract Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January–September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7–7.8%, p FDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7–10.5%, p FDR < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19–25%), cerebrovascular diseases (24%, 13–35%), nontraumatic intracranial hemorrhage (34%, 20–50%), encephalitis and/or myelitis (37%, 17–60%) and myopathy (72%, 67–77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease

International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries

International audienceAdditional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients

Evolving phenotypes of non-hospitalized patients that indicate long COVID

International audienceAbstract Background For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been grueling with lingering effects. Many of the symptoms characterized as the post-acute sequelae of COVID-19 (PASC) could have multiple causes or are similarly seen in non-COVID patients. Accurate identification of PASC phenotypes will be important to guide future research and help the healthcare system focus its efforts and resources on adequately controlled age- and gender-specific sequelae of a COVID-19 infection. Methods In this retrospective electronic health record (EHR) cohort study, we applied a computational framework for knowledge discovery from clinical data, MLHO, to identify phenotypes that positively associate with a past positive reverse transcription-polymerase chain reaction (RT-PCR) test for COVID-19. We evaluated the post-test phenotypes in two temporal windows at 3–6 and 6–9 months after the test and by age and gender. Data from longitudinal diagnosis records stored in EHRs from Mass General Brigham in the Boston Metropolitan Area was used for the analyses. Statistical analyses were performed on data from March 2020 to June 2021. Study participants included over 96 thousand patients who had tested positive or negative for COVID-19 and were not hospitalized. Results We identified 33 phenotypes among different age/gender cohorts or time windows that were positively associated with past SARS-CoV-2 infection. All identified phenotypes were newly recorded in patients’ medical records 2 months or longer after a COVID-19 RT-PCR test in non-hospitalized patients regardless of the test result. Among these phenotypes, a new diagnosis record for anosmia and dysgeusia (OR 2.60, 95% CI [1.94–3.46]), alopecia (OR 3.09, 95% CI [2.53–3.76]), chest pain (OR 1.27, 95% CI [1.09–1.48]), chronic fatigue syndrome (OR 2.60, 95% CI [1.22–2.10]), shortness of breath (OR 1.41, 95% CI [1.22–1.64]), pneumonia (OR 1.66, 95% CI [1.28–2.16]), and type 2 diabetes mellitus (OR 1.41, 95% CI [1.22–1.64]) is one of the most significant indicators of a past COVID-19 infection. Additionally, more new phenotypes were found with increased confidence among the cohorts who were younger than 65. Conclusions The findings of this study confirm many of the post-COVID-19 symptoms and suggest that a variety of new diagnoses, including new diabetes mellitus and neurological disorder diagnoses, are more common among those with a history of COVID-19 than those without the infection. Additionally, more than 63% of PASC phenotypes were observed in patients under 65 years of age, pointing out the importance of vaccination to minimize the risk of debilitating post-acute sequelae of COVID-19 among younger adults

International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

International audienceAbstract Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach