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[Background] Front-line medical staff are an important group in fighting against Coronavirus Disease 2019 (COVID-19), and their mental health should not be ignored. [Objective] This study investigates the current situation and influencing factors of post-traumatic stress disorder (PTSD) among front-line anti-epidemic medical staff during COVID-19 epidemic. [Methods] Medical staff who had participated in fighting against the COVID-19 epidemic wereselected from three grade III Class A hospitals and four grade II Class A hospitals in a city of Hubei Province by convenient sampling method in May 2020. The survey was conducted online using the Post-traumatic Stress Checklist-Civilian Version (PCL-C) as the main survey tool to investigate current situation and characteristics of PTSD among these participants. A total of 1120 questionnaires were collected, of which 1071 were valid, and the effective rate was 95.6%. [Results] Of the 1071 participants, the average age was (32.59+/-5.21) years;the ratio of male to female was 1: 5.02;the ratio of doctor to nurse was 1:5.8;nearly 70% participants came from grade III Class A hospitals;married participants accounted for 75.4%;most of them held a bachelor degree or above (86.5%);members of the Communist Party of China (CPC) accounted for 22.9%;50.9% had junior titles;the working years were mainly 5-10 years (42.8%);more than 80.0% participants volunteered to join the front-line fight;95.1% participants received family support;43.0% participated in rescue missions;78.1% participants fought the epidemic in their own hospitals;more than 60% participants considered the workload was greater than before;34.4% participants fought in the front-line for 2-4 weeks, and 23.5% participants did for more than 6 weeks. There were 111 cases of positive PTSD syndromes (PCL-C total score >=38) with an overall positive rate of 10.4%, and the scores of reexperience [1.40 (1.00, 1.80)] and hypervigilance [1.40 (1.00, 2.00)] were higher than the score of avoidance [1.14 (1.00, 2.57)]. The results of univariate analysis revealed that PTSD occurred differently among participants grouped by age, political affiliation, working years, anti-epidemic activities location, accumulated working hours in fighting against COVID-19, having child parenting duty, voluntariness, family support, whether family members participated in front-line activities, and rescue mission assignment (P<0.05). The results of logistic regression analysis showed that the incidence rates of reporting PTSD syndromes in medical personnel aged 31-40 years (OR=0.346, 95%CI: 0.164-0.730) and aged 41 years and above (OR=0.513, 95%CI: 0.319-0.823) were lower than that in those aged 20-30 years;the incidence rates of reporting PTSD syndromes in medical staff who were CPC members (OR=0.499, 95%CI: 0.274-0.909), volunteered to participate (OR=0.584, 95%CI: 0.360-0.945), and received family support (OR=0.453, 95%CI: 0.222-0.921) were lower than those did not (P<0.05);the incidence rates of reporting PTSD syndromes among medical workers who had child parenting duty (OR=2.372, 95%CI: 1.392-4.042), whose family members participated in front-line activities (OR=1.709, 95%CI: 1.135-2.575), and who participated in rescue missions (OR=1.705, 95%CI: 1.133-2.565) were higher than those who did not (P<0.05). [Conclusion] The positive PTSD syndrome rate is 10.4% in the front-line anti-epidemic medical staff. Age, political affiliation, voluntariness, family support, having child parenting duty, with a family members participating in the fight, and rescue mission assignment are the influencing factors of PTSD.Copyright © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.
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We report the case of a 65-year-old patient who was admitted during the COVID-19 pandemic to the intensive care unit for acute respiratory distress. Following a large meal the day before, she had recurrent episodes of vomiting, which were followed by intense retrosternal pain with progressively worsening dyspnea. The patient was admitted with initial suspicion of acute respiratory failure secondary to SARS-CoV-2 infection. However, after a careful anamnesis, the diagnosis of Boerhaave's syndrome was suggested. The aim of this article is to try to understand, through this clinical case of Boerhaave's syndrome, how this health crisis could influence the clinical reasoning of the physicians.Copyright © SRLF 2021.
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Since the outbreak of the COVID-19 in early 2020, the prevention and control of infectious diseases has been raised to a higher level. However, tuberculosis still ranks in the forefront of the incidence rate of various infectious diseases in China. The tuberculosis epidemic has also brought great economic pressure and negative social impact to the society every year. Therefore, we have always been very concerned about how to effectively prevent and control the spread of tuberculosis. However, the diagnostic data of tuberculosis are often high-dimensional, huge, messy and difficult to be used effectively. How to extract knowledge from the data to help medical staff find the incidence trend of tuberculosis to assist decision-making has become a practical topic. In this paper, after clarifying and standardizing the original data, the density peak clustering (DPC) algorithm is used for deep mining. The knowledge is extracted through clustering analysis and visualization. Finally, analysis results can intuitively illustrate the effectiveness and practical research significance of this work. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Background: Acute kidney injury (AKI) is a common complication of COVID-19 and is associated with poor outcomes. The aim of this study was to describe the incidence of AKI and to compare its clinical impact with other risk factors on the severity and outcomes of hospitalized COVID-19 patients. Method(s): We conducted a retrospective study on patients >= 18 years old who were admitted to our institution with a laboratory-confirmed diagnosis of COVID-19 infection from March 2020 to December 2020. Data on demographics, kidney function prior to and during hospitalization, inflammatory biomarkers, comorbidities, medications, and outcomes including mortality, mechanical ventilation (MV) and renal replacement therapy (RRT) were collect from electronic medical record. Definition and staging of AKI were based on the KDIGO guidelines. Survival and use of MV by AKI and AKI stage was analyzed using Chi-square test;strength of association was measured using correlation coefficients;and significance was assessed at p < 0.05. Result(s): Of 240 inpatients admitted for COVID-19, 153 (63.7%) survived to discharge. A total of 121 (50.4%) patients developed AKI during hospitalization: 43.7% stage 1, 34.5% stage 2, and 21.8% stage 3. Almost 1 in 4 patients with AKI (23.1%) required RRT. Fifty-eight (49.2% overall, 37.3%, 51.2%, and 70.8% for AKI stage 1, 2, and 3, respectively) patients with AKI required mechanical ventilation, compared to 15 (13.5%) with normal renal function (p< 0.001). Age, presence of AKI, AKI stage, history of coronary artery disease, and initial lactate dehydrogenase were significantly associated with in-hospital death. Development of AKI (r=0.33, p< 0.001) and AKI stage (r=0.38, p<0.001) were more strongly associated with in-hospital mortality than the remaining bivariate associations. Survival at discharge was strongly associated with renal function, with survival declining from 79.5% among patients with normal renal function to 61.5%, 41.5%, and 30.7% among AKI stage 1, 2, and 3 patients (p <0.001). Conclusion(s): AKI is more strongly associated with increased mortality among patients with COVID-19 infection compared with demographics, comorbidities, and inflammatory biomarkers. Patients with Stage 2-3 AKI are more likely to have greater severity and worse outcomes.
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Since the last century, animal viruses have posed great threats to the health of humans and the farming industry. Therefore, virus control is of great urgency, and regular, timely, and accurate detection is essential to it. Here, we designed a rapid on-site visual data-sharing detection method for the Newcastle disease virus with smartphone recognition-based immune microparticles. The detection method we developed includes three major modules: preparation of virus detection vectors, sample detection, and smartphone image analysis with data upload. First, the hydrogel microparticles containing active carboxyl were manufactured, which coated nucleocapsid protein of NDV. Then, HRP enzyme-labeled anti-NP nanobody was used to compete with the NDV antibody in the serum for color reaction. Then the rough detection results were visible to the human eyes according to the different shades of color of the hydrogel microparticles. Next, the smartphone application was used to analyze the image to determine the accurate detection results according to the gray value of the hydrogel microparticles. Meanwhile, the result was automatically uploaded to the homemade cloud system. The total detection time was less than 50 min, even without trained personnel, which is shorter than conventional detection methods. According to experimental results, this detection method has high sensitivity and accuracy. And especially, it uploads the detection information via a cloud platform to realize data sharing, which plays an early warning function. We anticipate that this rapid on-site visual data-sharing detection method can promote the development of virus selfchecking at home.
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Objective To explore the application and safety of apheresis technology in collection of Coronavirus Disease 2019 (COVID-19) convalescent plasma (CP), and to analyze the quality characteristics of the plasma. Methods The general data of COVID-19 convalescent plasma (CP) donors, including gender, age, date of discharge or release from medical isolation, were collected based on informed consent. After physical examination, the CP was collected by apheresis technology with plasma separator, inactivated with methylene blue, and determined for severe acute respiratory symptom Coronavirus 2 (SARS-CoV-2) nucleic acid and specific antibody (RBD-IgG) against SARS-CoV-2. Results The collection process went well, and no serious adverse events related to plasma collection were reported during or after the collection. The average age of COVID-19 CP donors was 38 years (n = 933). The distributions of blood groups A, B, AB and 0 in RhD (+) COVID-19 CP were 33. 4%, 29. 2%, 10% and 27. 2% respectively. The plasma donation date was 18 d from the discharge date in average. All the test results of SARS-CoV-2 nucleic acid in CP were negative, while the proportion of plasma samples at SARS-CoV-2 antibody titer of more than 1: 160 was 92. 60%. Conclusion Apheresis technology was safe and reliable. The COVID-19 CP contained high titer antibody. Large-scale collection and preparation of inactivated plasma against SARS-CoV-2 played an important role in the treatment of COVID-19.
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Under the influence of the COVID-19, consumers pay more and more attention to the safety and health of the air in the car. As the core component of the air purification in the car, the performance of the cabin air filter is a hot topic for vehicle enterprises and parts enterprises. This paper introduces the inspection and data analysis of cabin air filter products in China by China Automotive Technology And Research Center, which includes the product geographical distribution, brand compliance rate, the compliance rate of different testing items. Based on the analysis of fractional efficiency of 0.3 µm, 2.5 µm and 10 µm particle sizes and particle sizes distribution in the atmosphere, this paper puts forward the view that it is necessary to pay more attention to the fractional efficiency of particulates which below 1 µm. In addition, the existing problems of cabin air filter are studied by data and its development direction is prospected. © Published under licence by IOP Publishing Ltd.