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Objective: To investigate the wearing of masks and the knowledge of masks among high-risk positions for overseas import and pollution transmission. Methods: From May 14 to 17, 2022, a convenient sampling method was used to conduct an online survey among 963 workers in high-risk positions for overseas import and pollution transmission in Beijing. The behaviors of individual use and wearing masks, the distribution and supervision of the unit, the knowledge of personal mask protection and the subjective feelings of wearing masks were analyzed. The χ(2) test and logistic regression model were used to analyze the influencing factors of the correct selection of masks. Results: The majority of the workers in high-risk positions for overseas import and pollution transmission were male (86.0%, 828/963), age concentration in 18-44 years old (68.2%, 657/963), and the majority of them had college or bachelor degrees (49.4%, 476/963). 79.4%(765/963) of the workers chose the right type of masks, female, 45-59 years old and high school education or above were the risk factors for correct selection of masks (P <0.05). Workers had good behaviors such as wearing/removing masks, but only 10.5% (101/963) could correctly rank the protective effect of different masks. 98.4% (948/963) of the workers believed that their work units had provided masks to their employees, and 99.1% (954/963) and 98.2%(946/963) of them had organized training and supervision on the use of masks, respectively. 47.4%(456/963) of the workers were uncomfortable while wearing masks. Conclusion: The overall selection and use of masks among occupational groups in high-risk positions for overseas import and pollution transmission in China need to be further standardized. It is necessary to strengthen supervision and inspection on the use of masks among occupational groups, and take improvement measures to improve the comfort of wearing masks.
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Masks , Humans , Male , Female , Adolescent , Young Adult , Adult , Middle Aged , Cross-Sectional Studies , China , Surveys and Questionnaires , BeijingABSTRACT
AI and machine learning are increasingly often applied in the medical industry. The COVID-19 epidemic will start to spread quickly over the planet around the start of 2020. At hospitals, there were more patients than there were beds. It was challenging for medical personnel to identify the patient who needed treatment right away. A machine learning approach is used to predict COVID-19 pandemic patients at high risk. To provide input data and output results that execute the machine learning model on the backend, a straightforward Python Flask web application is employed. Here, the XGBoost algorithm, a supervised machine learning method, is applied. In order to predict high-risk patients based on their current underlying health issues, the model uses patient characteristics as well as criteria like age, sex, health issues including diabetes, asthma, hypertension, and smoking, among others. The XGBoost model predicts the patient's severity with an accuracy of about 98% after data pre-processing and training. The most important factors to the models are chosen to be age, diabetes, sex, and obesity. Patients and hospital personnel will benefit from this project's assistance in making timely choices and taking appropriate action. This will let medical personnel decide how much time and space to devote to the COVID-19 high-risk patients. providing a treatment that is both efficient and ideal. With this programme and the necessary patient data, hospitals may decide whether a patient need immediate care or not.
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Objective: Multiple major health organisations recommend the use of extracorporeal membrane oxygenation (ECMO) support for COVID-19-related acute hypoxaemic respiratory failure. Method(s): From march 2020 to november 2021 we done 108 veno-venous ECMO therapies. 35 patients required implantation immediately in intensive care unit in place of call by mobile ECMO team. Depend from distance of call it was used medical ambulance, rescue helicopter or medical plane. Result(s): In the first analyzed period (March-December 2020), 90-day mortality was 41%. 8 (7.6%) patients were discharged from the Intensive Care Unit. The remaining 3 (4.2%) were discharged home. 7 patients (6.6%) had both lung transplants. 7 patients (6.6%) required conversion to VV-A ECMO therapy due to the development of acute heart failure. Conclusion(s): In the analyzed period of March-December 2020, the mortality was 41%. As a result, the lower effect of regression of consolidation and inflammatory lesions of lung tissue indicates that ECMO therapy remains the treatment method in high-risk patients as a bridge therapy to lung transplantation.
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Aims: Children and adolescents were affected in various ways by the measures due to COVID-19 pandemic. The aims of this study were to investigate and compare the effects on mental health across age, to identify latent class trajectories of emotional and behavioural problems over 12-months and to examine the association of classes of trajectories with baseline demographic and clinical predictors. Method(s): Children (n = 1854) and adolescents (n = 1243) from the general population were assessed baseline, at 6-, 9-, and 12-month follow-up. They were eligible if they were residents in Austria, Germany, or Switzerland, were parents/caregivers of a child aged between 7 and 10 years or adolescents >=11 years, had sufficient German language skills and provided informed consent. Results and Conclusion(s): Significant age-effects were found regarding type and frequency of problems. While children had the largest increase in aggressive behaviours, adolescents reported the largest increase in emotional problems. Sociodemographic variables, exposure to and appraisal of COVID-19, psychotherapy before COVID-19 and parental mental health significantly predicted change in problemscores (F >= 3.69, p <= .001). Using growth mixture modelling, a oneclass solution was detected for the trajectory of aggressive behaviours and a two- and three-class solution for withdrawn/depression and anxiety/depression. A substantial proportion of children and adolescents experienced age-related mental health problems during the different stages of the COVID-19 pandemic. These results suggest that psychological problems of specific sub-groups should be monitored over the longer-term and interventions to improve communication, emotion regulation, and appraisal style should be offered to risk groups.
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The Covid-19 pandemic and Brexit have focused attention on the resilience of key sectors and firms. This paper explores the financial resilience of the 50 largest automotive firms in the West Midlands region of the UK in their response to disruption and economic shocks. The findings demonstrate that 22 firms are at high risk due to poor current liquidity ratios, with Coventry and Birmingham emerging as locations most susceptible to firm closures. High-risk firms include key flagship original equipment manufacturers operating at the downstream end of supply chains. If these firms were to fail, there would be a significant destructive impact on both the industry and the local economy. We assert an effective subnational industrial policy is required in order to support economic resilience in regions such as the West Midlands where a few firms account for a disproportionate share of employment and value-added.
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Objectives: Several populations are at greater risk of severe COVID-19 due to inadequate responses to COVID-19 vaccines. Many of these individuals, and their caregivers, continue practicing varying degrees of social isolation to avoid SARS-CoV-2 infection. Following the end of lockdowns, the behaviors and impacts of continued isolation on the quality-of-life of high-risk populations remain poorly understood. This study describes the main avoidance and protective behaviors and ongoing impacts experienced by adults and caregivers of adults at high-risk of severe COVID-19. Method(s): Four virtual focus groups (April-July 2022) were conducted with individuals at high-risk of severe COVID-19, or caregivers, recruited via a convenience sample from patient panels. A discussion guide of open-ended questions was prepared based on COVID-19 guidance documents and a literature review. For qualitative analyses, an inductive approach was used for behaviors, deductive for impacts. A pre-defined codebook was updated throughout as needed. Salient concepts were defined as those mentioned by >=30% of participants or in every focus-group session. Result(s): Fourteen participants were interviewed (12 patients, 2 caregivers). Participants highlighted continued behaviors greatly impacting their quality-of-life. Avoidance behaviors (staying home, avoiding bystanders, avoiding shopping facilities and gatherings, using delivery services, family protection [43%-64%]) and protective behaviors (masking [79%], vaccination [57%]) were reported. Negative impacts included family relationship impacts (71%), collapse of social relationships (57%), difficulties accessing healthcare (43%), anxiety, fear, loneliness and depression (36%-50%), and impacts on employment/finances (36%). Positive impacts included the advent of telehealth (57%) and recognizing family importance (36%). Lack of trust in authority (57%) and hoarding of medications (36%) were negative general impacts of the COVID-19 pandemic highlighted. Concepts reported by patients and caregivers were similar. Conclusion(s): Individuals at high-risk of severe COVID-19 and their caregivers maintained avoidance and protective behaviors similar to those reported during lockdowns. This study highlights the continued burden experienced by high-risk populations.Copyright © 2023
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Online public opinion warning for emergencies can help people understand the real situation, avoid panic, timely remind people not to go to high-risk areas, and help the government to carry out epidemic work.In this paper, key technologies of network public opinion warning were studied based on improved Stacking algorithm. COVID-19, herpangina, hand, foot and mouth, varicella and several emergency outbreaks were selected as public opinion research objects, and rough set was used to screen indicators and determine the final warning indicators.Finally, the warning model was established by the 50% fold Stacking algorithm, and the training accuracy and prediction accuracy experiments were carried out.According to the empirical study, the prediction accuracy of 50% Stacking is good, and the early warning model is practical and robust.This study has strong practicability in the early warning of the online public opinion of the sudden epidemic. © 2023 SPIE.
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We describe our experience with COVID-19 after pediatric liver transplantation (LT). In this study, we analyzed 18 of 196 children who contracted COVID-19 after LT during outpatient follow-up at our department. The severity of COVID-19 was mild in all cases, and all cases were cured without sequelae. COVID-19 after LT in children may have a high risk of severe disease. However, the disease is relatively mild and may be cured.Copyright © 2022 The Japan Society of Hepatology.
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Introduction: Lung cancer is third most common cancer and highest cause of cancer death in the UK. COPD and smoking are known cancer risk factors so early intervention is essential. Incidence is higher in areas of deprivation where early presentation is less likely and outcomes poorer. Middlesbrough has some of the highest areas of deprivation. Aim(s): To evaluate diagnostic value of CT screening pilot in detecting lung cancer and follow-up outcomes for patients with incidental finding of pulmonary nodules. Method(s): Between March 2019 - December 2022 17 GP practices in Middlesbrough were invited to offer non-contrast CT thorax to asymptomatic COPD patients eligible for review, aged 50-75 with 20 pack year history and QCancer risk >5%. Pulmonary nodules followed up as per BTS guidelines. This pilot was conducted in partnership and with support from the Northern Cancer Alliance. Result(s): 407 patients referred for CT, 312 met the criteria and enrolled. 5 (1.6% conversion rate) lung cancers, also 1 renal cancer diagnosed. 51 (17%) had features of pulmonary nodules or groundglass opacities and selected for follow up. 2 died from COVID infection before follow-up CT. 32 (62.8%) discharged after followup CT revealed stable appearances or resolution, follow-up CT still outstanding for 2. 4 (7.8%) selected for further follow-up of sub-solid, new or increasing nodules. 2 (3.9%) received radiological diagnosis of lung cancer and referred for radiotherapy, 1 underwent surgical resection revealing lung tumourlets and 1 referred for surgical resection of enlarging nodule. Conclusion(s): Pulmonary nodules consisted significant part of the CT screening pilot findings in COPD patients with significant further conversion rate to lung cancer diagnosis after follow-up. Therefore, CT screening of high-risk population in deprived areas has a role in detecting lung cancer and identifying pulmonary nodules, with a proportion of those later diagnosed as early lung cancer. Disclosure: No significant relationships.Copyright © 2023 Elsevier B.V.
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Aim: The purpose of this study is to create a scoring system to decide which patient will take maximum precautions while the covid 19 disease continues. Taking maximum precautions is not always possible in all surgical procedures. Therefore, surgical scoring in asymptomatic patients, selecting patients who need maximum precautions, and taking the necessary precautions for these patients will prevent unnecessary use of the equipment. Material(s) and Method(s): A total of 347 who were surgically treated for emergency or elective procedures between March 11 and November 11, 2020 were included in the study. Of these patients, 277 patients whose data could be accessed were included in the study. A scoring system has been created. Patients were divided into 2 groups: bearing low and high risk. Patients with a score above 10 were identified as having a high surgical risk, and those with a score below 10 were identified as having a low surgical risk. Result(s): There were 132 patients in Group 1 and 145 patients in Group 2. It was observed that 29 of 277 patients became positive within the first month. Two of these patients were in Group 1 and 27 of them were in Group 2. It was observed that COVID-19 antibody or PCR tests gave more positive results in patients in Group 2 in the first month compared to two patients in Group 1. The highest positivity rate in Group 2 was observed in the arthroscopy group. Discussion(s): Advanced precautions should be taken in patients with high surgical risk scores. In patients with low surgical risk scores, less strict precautions can be taken.Copyright © 2023, Derman Medical Publishing. All rights reserved.
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Introduction: The COVID-19 pandemic introduced a sudden need to decrease in-person visits. While many elective operations were postponed or canceled, GI cancers cases continued since treatment delay would risk disease progression. To mitigate contact risks, virtual postoperative visits replaced traditional encounters in the majority of patients. This study evaluates whether the shift to virtual postoperative visits increased hospital readmissions. Method(s): The Epic Clarity database was used to develop a retrospective cohort of patients undergoing inpatient oncologic operations. Readmission was compared Pre and Post-Covid with further analysis between Telehealth and In-Person subgroups in the Post- Covid cohort. A combination of univariate and multivariate logistic regressions was conducted on 30-day readmissions from the index admission. Result(s): The cohort consisted of 1,926 patients in the Pre- Covid timeframe and 1,064 patients in the Post-Covid, 699 (65.7%) Telehealth and 365 (34.3%) In-person follow-up visits. The readmission rate was 6.9% Pre-Covid and 7.2% Post-Covid (p=0.447) which did not change despite the shift to Telehealth. Those seen in-person Post-Covid visits were 46% more likely to be readmitted (p=0.026). Conclusion(s): Swift implementation of virtual clinics during the COVID-19 pandemic enabled video-based follow-up for the majority of GI oncology postoperative patients. Despite the high adoption of virtual follow-up visits, readmission rates did not increase. Further, higher readmissions in the Covid In-Person cohort suggest high-risk patients can effectively be identified and screened for in-person evaluation. Ongoing analysis is focused onidentifying a patient characteristic model for selecting appropriate postsurgical follow up.
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University students' mental health and wellbeing has been a global public health issue of increasing concern in recent years, with a growing body of empirical evidence suggesting university students are a 'very high-risk population' for mental disorders and psychological distress. Pre-existing mental health challenges among university students have consequently been compounded by the global COVID-19 pandemic. A sample of 20 students registered in the education faculty at a large urban university in South Africa participated in a Photovoice study. The research required them to capture three photos or images of their experiences of wellbeing during the pandemic. The findings showed that students experienced mental health concerns and disillusionment with higher education. Their wellbeing was associated with a sense of connection with themselves, their peers and the campus space, and the cultivation of resilience.
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Objectives: Efforts to combat COVID-19 have largely focused on vaccination and non-pharmaceutical interventions to decrease hospitalization and death and to reduce transmission. First generation COVID-19 direct-acting antivirals (DAAs) are only authorized for high-risk patients to reduce individual risk of disease progression. However, DAAs can also impact transmission by reducing viral load, thereby shortening the duration of infectivity. Next generation oral DAAs in development may have safety profiles that are amenable to broader eligibility and use. This analysis estimates the economic and clinical impact of increasing the utilization of DAAs to treat COVID-19. Method(s): A susceptible-infected-recovered-susceptible model was developed to estimate COVID-19-related outcomes based on DAA uptake. Cost-savings modeled included reduced healthcare utilization amongst individual patients and, importantly, potential savings attributable to reduced transmission. Cost inputs included treatment acquisition costs, adverse events, healthcare utilization, and productivity losses based on published literature. One million individuals were assessed with clinical and economic outcomes estimated for DAA adoption by risk level. Result(s): The model projects 402,330 new infections per 1 million individuals annually, leading to 6,000 hospitalizations and 107 deaths. By increasing DAA use by 10% in the high-risk population and 20% in the standard-risk population, infections decreased to 312,000, with 1,800 fewer hospitalizations and 34 fewer deaths. Decreases in medical encounters were driven by reduction in transmission (77% of the decrease) and reduction in severity amongst those treated (23% of the decrease). Among deaths averted, 72% were attributable to the reduction in transmission. Overall, costs decrease by 23.5% with increased treatment. Conclusion(s): This study is among the first to model the potential population-level impact of DAAs in reducing infectivity and transmission, a factor currently under-emphasized in the literature. New DAAs under development with potentially improved safety profiles may expand the uptake of treatment and substantially reduce the clinical and economic burden of COVID-19.Copyright © 2023
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Background. After the first wave of the new SARS-CoV-2 coronavirus infection, the researchers focused on identifying potential short-and long-term complications of COVID-19, especially in high-risk patients, after prolonged hospitalization and intensive care. Objective. To study the outcomes, adverse effects of severe COVID-19 and their predictors 90 days after hospital discharge in elderly patients with asthma. Material and methods. The study included elderly patients (101 subjects, 42 males and 59 females;median age 74 (67;79) years) with asthma, discharged from the hospital after treatment of severe COVID-19. They were followed up for 90 days after discharge. In the hospital, COVID-19 was confirmed by laboratory tests (polymerase chain reaction method) and/or clinically and radiologically. All patients had a documented history of asthma according to GINA 2020 criteria. Results and discussion. During the 90-day post-hospital follow-up, 86 (85%) patients survived, and 15 (15%) died after discharge. Deaths were reported within 1 to 4 weeks after discharge: 6 subjects died during re-hospitalization, 6 at home, and 3 in a rehabilitation center. The multivariate regression analysis model, adjusted for all statistically significant indicators, and the ROC analysis showed the most significant predictors of 90-day post-hospital mortality and their threshold values. They include the Charlson comorbidity index >=4 points, lung damage according to computed tomography >=30%, the absolute number of eosinophils <=100 cells/muL, and concomitant diabetes mellitus. The analysis showed that 90-day post-hospital mortality depends on combinations of identified risk factors;a combination of two, three, and especially four risk factors statistically significantly is associated with patients' lower average survival time. Conclusion. The key risk factors for 90-day post-hospital mortality in elderly patients with asthma after severe COVID-19 include the Charlson comorbidity index, lung damage >=30% according to computed tomography, the absolute number of eosinophils <=100 cells/muL, and concomitant diabetes mellitus. The 90-day post-hospital survival rate is correlated with the number of risk factors identified in patients. The effect of asthma severity on 90-day post-hospital mortality in elderly patients was not observed.Copyright © 2023, Media Sphera Publishing Group. All rights reserved.
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The proceedings contain 117 papers. The topics discussed include: informing local policy through an audit of the assessment, management and outcomes of intermediate and high-risk patients with pulmonary embolism;an initial exploration into the use of a novel virtual reality system to aid rehabilitation in intensive care;surprising chest radiograph- air in mediastinum;exploring tissue donation as part of end-of-life wishes- a duty of care following death on ICU?;the impact of deprivation on respiratory support unit outcomes in COVID-19 patients, and highlights from wave 2 data in Portsmouth;survey of attitudes towards end of life care as a tool in identifying areas for improvement;a quality improvement project regarding family communication within critical care;sleep promotion in a busy inner city high dependency unit;findings from a regional survey of critical care nursing staff focusing on retention and factors that influence wellbeing;and tracking functional recovery post critical illness.