COVID-19 Pandemic: Analysis of Health Effects on Emergency Service Nursing Workers via a Qualitative Approach.

During the COVID-19 pandemic, longstanding issues involving nursing work, which has always involved significant risks of illness and infection, were intensified. It is necessary to acknowledge the risks and nurses' perceptions about the risks qualitatively during the period of the health crisis. The aim of this study was to examine the health repercussions perceived by nursing workers in emergency services during the outbreak of the COVID-19 pandemic in Brazil. This was a qualitative, descriptive, cross-sectional study. The settings of the study were emergency services with a national scope; the participants were nursing workers. Data were collected via face-to-face virtual calling interviews and analyzed via a content analysis technique, which was supported by IRAMUTEQ software. The formation of textual classes pointed in three thematic directions, from which three categories emerged: nursing workers' exposure, due to a lack of protective equipment, to the risk of being contaminated with, falling ill from, and transmitting the COVID-19 virus; changes in work environments, processes, and relations in response to the pandemic; and physical, mental, and psychosocial alterations perceived by emergency service nursing workers. The exposure to the virus, risk of contamination, and changes in the work environment and relations all resulted in health repercussions, which were perceived as physical, mental, and psychosocial alterations that were described as dietary disturbances, physical fatigue, burnout, increased smoking, anxiety, sleep alterations, fear, exhaustion, stress, social isolation, loneliness, distancing from relatives, and social stigma.

A Comparison of BUN/Albumin Ratio with PSI and CURB-65 for Predicting Mortality in COVID-19 Pneumonia in the Emergency Department

Introduction: The coronavirus disease-2019 (COVID-19) pandemic was the leading cause of high mortality and morbidity in the previous two years. Rapid determination of the severity of the disease is important in terms of reducing the intensity and initiating effective treatment. Although the pneumonia severity index (PSI) and CURB-65 classifications are widely employed to predict mortality and morbidity in patients diagnosed with pneumonia, biomarkers predicting the mortality and severity of COVID-19 in the emergency department (ED) are also needed. This study investigated the relationship between the blood urea nitrogen (BUN)/albumin ratio (BAR) and mortality and disease severity. Methods: Five hundred eighty-one patients presenting to the ED between March 2020 and January 2022 and diagnosed with COVID pneumonia were included in this observational study. Patients' BUN and albumin levels, and PSI and CURB-65 scores were calculated, and in-hospital mortality was recorded. The power of BAR in predicting mortality was compared with that of PSI and CURB-65 by using statistical analysis. Results: A significant association was determined between increased BAR and mortality. The area under the curve (AUC) value of BAR was 0.684, with 76.6% selectivity and 53.4% sensitivity at a cut-off point of 6.85. The CURB-65 score AUC value was 0.571, with 56% selectivity and 55.9% sensitivity at a cut-off point of 1.5. The AUC value for the PSI score was 0.609, with 63.3% selectivity and 50.3% sensitivity at a cut-off point of 107.5. Conclusion: BAR is a simple but independent marker of mortality and severity in COVID-19 viral pneumonia. [ FROM AUTHOR]

Application of Data Mining Technology-Based Nursing Risk Management in Emergency Department Care

Nursing risk refers to all unsafe events that may occur in clinical nursing work. Common risk events include bed fall, fall, scald, line dislodgement, drug extravasation, and drug administration error, which easily lead to nursing-patient disputes and seriously affect the prognosis of patients. In order to effectively avoid nursing risks, strengthening nursing risk management (NRM), improving nursing management mechanism, and improving nursing operation process have become effective ways to manage risks. The emergency department is an important window for rescuing critically ill patients in the hospital, and it is also the main department where diagnosis, nursing risk events, and medical disputes occur. The traditional risk care model has failed to meet the current demand for emergency patient management, and a more scientific and standardized management scheme is urgently needed. In order to improve the quality of NRM in emergency departments and combine the advantages and characteristics of big data-related technologies, this paper proposes an algorithm based on data mining for application in emergency care. The application of data mining in medical care is summarized and combined with the work content and requirements of hospital emergency care, and the application of big data in patient condition monitoring and early warning, medical and nursing staff scheduling, and patient emotional reassurance is discussed, and then, a solution for hospitals to optimize emergency care using data mining is proposed for the special characteristics of emergency care. Initially, the optimized solution is proposed to improve the efficiency and accuracy of patient condition monitoring and early warning, to improve the real-time scheduling of medical and nursing staff, and to solve medical care problems such as patient emotional calming. The analysis shows that the application of big data in emergency care can improve the efficiency of emergency ambulance, improve the doctor-patient relationship, and promote the development of emergency care. [ FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Emergency Department Overcrowding: Understanding the Factors to Find Corresponding Solutions.

It is certain and established that overcrowding represents one of the main problems that has been affecting global health and the functioning of the healthcare system in the last decades, and this is especially true for the emergency department (ED). Since 1980, overcrowding has been identified as one of the main factors limiting correct, timely, and efficient hospital care. The more recent COVID-19 pandemic contributed to the accentuation of this phenomenon, which was already well known and of international interest. Considering what would appear to be a trivial definition of overcrowding, it may seem simple for the reader to hypothesize solutions for what seems to be one of the most avoidable problems affecting the hospital system. However, proposing solutions to overcrowding, as well as their implementation, cannot be separated from a correct and precise definition of the issue, which must consider the main causes and aggravating factors. In light of the need of finding solutions that can put an end to hospital overcrowding, this review aims, through a review of the literature, to summarize the triggering factors, as well as the possible solutions that can be proposed.

Covid-19: As a Fear Factor in Response to Stroke Code and Other Interventional Radiology Emergencies?

The COVID-19 coronavirus crisis has posed an international challenge for all health systems. The first patient registered in Spain with the COVID-19 coronavirus was known on January 31, and the state of alarm was declared on March 14, 2020. The advance of the infection worldwide has caused a modification of the usual pattern in hospital emergency responses. This study describes the incidence of emergencies in the interventional radiology section of the Marqués de Valdecilla University Hospital and analyzes whether the presence of COVID-19 caused a decrease in the number of patients treated especially for ischemic strokes. A descriptive cross-sectional study was carried out on a sample of 236 patients treated at the interventional radiology on call between June 1, 2019 and May 10, 2020, at the Marqués de Valdecilla University Hospital. No specific results were found that indicate a decrease in the incidence of urgent procedures, especially mechanical thrombectomies in patients with ischemic strokes performed by the interventional radiology team since the establishment of the alarm state by COVID-19 in Cantabria. Patients' fear of contracting COVID-19 infection in the hospital environment has not led to a decrease in urgent procedures, especially for ischemic strokes.