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Identifying common baseline clinical features of COVID-19: a scoping review.

ABSTRACT: OBJECTIVES:Our research question was: what are the most frequent baseline clinical characteristics in adult patients with COVID-19? Our major aim was to identify common baseline clinical features that could help recognise adult patients at high risk of having COVID-19. DESIGN:We conducted a scoping review of all the evidence available at LitCovid, until 23 March 2020. SETTING:Studies conducted in any setting and any country were included. PARTICIPANTS:Studies had to report the prevalence of sociodemographic characteristics, symptoms and comorbidities specifically in adults with a diagnosis of infection by SARS-CoV-2. RESULTS:In total, 1572 publications were published on LitCovid. We have included 56 articles in our analysis, with 89% conducted in China and 75% containing inpatients. Three studies were conducted in North America and one in Europe. Participants' age ranged from 28 to 70 years, with balanced gender distribution. The proportion of asymptomatic cases were from 2% to 79%. The most common reported symptoms were fever (4%-99%), cough (4%-92%), dyspnoea/shortness of breath (1%-90%), fatigue (4%-89%), myalgia (3%-65%) and pharyngalgia (2%-61%), while regarding comorbidities, we found cardiovascular disease (1%-40%), hypertension (0%-40%) and cerebrovascular disease (1%-40%). Such heterogeneity impaired the conduction of meta-analysis. CONCLUSIONS:The infection by COVID-19 seems to affect people in a very diverse manner and with different characteristics. With the available data, it is not possible to clearly identify those at higher risk of being infected with this condition. Furthermore, the evidence from countries other than China is, at the moment, too scarce.

SUBMITTER: Ferreira-Santos D

PROVIDER: S-EPMC7496569 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Identifying common baseline clinical features of COVID-19: a scoping review.

Ferreira-Santos Daniela D Maranhão Priscila P Monteiro-Soares Matilde M

BMJ open 20200916 9

<h4>Objectives</h4>Our research question was: what are the most frequent baseline clinical characteristics in adult patients with COVID-19? Our major aim was to identify common baseline clinical features that could help recognise adult patients at high risk of having COVID-19.<h4>Design</h4>We conducted a scoping review of all the evidence available at LitCovid, until 23 March 2020.<h4>Setting</h4>Studies conducted in any setting and any country were included.<h4>Participants</h4>Studies had to ...[more]

PMID: 32938604

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Project description:BackgroundThe global outbreak of COVID-19 (coronavirus disease 2019) disease has highlighted the importance of disease monitoring, diagnosing, treating, and screening. Technology-based instruments could efficiently assist healthcare systems during pandemics by allowing rapid and widespread transfer of information, real-time tracking of data transfer, and virtualization of meetings and patient visits. Therefore, this study was conducted to investigate the applications of clinical informatics (CI) during the COVID-19 outbreak.MethodsA comprehensive search was performed on Medline and Scopus databases in September 2020. Eligible studies were selected based on the inclusion and exclusion criteria. The extracted data from the studies reviewed were about study sample, study type, objectives, clinical informatics domain, applied method, sample size, outcomes, findings, and conclusion. The risk of bias was evaluated in the studies using appropriate instruments based on the type of each study. The selected studies were then subjected to thematic synthesis.ResultsIn this review study, 72 out of 2716 retrieved articles met the inclusion criteria for full-text analysis. Most of the articles reviewed were done in China and the United States of America. The majority of the studies were conducted in the following CI domains: prediction models (60%), telehealth (36%), and mobile health (4%). Most of the studies in telehealth domain used synchronous methods, such as online and phone- or video-call consultations. Mobile applications were developed as self-triage, self-scheduling, and information delivery tools during the COVID-19 pandemic. The most common types of prediction models among the reviewed studies were neural network (49%), classification (42%), and linear models (4.5%).ConclusionThe present study showed clinical informatics applications during COVID-19 and identified current gaps in this field. Health information technology and clinical informatics seem to be useful in assisting clinicians and managers to combat COVID-19. The most common domains in clinical informatics for research on the COVID-19 crisis were prediction models and telehealth. It is suggested that future researchers conduct scoping reviews to describe and analyze other levels of medical informatics, including bioinformatics, imaging informatics, and public health informatics.

Project description:IntroductionDelay between symptom onset and access to care is essential to prevent clinical worsening for different infectious diseases. For COVID-19, this delay might be associated with the clinical prognosis, but also with the different characteristics of patients. The objective was to describe characteristics and symptoms of community-acquired (CA) COVID-19 patients at hospital admission according to the delay between symptom onset and hospital admission, and to identify determinants associated with delay of admission.MethodsThe present work was based on prospective NOSO-COR cohort data, and restricted to patients with laboratory confirmed CA SARS-CoV-2 infection admitted to Lyon hospitals between February 8 and June 30, 2020. Long delay of hospital admission was defined as ≥6 days between symptom onset and hospital admission. Determinants of the delay between symptom onset and hospital admission were identified by univariate and multiple logistic regression analysis.ResultsData from 827 patients were analysed. Patients with a long delay between symptom onset and hospital admission were younger (p<0.01), had higher body mass index (p<0.01), and were more frequently admitted to intensive care unit (p<0.01). Their plasma levels of C-reactive protein were also significantly higher (p<0.01). The crude in-hospital fatality rate was lower in this group (13.3% versus 27.6%), p<0.01. Multiple analysis with correction for multiple testing showed that age ≥75 years was associated with a short delay between symptom onset and hospital admission (≤5 days) (aOR: 0.47 95% CI (0.34-0.66)) and CRP>100 mg/L at admission was associated with a long delay (aOR: 1.84 95% CI (1.32-2.55)).DiscussionDelay between symptom onset and hospital admission is a major issue regarding prognosis of COVID-19 but can be related to multiple factors such as individual characteristics, organization of care and severe pathogenic processes. Age seems to play a key role in the delay of access to care and the disease prognosis.

Project description:Background: Since the coronavirus disease 2019 (COVID-19) outbreak was first reported in December 2019, many independent trials have been planned that aim to answer similar questions. Tools allowing researchers to review studies already underway can facilitate collaboration, cooperation and harmonisation. The Infectious Diseases Data Observatory (IDDO) has undertaken a living systematic review (LSR) to provide an open, accessible and frequently updated resource summarising characteristics of COVID-19 study registrations. Methods: Review of all eligible trial records identified by systematic searches as of 3 April 2020 and initial synthesis of clinical study characteristics were conducted. In partnership with Exaptive, an open access, cloud-based knowledge graph has been created using the results. Results: There were 728 study registrations which met eligibility criteria and were still active. Median (25 th, 75 th percentile) sample size was 130 (60, 400) for all studies and 134 (70, 300) for RCTs. Eight lower middle and low income countries were represented among the planned recruitment sites. Overall 109 pharmacological interventions or advanced therapy medicinal products covering 23 drug categories were studied. Majority (57%, 62/109) of them were planned only in one study arm, either alone or in combination with other interventions. There were 49 distinct combinations studied with 90% (44/49) of them administered in only one or two study arms. The data and interactive platform are available at https://iddo.cognitive.city/. Conclusions: Baseline review highlighted that the majority of investigations in the first three months of the outbreak were small studies with unique treatment arms, likely to be unpowered to provide solid evidence. The continued work of this LSR will allow a more dependable overview of interventions tested, predict the likely strength of evidence generated, allow fast and informative filtering of relevant trials for specific user groups and provide the rapid guidance needed by investigators and funders to avoid duplication of efforts.

Project description:ObjectivesIn response to the COVID-19 pandemic there have been significant developments in research, its conduct and the supporting ethical framework. While many protocols have been delayed, halted or modified, other research efforts have been accelerated, generating controversy. The goal of this paper is to determine the rates of references surrounding the ethical oversight of research as reported in current COVID-19-related research publications.DesignScoping review.SettingPopulation-based observational or interventional studies from December 2019 to May 2020 with sample size of two or more. Studies were searched through electronic databases including Medline, EMBASE, and Cochrane CENTRAL Register of Controlled Trials.ParticipantsEligibility criteria included participants within published studies who tested positive for COVID-19.Main outcomes and measuresData were extracted and charting methods included taking note of references to ethical frameworks, institutional review board (IRB), ethics committee (EC) or research ethics board (REB) involvement, consent processes, and other variables.Results11 556 articles were screened, with 656 included in the final analysis. References to ethics were present in 530 (80.8%) studies, with 491 (74.8%) involving IRB/ECs/REBs and 126 (19.2%) not referencing ethics. Consent processes were outlined in 201 (30.6%) studies, with 198 (30.2%) reporting that they obtained consent waivers, however, 257 (39.2%) did not mention consent at all. Differences (p<0.001) in ethics-related references were apparent when analysed by continent, publication type, sample size and IF.ConclusionsThe majority of published articles pertaining to COVID-19 research made mention of ethical considerations, however, national and regional variations in research ethics review requirements introduce heterogeneity between studies and raise important questions about the conduct of scientific research during global public emergencies.Trial registration numberOpen Science Framework: https://osfio/z67wb.

Project description:BackgroundAs one of the non-pharmacological interventions to control the transmission of COVID-19, determining the quarantine duration is mainly based on the accurate estimates of the incubation period. However, patients with coarse information of the exposure date, as well as infections other than the symptomatic, were not taken into account in previously published studies. Thus, by using the statistical method dealing with the interval-censored data, we assessed the quarantine duration for both common and uncommon infections. The latter type includes the presymptomatic, the asymptomatic and the recurrent test positive patients.MethodsAs of 10 December 2020, information on cases have been collected from the English and Chinese databases, including Pubmed, Google scholar, CNKI (China National Knowledge Infrastructure) and Wanfang. Official websites and medias were also searched as data sources. All data were transformed into doubly interval-censored and the accelerated failure time model was applied. By estimating the incubation period and the time-to-event distribution of worldwide COVID-19 patients, we obtain the large percentiles for determining and suggesting the quarantine policies. For symptomatic and presymptomatic COVID-19 patients, the incubation time is the duration from exposure to symptom onset. For the asymptomatic, we substitute the date of first positive result of nucleic acid testing for that of symptom onset. Furthermore, the time from hospital discharge or getting negative test result to the positive recurrence has been calculated for recurrent positive patients.ResultsA total of 1920 laboratory confirmed COVID-19 cases were included. Among all uncommon infections, 34.1% (n = 55) of them developed symptoms or were identified beyond fourteen days. Based on all collected cases, the 95th and 99th percentiles were estimated to be 16.2 days (95% CI 15.5-17.0) and 22.9 days (21.7‒24.3) respectively. Besides, we got similar estimates based on merely symptomatic and presymptomatic infections as 15.1 days (14.4‒15.7) and 21.1 days (20.0‒22.2).ConclusionsThere are a certain number of infected people who require longer quarantine duration. Our findings well support the current practice of the extended active monitoring. To further prevent possible transmissions induced and facilitated by such infectious outliers after the 14-days quarantine, properly prolonging the quarantine duration could be prudent for high-risk scenarios and in regions with insufficient test resources.

Project description:BackgroundIn November 2020, the World Health Organization (WHO) created interim guidance on how to integrate testing for SARS-CoV-2 into existing influenza surveillance systems. Influenza-like illness (ILI) and severe acute respiratory illness (SARI) case definitions have been used to specify the case definition of COVID-19 for surveillance purposes. This review aims to assess whether the common clinical features of COVID-19 have changed to the point that the criteria used to identify both COVID-19 and influenza in surveillance programs needs to be altered.MethodsA systematic review of reviews following PRISMA-P guidelines was conducted using the "COVID-19 evidence review" database from August 19, 2020, to August 19, 2021. Reviews providing pooled estimates of the prevalence of clinical features of COVID-19 within the general population, diagnosed by polymerase chain reaction or rapid diagnostic test, were included. These were critically appraised and sensitivity analysis was undertaken to examine potential causes of bias.ResultsFourteen reviews were identified, including three on adults only and three on children only. For all reviews, combined fever (median prevalence = 73.0%, IQR = 58.3-78.7) and cough (45.1%, IQR = 28.9-54.0) were the most common features. These were followed by loss of taste or smell (45.1%, IQR = 28.9-54.0), hypoxemia (33%, one review), fatigue (26.4%, IQR = 9.0-39.4) and expectoration (23.9%, IQR = 23.3-25.5). Fever and cough continued to be the most prevalent features for adults and children, with subsequent symptoms being similar for adults only. However, the pattern differed for children, with headache (34.3%, IQR = 18-50.7) and nasal congestion (20%, one review) being the third and fourth commonest symptoms.ConclusionsThe prevalent features found in this recent review were the same as the ones identified at the beginning of the pandemic. Therefore, the current approach of using the ILI and SARI criteria which incorporate fever and cough will identify COVID-19 cases in addition to influenza. Interestingly, children may present with different features, as headaches and nasal congestion were more common in this group. Future research could examine this further and investigate whether symptomology changes with new variants of COVID-19.

Project description:BackgroundCoronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 strain, was first identified in late 2019 in China. The outcomes of patients affected by the virus can worsen, developing acute respiratory failure and other serious complications, especially in older individuals and people with obesity and comorbidities. Thus, obese patients tend to have a more severe course of COVID-19. Thus, this review aims to synthesize the evidence in the literature that associates COVID-19 and the severity of clinical outcomes in infected obese patients.MethodsThis protocol was designed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols Statement. Scientific and gray literature will be systematically selected from PubMed/MEDLINE, Latin American Literature in Health Sciences, Online Scientific Electronic Library, Scopus, ScienceDirect, Web of Science, Embase, and Cochrane. The selection of articles will be limited to studies published in English, Portuguese, and Spanish from December 2019 onwards. The main clinical outcomes will be clinical severity in obese patients with COVID-19 as tachypnea (respiratory rate, ≥ 30 breaths per minute), hypoxemia (oxygen saturation, ≤ 93%), the ratio of the partial pressure of arterial oxygen to fraction of inspired oxygen (< 300), lung infiltrate (> 50% of the lung field involved within 24-48 h), diagnosis of the severe acute respiratory syndrome, need of invasive mechanical ventilation, and mortality. Two reviewers will independently screen all citations, full-text articles, and abstract data. Selection bias will be minimized by excluding studies published before December 2019. Conflicts will be resolved through a third reviewer and consensus-building. Moreover, findings will be reported using narrative synthesis and tabulation of the summaries.DiscussionGiven the need for early detection of the possible implications and treatment for patients with obesity diagnosed with COVID-19, the scoping review will be useful to capture the state of the current literature, identify the gaps, and make recommendations for future research for directing the conduct and optimization of therapies in these patients by the multiprofessional teams.Systematic review registrationOpen Science Framework: https://osf.io/xrkec.

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Identifying common baseline clinical features of COVID-19: a scoping review.

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Identifying common baseline clinical features of COVID-19: a scoping review.

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