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BackgroundSARS-CoV-2 nosocomial transmission to patients and healthcare workers (HCWs) has occurred throughout the COVID-19 pandemic. Aerosol generating procedures (AGPs) seemed particularly risky, and policies have restricted their use in all settings. We examined the prevalence of aerosolized SARS-CoV-2 in the rooms of COVID-19 patients requiring AGP or supplemental oxygen compared to those on room air. MethodsSamples were collected prospectively near to adults hospitalised with COVID-19 at two tertiary care hospitals in the UK from November 2020 - October 2021. The Sartorius MD8 AirPort air sampler was used to collect air samples at a minimum distance of 1.5 meters from patients. RT-qPCR was used following overnight incubation of membranes in culture media and extraction. ResultsWe collected 219 samples from patients rooms: individuals on room air (n=67), receiving oxygen (n=65) or AGP (n=67). Of these, 54 (24.6%) samples were positive for SARS-CoV-2 viral RNA. The highest prevalence was identified in the air around patients receiving oxygen (32.3%, n=21, CI95% 22.2 to 44.3%) with AGP and room air recording prevalence of (20.7%, n=18, CI95% 14.1 - 33.7%) and (22.3%, n=15, CI95% 13.5 - 30.4%) respectively. We did not detect a significant difference in the observed frequency of viral RNA between interventions. InterpretationSARS-CoV-2 viral RNA was detected in the air of hospital rooms of COVID-19 patients, and AGPs did not appear to impact the likelihood of viral RNA. Enhanced respiratory protection and appropriate infection prevention and control measures are required to be fully and carefully implemented for all COVID-19 patients to reduce risk of aerosol transmission.
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ObjectiveTo summarize the frequency of neurological manifestations reported in COVID-19 patients and investigate the association of these manifestations with disease severity and mortality. DesignSystematic review and meta-analysis Eligibility criteriaStudies enrolling consecutive COVID-19 patients (probable or confirmed) presenting with neurological manifestations. Data sourcesPubMed, Medline, Cochrane library, clinicaltrials.gov and EMBASE from 31st December 2019 to 15th December 2020. Data extraction and analysisTwo authors independently screened titles and abstracts retrieved by literature search. Risk of bias was examined using Joanna Briggs Institute (JBI) scale. A random-effects meta-analysis was performed, and pooled prevalence and 95% Confidence Intervals (CI) were calculated for neurological manifestations. Odds ratio (OR) and 95%CI were calculated to determine the association of neurological manifestations with disease severity and mortality. Presence of heterogeneity was assessed using I-square, meta-regression, and subgroup analyses. Statistical analyses were conducted in R version 3.6.2. ResultsOf 2,455 citations, 350 studies were included in this review, providing data on 145,634 COVID-19 patients, 89% of whom were hospitalized. Forty-one neurological manifestations (24 symptoms and 17 diagnoses) were identified. Pooled prevalence of the most common neurological symptoms included: fatigue (32%), myalgia (20%), taste impairment (21%), smell impairment (19%) and headache (13%). A low risk of bias was observed in 85% of studies; studies with higher risk of bias yielded higher prevalence estimates. Stroke was the most common neurological diagnosis (pooled prevalence-2%). In COVID-19 patients aged >60, the pooled prevalence of acute confusion/delirium was 34% and the presence of any neurological manifestations in this age group was associated with mortality (OR 1.80; 95%CI 1.11 to 2.91). ConclusionsUp to one-third of COVID-19 patients analysed in this review experienced at least one neurological manifestation. One in 50 patients experienced stroke. In those over 60, more than one-third had acute confusion/delirium; the presence of neurological manifestations in this group was associated with near doubling of mortality. Results must be interpreted keeping in view the limitations of observational studies and associated bias. Systematic review registrationPROSPERO CRD42020181867. What is already known on this topicThe frequency of neurological manifestations including fatigue, myalgia, taste and smell impairments, headache and dizziness in COVID-19 patients has been reported in a few systematic reviews and meta-analyses. However, considerable heterogeneity has been observed in terms of methodological quality of the studies, severity of the disease, mean age and hospitalization status of the patients. The evidence regarding the frequency of neurological diagnoses including stroke, encephalitis, Guillain Barre syndrome (GBS) is also limited to case reports and case series and no data exists thus far on the pooled prevalence estimates for neurological diagnoses in COVID-19 patients. What this study addsTo the best of the authors knowledge, this is the largest systematic review and meta-analysis to date (including 350 studies with data on 145,634 cases) summarizing the evidence on the frequency of the full spectrum of neurological manifestations in COVID-19 patients in the overall, young and elderly populations. For the first time, our review reports the pooled prevalence of stroke in COVID-19 patients. Risk of bias, old age and disease severity were potential determinants of the frequency and nature of neurological manifestations as well as its association with mortality. Our review also highlights the need to develop reporting standards for studies describing the frequency of clinical features. Moreover, we note that this will be the first systematic review and meta-analysis on this subject to include studies reported in all languages.
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ObjectivesThere is accumulating evidence of the neurological and neuropsychiatric features of infection with SARS-CoV-2. In this systematic review and meta-analysis, we aimed to describe the characteristics of the early literature and estimate point prevalences for neurological and neuropsychiatric manifestations. MethodsWe searched MEDLINE, Embase, PsycInfo and CINAHL up to 18 July 2020 for randomised controlled trials, cohort studies, case-control studies, cross-sectional studies and case series. Studies reporting prevalences of neurological or neuropsychiatric symptoms were synthesised into meta-analyses to estimate pooled prevalence. Results13,292 records were screened by at least two authors to identify 215 included studies, of which there were 37 cohort studies, 15 case-control studies, 80 cross-sectional studies and 83 case series from 30 countries. 147 studies were included in the meta-analysis. The symptoms with the highest prevalence were anosmia (43.1% [35.2--51.3], n=15,975, 63 studies), weakness (40.0% [27.9--53.5], n=221, 3 studies), fatigue (37.8% [31.6--44.4], n=21,101, 67 studies), dysgeusia (37.2% [30.0--45.3], n=13,686, 52 studies), myalgia (25.1% [19.8--31.3], n=66.268, 76 studies), depression (23.0 % [11.8--40.2], n=43,128, 10 studies), headache (20.7% [95% CI 16.1--26.1], n=64,613, 84 studies), anxiety (15.9% [5.6--37.7], n=42,566, 9 studies) and altered mental status (8.2% [4.4--14.8], n=49,326, 19 studies). Heterogeneity for most clinical manifestations was high. ConclusionsNeurological and neuropsychiatric symptoms of COVID-19 in the pandemics early phase are varied and common. The neurological and psychiatric academic communities should develop systems to facilitate high-quality methodologies, including more rapid examination of the longitudinal course of neuropsychiatric complications of newly emerging diseases and their relationship to neuroimaging and inflammatory biomarkers.
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Introductory paragraphThe mechanisms that underpin COVID-19 disease severity, and determine the outcome of infection, are only beginning to be unraveled. The host inflammatory response contributes to lung injury, but circulating mediators levels fall below those in classical cytokine storms. We analyzed serial plasma samples from 619 patients hospitalized with COVID-19 recruited through the prospective multicenter ISARIC clinical characterization protocol U.K. study and 39 milder community cases not requiring hospitalization. Elevated levels of numerous mediators including angiopoietin-2, CXCL10, and GM-CSF were seen at recruitment in patients who later died. Markers of endothelial injury (angiopoietin-2 and von-Willebrand factor A2) were detected early in some patients, while inflammatory cytokines and markers of lung injury persisted for several weeks in fatal COVID-19 despite decreasing antiviral cytokine levels. Overall, markers of myeloid or endothelial cell activation were associated with severe, progressive, and fatal disease indicating a central role for innate immune activation and vascular inflammation in COVID-19.
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Prognostic models to predict the risk of clinical deterioration in acute COVID-19 are required to inform clinical management decisions. Among 75,016 consecutive adults across England, Scotland and Wales prospectively recruited to the ISARIC Coronavirus Clinical Characterisation Consortium (ISARIC4C) study, we developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) using 11 routinely measured variables. We used internal-external cross-validation to show consistent measures of discrimination, calibration and clinical utility across eight geographical regions. We further validated the final model in held-out data from 8,252 individuals in London, with similarly consistent performance (C-statistic 0.77 (95% CI 0.75 to 0.78); calibration-in-the-large 0.01 (-0.04 to 0.06); calibration slope 0.96 (0.90 to 1.02)). Importantly, this model demonstrated higher net benefit than using other candidate scores to inform decision-making. Our 4C Deterioration model thus demonstrates unprecedented clinical utility and generalisability to predict clinical deterioration among adults hospitalised with COVID-19.
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BackgroundThe Coronavirus disease 2019 (covid-19) pandemic has spread rapidly across the globe. Accurate clinical characterisation studies conducted early in the pandemic are essential to informing research, diagnosis and clinical management efforts. In this scoping review we identify the clinical characteristics of patients admitted to hospital in the early months of the pandemic, focusing on symptoms, laboratory and imaging findings, and clinical outcomes. MethodsA scoping review. MEDLINE, EMBASE and Global Health databases were searched for studies published from January 1st 2020 to April 28th 2020. Studies which reported on at least 100 hospitalised patients with covid-19 of any age were included. ResultsOf 1,249 studies identified through the search 78 studies were eligible for inclusion; one randomized control trial and 77 observational studies presenting data on 77,443 patients admitted with covid-19. Most studies were conducted in China (82%), 9% in the US and 10% in Europe and two studies were set in more than one country. No studies included patients from low and middle income countries. Coagulopathy was underrecognised as a complication in the early months of the pandemic. Use of corticosteroids varied widely, and the use of anticoagulants was reported in only one study. Fever, cough and dyspnoea are less common in older adults; gastrointestinal symptoms, as the only presenting feature was underrecognised. The most common laboratory finding was lymphocytopenia. Inflammatory biomarkers were commonly elevated, including C-reactive protein and interleukin-6. Typical computed tomography findings include bilateral infiltrates however imaging may be normal in early disease. Data on clinical characteristics in children and vulnerable populations were limited. ConclusionsClinical characterisation studies from early in the pandemic indicated that covid-19 is a multisystem disease, with biomarkers indicating inflammation and coagulopathy. However, early data collection on symptoms and clinical outcomes did not consistently reflect this wide spectrum. Corticosteroid use varied widely, and anticoagulants were rarely used. Clinicians should remain vigilant to the possibility of covid-19 in patients presenting without fever, cough and dyspnoea, particularly in older adults. Further characterisation studies in different at-risk populations is needed. Review registrationAvailable at https://osf.io/r2ch9
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ObjectivesTo develop and validate a pragmatic risk score to predict mortality for patients admitted to hospital with covid-19. DesignProspective observational cohort study: ISARIC WHO CCP-UK study (ISARIC Coronavirus Clinical Characterisation Consortium [4C]). Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited between 21 May and 29 June 2020. Setting260 hospitals across England, Scotland, and Wales. ParticipantsAdult patients ([≥]18 years) admitted to hospital with covid-19 admitted at least four weeks before final data extraction. Main outcome measuresIn-hospital mortality. ResultsThere were 34 692 patients included in the derivation dataset (mortality rate 31.7%) and 22 454 in the validation dataset (mortality 31.5%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea, and C-reactive protein (score range 0-21 points). The 4C risk stratification score demonstrated high discrimination for mortality (derivation cohort: AUROC 0.79; 95% CI 0.78 - 0.79; validation cohort 0.78, 0.77-0.79) with excellent calibration (slope = 1.0). Patients with a score [≥]15 (n = 2310, 17.4%) had a 67% mortality (i.e., positive predictive value 67%) compared with 1.0% mortality for those with a score [≤]3 (n = 918, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (AUROC range 0.60-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). ConclusionsWe have developed and validated an easy-to-use risk stratification score based on commonly available parameters at hospital presentation. This outperformed existing scores, demonstrated utility to directly inform clinical decision making, and can be used to stratify inpatients with covid-19 into different management groups. The 4C Mortality Score may help clinicians identify patients with covid-19 at high risk of dying during current and subsequent waves of the pandemic. Study registrationISRCTN66726260
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COVID-19 is a complex disease phenotype where the underlying microbiome could influence morbidity and mortality. Amplicon and metagenomic MinION based sequencing was used to rapidly (within 8 hours) identify SARS-CoV-2 and assess the microbiome in nasopharyngeal swabs obtained from patients with COVID-19 by the ISARIC 4C consortium.
