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1.
Preprint in English | EuropePMC | ID: ppcovidwho-291207

ABSTRACT

Since the emergence of Corona Virus Disease 2019 (COVID-19) in Wuhan city, Hubei Province, China, it has caused thousands of deaths. As the ongoing outbreak of COVID-19 around the world, the number of deaths will definitely continue to increase. We aimed to further describe the clinical characteristics of dead cases with COVID-19 through a large sample and multi-centered study and to find some clinical predictors for the deterioration of COVID-19 during the process. Methods One hundred and seven patients (16 patients from Lei Shen-Shan Hospital, 54 patients from Seventh Hospital of Wuhan and 37 patients from Zhongnan Hospital of Wuhan University) with COVID-19 were enrolled in our research from Jan 22 to Feb 29, 2020. The demographic, clinical, radiological, laboratory and treatment data of all cases were analysed. Results Of the 107 dead patients with COVID-19, 71 (66.4%) were male and 36 (33.6%) were female. The mean age of the patients was 71.2 ± 12.1 years. 82 (76.6%) of patients had chronic diseases. The mean duration from admission to death was 9 (IQR,5-14) days. Respiratory functional damage was the most common one followed by heart and kidney. Hematuria was found in 36(33.6%) patients. 89(83.2%) patients’ albumin levels were decreased. 68(63.6%) patients had anemia. concerning laboratory results, 55 (69.6%) and 56 (70.1%) patients have the elevated white blood cells and elevated Neutrophils during the process;only 43 (54.4%) have the decreased Lymphocytes;The values of platelets and haemoglobin decreased in 64(81.0%) and 58 (73.4%) patients. Alanine aminotransferase and aspartate aminotransferase elevated in near half of patients, while almost 80% of patients have the decreased albumin. The elevated blood urea nitrogen and cystatin C were manifested in about 70% of patients. Procalcitonin was elevated in 38 (71.7%) patients. Conclusions In conclusion, the older men with chronic diseases are more likely to die from COVID-19. Apart from that, more attention should be pay on timely treatment, coinfections, malnutrition, and dysfunction of kidney and coagulation. The rising values (white blood cell, blood urea nitrogen, cystatin C, PCT and PT) and the decreased values (PLT, Hb and albumin) maybe meaningful for predict the poor prognosis.

2.
Preprint in English | EuropePMC | ID: ppcovidwho-291206

ABSTRACT

The novel coronavirus (COVID-19) pandemic started in December 2019 in Wuhan (Hubei, China) and spread rapidly;therefore, it is essential to detect the disease at an early stage and immediately isolate the infected patients [1]. The most common symptoms of COVID-19 infection include fever, asthenia, cough and dyspnea [2]. However, some patients are asymptomatic from the respiratory symptoms, and may only present abdominal manifestations as an initial finding, what creates a diagnostic challenge.We describe two cases with diagnostic confirmations of COVID-19 who showed up at the Emergency Department with abdominal symptoms before presenting respiratory manifestations, and who had their initial suspicion based on the findings of the thoracoabdominal transition, demonstrating the importance of an adequate assessment of the lung base images.

3.
Preprint in English | EuropePMC | ID: ppcovidwho-291205

ABSTRACT

Background: The outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread all over the world. The specific information about immunity of non-survivors with COVID-19 is scarce. We aimed to describe the clinical characteristics and abnormal immunity of the confirmed COVID-19 non-survivors. Methods: In this single-centered, retrospective, observational study, we enrolled 125 patients with COVID-19 who were died between Jan, 13 and Mar 4, 2020 from Renmin Hospital of Wuhan University. 414 randomly recruited patients with confirmed COVID-19 who were discharged from the same hospital during the same period served as control. Demographic and clinical characteristics, laboratory findings and chest computed tomograph results at admission, and treatment were collected. The immunity-related risk factors associated with in-hospital death were detected. Results: Non-survivors were older than survivors. More than half of non-survivors was male. Nearly half of the patients had chronic medical illness. The common signs and symptoms at admission of non-survivors were fever. Non-survivors had higher white blood cell (WBC) count, more elevated neutrophil count, lower lymphocytes and platelete count, raised concentration of procalcitonin and C-reactive protein (CRP) than survivors. The levels of CD3 + T cells, CD4 + T cells, CD8 + T cells, CD19 + T cells, and CD16 + 56 + T cells were significantly decreased in non-survivors when compared with survivors. The concentrations of immunoglobulins (Ig) G, IgA and IgE were increased, whereas the levels of complement proteins (C)3 and C4 were decreased in non-survivors when compared with survivors. Non-survivors presented lower levels of oximetry saturation at rest and lactate. Old age, comorbidity of malignant tumour, neutrophilia, lymphocytopenia, low CD4 + T cells, decreased C3, and low oximetry saturation were the risk factors of death in patients with confirmed COVID-19. The frequency of CD4 + T cells positively correlated with the numbers of lymphocytes and the level of oximetry saturation, whereas CD4 + T cells were negatively correlated with age and the numbers of neutrophils. Conclusion: Abnormal cellular immunity and humoral immunity were considerable in non-survivors with COVID-19. Neutrophilia, lymphocytopenia, low CD4 + T cells, and decreased C3 were the immunity-related risk factors predicting mortality of patients with COVID-19.

4.
Preprint in English | EuropePMC | ID: ppcovidwho-291204

ABSTRACT

A novel coronavirus (2019-nCoV) that is initially found to trigger human severe respiratory illness in Wuhan City of China, 2019, has been recognized as a public health emergency of international concern. In the past two months, this deadly agent has caused 77,785 cases with 2,666 deaths via rapid person-to-person transmission and reached at least 25 countries. However, its evolutionary origin is poorly understood. Here we show integrative evidence that 2019-nCoV is a possible progenitor for SARS-CoV with bat origin. Our finding underscores the importance of tracing origin in the efficient monitoring, and effectively preventing the interspecies transmission of such emerging/re-emerging coronaviruses.

5.
Preprint in English | EuropePMC | ID: ppcovidwho-291202

ABSTRACT

Research significance: The extended version of this paper has been accepted by IEEE Internet of Things journal (DOI: 10.1109/JIOT.2020.2991456), please cite the journal version. During the epidemic prevention and control period, our study can be helpful in prognosis, diagnosis and screening for the patients infected with COVID-19 (the novel coronavirus) based on breathing characteristics. According to the latest clinical research, the respiratory pattern of COVID-19 is different from the respiratory patterns of flu and the common cold. One significant symptom that occurs in the COVID-19 is Tachypnea. People infected with COVID-19 have more rapid respiration. Our study can be utilized to distinguish various respiratory patterns and our device can be preliminarily put to practical use. Demo videos of this method working in situations of one subject and two subjects can be downloaded online. Research details: Accurate detection of the unexpected abnormal respiratory pattern of people in a remote and unobtrusive manner has great significance. In this work, we innovatively capitalize on depth camera and deep learning to achieve this goal. The challenges in this task are twofold: the amount of real-world data is not enough for training to get the deep model;and the intra-class variation of different types of respiratory patterns is large and the outer-class variation is small. In this paper, considering the characteristics of actual respiratory signals, a novel and efficient Respiratory Simulation Model (RSM) is first proposed to fill the gap between the large amount of training data and scarce real-world data. The proposed deep model and the modeling ideas have the great potential to be extended to large scale applications such as public places, sleep scenario, and office environment.

6.
Preprint in English | EuropePMC | ID: ppcovidwho-291201

ABSTRACT

A 1900-2016 time series model predicts former Vice President Joe Biden will win 55.44 percent of the 2020 US presidential popular vote. A change in party control of the U.S. House of Representatives two years before a presidential election has a significant coefficient to explain the popular vote that has not been explored in the past 25 years. A cross-section 50 state Electoral College probit model projects President Trump’s reelection, winning 26 states with 279 electoral votes while Biden receives 259. These popular vote and electoral vote forecasts surely have wide discrepancies. Biden is forecast to win the Electoral College vote under several circumstances. If he wins Wisconsin’s 10 electoral votes, which are predicted for Trump, the candidates could tie with 269 electoral votes and the House of Representatives would select the president. Biden would be elected if he wins Wisconsin and the popular vote in one Congressional district in Nebraska or both districts in Maine. Biden could win with victories in several states where he is forecast to lose close contests. Numbers of COVID-19 virus cases and deaths are not highly correlated with states where Trump is projected to win. The effects of factors such as the President’s health and candidates’ closing campaign behavior cannot be measured. Forecasting US presidential outcomes in the 21st century has become a highly risky activity.

7.
Preprint in English | EuropePMC | ID: ppcovidwho-291200

ABSTRACT

A 1900-2016 time series model predicts former Vice President Joe Biden will win 55.44 percent of the 2020 US presidential popular vote. A change in party control of the U.S. House of Representatives two years before a presidential election has a significant coefficient to explain the popular vote that has not been explored in the past 25 years. A cross-section 50 state Electoral College probit model projects President Trump’s re-election, winning 26 states with 279 electoral votes while Biden receives 259. These popular vote and electoral vote forecasts surely have wide discrepancies.<br><br>Biden is forecast to win the Electoral College vote under several circumstances. If he wins Wisconsin’s 10 electoral votes, which are predicted for Trump, the candidates could tie with 269 electoral votes and the House of Representatives would select the president. Biden would be elected if he wins Wisconsin and the popular vote in one Congressional district in Nebraska or both districts in Maine. Biden could win with victories in several states where he is forecast to lose close contests. Numbers of COVID-19 virus cases and deaths are not highly correlated with states where Trump is projected to win. The effects of factors such as the President’s health and candidates’ closing campaign behavior cannot be measured. Forecasting US presidential outcomes in the 21st century has become a highly risky activity.<br>

8.
Preprint in English | EuropePMC | ID: ppcovidwho-291198

ABSTRACT

2020 has been highly affected by the COVID-19 outbreak. The urgent needs for a potent and effective drug for treatment of this malignance put pressure on researchers and scientists worldwide to develop potential drug or a vaccine to resist SARS-CoV-2. We report in this paper the assessment of the efficiency of thirty alkaloid compounds derived from African medicinal plants against the SARS-CoV-2 main protease through molecular docking and bioinformatics approaches. The results reveal four potential inhibitors (ligands 18 , 21 , 23 and 24 ) with the highest binding energies up to 12.26 kcal/mol with good profile of ADMET, as well as fully obey the Lipinski’s rule of five.

9.
Preprint in English | EuropePMC | ID: ppcovidwho-291195

ABSTRACT

Noncovalent interaction energetics associated with ACE2 affinity differences are investigated using electronic structure methods;Our results were found to challenge previous predictions – claiming a higher affinity for 2019-nCoV compared to SARS-CoV based merely on "chemical intuition". In addition, we demonstrate that a broadly-used classical molecular dynamics force field – MMFF94 – is clearly incapable of reproducing DFT-based noncovalent interaction energetics for the systems at hand (despite being specifically parameterized for van der Waals interactions).

10.
Preprint in English | EuropePMC | ID: ppcovidwho-291190

ABSTRACT

Contact tracing is an important measure to counter the COVID-19 pandemic. In the early phase, many countries employed manual contact tracing to contain the rate of disease spread, however it has many issues. The manual approach is cumbersome, time consuming and also requires active participation of a large number of people to realize it. In order to overcome these drawbacks, digital contact tracing has been proposed that typically involves deploying a contact tracing application on people's mobile devices which can track their movements and close social interactions. While studies suggest that digital contact tracing is more effective than manual contact tracing, it has been observed that higher adoption rates of the contact tracing app may result in a better controlled epidemic. This also increases the confidence in the accuracy of the collected data and the subsequent analytics. One key reason for low adoption rate of contact tracing applications is the concern about individual privacy. In fact, several studies report that contact tracing applications deployed in multiple countries are not privacy friendly and have potential to be used for mass surveillance by the concerned governments. Hence, privacy respecting contact tracing application is the need of the hour that can lead to highly effective, efficient contact tracing. As part of this study, we focus on various cryptographic techniques that can help in addressing the Private Set Intersection problem which lies at the heart of privacy respecting contact tracing. We analyze the computation and communication complexities of these techniques under the typical client-server architecture utilized by contact tracing applications. Further we evaluate those computation and communication complexity expressions for India scenario and thus identify cryptographic techniques that can be more suitably deployed there.

11.
Preprint in English | EuropePMC | ID: ppcovidwho-291189

ABSTRACT

The present study aims to screen the different phytoconstituents and drugs for potential treatment of the corona virus COVID-19 and for specificity through virtual screening. The plant molecules selected were based upon traditional knowledge and are prescribed in the Indian system of medicine for infectious/ respiratory conditions. The three target proteins selected for the study are 3CLpro, PLpro, and SPIKE. These proteins have defined pathological roles in disease transmission. The virtual screening was carried out in these proteins using the GLIDE Schrödinger Maestro software version 11.9.011. The efficacy was assessed by the calculated G-score of the ligand interaction with the amino acid side chains of the ligand binding domain. Molecules such as saponarin, mangiferin, and hesperidin exhibited better G-score with 3CLpro and PLpro. Similarly, diphyllin and tuberculatin exhibited better G-score for SPIKE protein. The reference anti malarial drug hydroxychloroquine showed better interactions with 3CLpro and PLpro. Similarly, protease inhibitors and antiviral drugs have shown interaction with 3CLpro specific protease protein. Interestingly, SPIKE protein ligands, diphyllin and tuberculatin from Justicia adhatoda (vasaka), were found to be unique and did not show affinity to protease inhibitor. It can be concluded, that the molecules having flavone scaffolds show better binding affinity with protease proteins 3CLpro and PLpro. SPIKE protein scaffold is different and showed better binding affinity with molecules having naptho-furan ring. The traditionally used plant phytoconstituents did not exhibit good binding affinity;however, we believe that a combination of these herbs might induce human immune system against microbial infection.

12.
Preprint in English | EuropePMC | ID: ppcovidwho-291185

ABSTRACT

The pandemic outbreak of COVID-19 had begun in March of 2020 on a global scale. This outbreak has originated numerous questions for society and many challenges for public managers. The disease is worrying because it has a high propagation velocity, high lethality levels, and there is no cure. Some groups are considered more vulnerable due to pre-existing disease conditions, age-range, and living conditions. In Latin American countries, people live in different conditions than those who live in countries located in the North hemisphere, such as climatic conditions, less favorable socioeconomic conditions, different educational levels, inequality, precarious urban infrastructure, etc. These factors generate even more concern and uncertainty about the pandemic than in developed countries. This study aimed, although preliminarily, to identify areas of great socio-spatial vulnerability and susceptibility of infection of people over 60 years old of COVID-19 in Brasília, Brazil. In this research, publicly available data and information about the population characteristics and social aspects were used, all connected directly to the census sectors. With the support of Geographic Information System (GIS), a matrix was used to cross-check the data and, thereby, achieve the objective of identifying the most vulnerable sectors for people aged over 60 years old. The results point out to more than 400 census sectors classified as Extremely Vulnerable in Brasília and it should be the object of special attention for public managers to do specific health care actions.

13.
Preprint in English | EuropePMC | ID: ppcovidwho-291184

ABSTRACT

Pigs ( Sus scrofa ) may be important surveillance targets for risk assessment and risk-based control planning against emerging zoonoses. Pigs have high-contact rates with humans and other animals, transmit similar pathogens as humans including CoVs, and serve as reservoirs and intermediate hosts for notable human pandemics.Wild and domestic pigs both interface with humans and each other but have unique ecologies that demand different surveillance strategies. Three fundamental questions shape any surveillance program: where, when, and how can surveillance be conducted to optimize the surveillance objective? Using theory of mechanisms of zoonotic spillover and data on risk factors, we propose a framework for determining where surveillance might begin initially to maximize a detection in each host species at their interface. We illustrate the utility of the framework using data from the United States. We then discuss variables to consider in refining when and how to conduct surveillance. Recent advances in accounting for opportunistic sampling designs and in translating serology samples into infection times provide promising directions for extracting spatio-temporal estimates of disease risk from typical surveillance data. Such robust estimates of population-level disease risk allow surveillance plans to be updated in space and time based on new information (adaptive surveillance) thus optimizing allocation of surveillance resources to maximize the quality of risk assessment insight.

14.
Preprint in English | EuropePMC | ID: ppcovidwho-291183

ABSTRACT

The COVID-19 pandemic is having an impact on physical and mental health. Most studies report the impact on mental health and mental distress during the pandemic. As a result of various stressors (such as lockdown, quarantines, and misinformation) there is heightened fear of a pandemic. The sufferer may experience a variety of symptoms of anxiety, depression, and even psychosis. In predisposed vulnerable individuals, fear of COVID-19 is perpetuating pain and dysfunction. This study discussed the ABC framework of fear and influencer to better understand the different levels of symptoms and interventions. There is an urgent need to integrate mental health into primary health-care centers. The attending physician should be aware of the stress disorders associated with the pandemic. This article introduces a handy and practical portrayal of the ABC framework that can be taught to individuals in distress during clinical visits to primary care centers providing awareness of the relationship between thinking, emotional and behavioral responses.

15.
Preprint in English | EuropePMC | ID: ppcovidwho-291182

ABSTRACT

Purpose: Many commonly used mask designs are secured by elastic straps looping around the posterior auricular region. This constant pressure and friction against the skin may contribute to increased wearer pain, irritation, and discomfort. The purpose of this work is to report a modified 3D printed mask extender to alleviate discomfort and increase mask wearability by relieving posterior auricular pressure from isolation masks.Methods : Our institutional review board designated this project as non-human research and exempt. As part of resourcing 3D printing laboratories along with individual 3D printers to provide resources to healthcare workers, mask extenders were printed to relieve posterior auricular pressure from individuals wearing isolation masks. The authors modifed an existing mask extender, increasing its length with accompanying peripheral rungs for isolation mask securement. 3D printing was performed with Ultimaker S5 (Ultimaker B.V.;Geldermalsen, Netherlands) and CR-10 (Creality3D;Shenzhen, China) 3D printers using polylactic acid filaments. The author’s modified extended mask extenders were printed and freely delivered to healthcare workers (physicians, nurses, technologists, and other personnel) at the authors’ institution. Results: The final mask extender design was printed with the two 3D printers with a maximum 7 straps printed simultaneously on each 3D printer. Mean print times ranges from 105 minutes for the Ultimaker S5 printer and 150 minutes for the CR-10. 475 mask extenders were delivered to healthcare workers at the authors’ institution, with the demand far exceeding the available supply. Conclusion: We offer a modification of a 3D printed mask extender design that decreases discomfort and increases the wearability of isolation mask designs with ear loops thought to relieve posterior auricular skin pressure and ability to control strap tension. The design is simple, produced with inexpensive material (polylactic acid), and have been well-received by healthcare providers at our institution

16.
Preprint in English | EuropePMC | ID: ppcovidwho-291181

ABSTRACT

As continued COVID-19 disruption looks likely across the world, perhaps until 2021, contingency plans are evolving in case of further disruption in the 2020-2021 academic year. This includes delivering face-to-face programmes fully-online for at least part of the upcoming academic year for new and continuing cohorts This temporary pivot will necessitate distance teaching and learning across almost every conceivable pedagogy, from fundamental degrees to professionally accredited ones. Each institution, programme, and course will have its own myriad of individualised needs , however, there is a common question that unites us all: how do we provide teaching and assessment to students in a manner that is accessible, fair, equitable, and provides the best learning whilst acknowledging the temporary nature of the Pivot? No ‘one size fits all’ solution exists and many of the choices that need to be made will be far from simple, however, this paper provides a starting point and basic principles to facilitate discussions taking place around the globe by balancing what we know from the pedagogy of online learning with the practicalities imposed by this crisis.

17.
Preprint in English | EuropePMC | ID: ppcovidwho-291176

ABSTRACT

Background: The impact of liver function test (LFTs) abnormality on adverse clinical outcomes in coronavirus disease 2019 (COVID-19) patients remains controversial. We aim to assess the impact of abnormal LFTs on clinical outcomes in a large cohort of hospitalized patients with COVID-19.<br><br>Methods: We retrospectively collected data on 2912 consecutive hospitalized patients with COVID-19 between 5 February and 23 March 2020. The association between LFTs abnormalities (baseline and peak values) and clinical outcomes was measured by using Cox regression models.<br><br>Findings: On admission 1414 patients (48.6%) had abnormal LFTs, with alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), alkaline phosphatase (ALP), and glutamyl transferase (GGT) elevation in 662 (22.7%), 221 (7.6%), 52 (1.8%), 135 (4.6%) and 536 (18.5%) patients, respectively and hypoalbuminemia in 737 (25.3%) patients. During a median 13 (IQR: 8-19) days of hospitalization, 61 patients (2.1%) died, 106 (3.6%) admitted to intensive care unit (ICU) and 75 (2.6%) required mechanical ventilation. After adjustment for confounders, baseline abnormal LFTs were independently associated with increased risks of mortality (adjusted HR 3.66, 95%CI 1.64-8.19, p=0.002), ICU admission (adjusted HR 3.12 95%CI 1.86-5.23, p<0.001) and mechanical ventilation (adjusted HR 3.00, 95%CI 1.63-5.52, p<0.001). Among the parameters of LTFs, the associations with outcomes were more pronounced for AST and albumin abnormality. In contrast, ALT elevation was not significantly associated with those outcomes. Similar results were observed for peak values of LFTs during hospitalization.<br><br>Interpretation: Abnormality of AST, albumin, TBIL, ALP and GGT but not ALT were independently associated with adverse outcomes.<br><br>Funding: Boost program of Xijing Hospital, Clinical Applied Research Subject of Military Medicine and China Postdoctoral Science Foundation.<br><br>Declaration of Interests: The authors declare no competing interests.<br><br>Ethics Approval Statement: This study was approved by the National Health Commission of China and the institutional review board at Huoshenshan hospital. Written informed consent was waived by the ethics committee of the Huoshenshan hospital for patients with emerging infectious diseases.

18.
Preprint in English | EuropePMC | ID: ppcovidwho-291175

ABSTRACT

The Coronavirus Disease (COVID-19) has affected 1.8 million people and resulted in more than 110,000 deaths as of April 12, 2020. Several studies have shown that tomographic patterns seen on chest Computed Tomography (CT), such as ground-glass opacities, consolidations, and crazy paving pattern, are correlated with the disease severity and progression. CT imaging can thus emerge as an important modality for the management of COVID-19 patients. AI-based solutions can be used to support CT based quantitative reporting and make reading efficient and reproducible if quantitative biomarkers, such as the Percentage of Opacity (PO), can be automatically computed. However, COVID-19 has posed unique challenges to the development of AI, specifically concerning the availability of appropriate image data and annotations at scale. In this paper, we propose to use synthetic datasets to augment an existing COVID-19 database to tackle these challenges. We train a Generative Adversarial Network (GAN) to inpaint COVID-19 related tomographic patterns on chest CTs from patients without infectious diseases. Additionally, we leverage location priors derived from manually labeled COVID-19 chest CTs patients to generate appropriate abnormality distributions. Synthetic data are used to improve both lung segmentation and segmentation of COVID-19 patterns by adding 20% of synthetic data to the real COVID-19 training data. We collected 2143 chest CTs, containing 327 COVID-19 positive cases, acquired from 12 sites across 7 countries. By testing on 100 COVID-19 positive and 100 control cases, we show that synthetic data can help improve both lung segmentation (+6.02% lesion inclusion rate) and abnormality segmentation (+2.78% dice coefficient), leading to an overall more accurate PO computation (+2.82% Pearson coefficient).

19.
Preprint in English | EuropePMC | ID: ppcovidwho-291174

ABSTRACT

Background: Although the number of patients with COVID-19 infection is increasing and concerns for their long-term disabilities are increasing, there is a lack of data about the delivery of the ABCDEF-bundle and supportive care in Intensive Care Units (ICUs). The aim of this study is to investigate the implementation of the ABCDEF-bundle and supportive care provided to patients with COVID-19 infections in ICUs. Methods: This was a world-wide two-day point prevalence study, on June 3 and July 1, 2020. A total of 212 ICUs in 38 countries (166 ICUs on Day 1 and 212 on Day 2) participated. Clinicians in each participating ICU completed web-based online surveys. The implementation rate for elements of the ABCDEF-bundle, other supportive ICU care measures and implementation associated structures were investigated. RESULTS Data for 262 patients was collected during the two-day study. Of patients included, 124 (47.3%) underwent mechanical ventilation (MV) and 12 (4.6%) patients were treated with extracorporeal membrane oxygenation (ECMO). The proportion of patients with implementation of each element was: Element A (regular pain assessment) 45%;B (both spontaneous awakening and breathing trials) 28%;C (regular sedation assessment) 52%;D (regular delirium assessment) 38%;E (early mobility and exercise) 47%;and F (family engagement and empowerment) 16%. The implementation of element E for patients on MV was 16% and ECMO was 17%. Supportive care, such as providing protein throughout the ICU stay (under 1.2g/kg for more than 50% of the patients) and introduction of an ICU diary (25%) was inadequate. A higher implementation rate of elements A and D were recognized in ICUs with specific protocols for ICU care and lower numbers of ICU beds exclusively for patients with COVID-19 infection. Element E was implemented at a higher rate in ICUs with more ICU beds for patients with COVID-19 infection. CONCLUSIONS This worldwide two-day point prevalence study found low implementation of the ABCDEF-bundle. Specific protocols and the number of ICU beds reserved for patients with COVID-19 infections might be key factors to deliver appropriate supportive care.Trial registration: UMIN, UMIN000040405. Registered 14 May 2020, https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000046103

20.
Preprint in English | EuropePMC | ID: ppcovidwho-291173

ABSTRACT

China's policy interventions to reduce the spread of the coronavirus disease 2019 have environmental and economic impacts. Tropospheric nitrogen dioxide indicates economic activities, as nitrogen dioxide is primarily emitted from fossil fuel consumption. Satellite measurements show a 48% drop in tropospheric nitrogen dioxide vertical column densities from the 20 days averaged before the 2020 Lunar New Year to the 20 days averaged after. This is 20% larger than that from recent years. We relate to this reduction to two of the government's actions: the announcement of the first report in each province and the date of a province's lockdown. Both actions are associated with nearly the same magnitude of reductions. Our analysis offers insights into the unintended environmental and economic consequences through reduced economic activities.

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