Characterising long COVID: a living systematic review.
TL;DR: In this article, a living systematic review was conducted to synthesize evidence on Long Covid characteristics, to inform clinical management, rehabilitation, and interventional studies to improve long term outcomes.
Abstract: Background: While it is now apparent clinical sequelae (often called Long Covid) may persist after acute Covid-19, their nature, frequency, and aetiology are poorly characterised. This study aims to regularly synthesise evidence on Long Covid characteristics, to inform clinical management, rehabilitation, and interventional studies to improve long term outcomes.
Methods: A living systematic review. Medline, CINAHL (EBSCO), Global Health (Ovid), WHO Global Research Database on Covid-19, LitCOVID, and Google Scholar were searched up to 17th March 2021. Published studies including at least 100 people with confirmed or clinically suspected Covid-19 at 12 weeks or more post-onset were included. Results were analysed using descriptive statistics and meta-analyses to estimate prevalence with 95% confidence intervals (CIs).
Results: Thirty-nine studies were included: 32 cohort, six cross-sectional, and one case-control. Most showed high or moderate risk of bias. None were set in low-income countries, limited studies included children. Studies reported on 10,951 people (48% female) in 12 countries. Most followed-up post hospital discharge (78%, 8520/10951). The longest mean follow-up was 221.7 (SD: 10.9) days post Covid-19 onset. An extensive range of symptoms with wide prevalence was reported, most commonly weakness (41%; 95% CI 25% to 59%), malaise (33%; 95% CI 15% to 57%), fatigue (31%; 95% CI 24% to 39%), concentration impairment (26%; 95% CI 21% to 32%), and breathlessness (25%; 95% CI 18% to 34%). Other frequent symptoms included musculoskeletal, neurological, and psychological. 37% (95% CI 18% to 60%) of people reported reduced quality of life.
Conclusion: Long Covid is a complex condition with heterogeneous symptoms. The nature of the studies precludes a precise case definition or evaluation of risk factors. There is an urgent need for prospective, robust, standardised controlled studies into aetiology, risk factors, and biomarkers to characterise Long Covid in different at-risk populations and settings.
Systematic review registration: The protocol was prospectively registered on the PROSPERO database (CRD42020211131).
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TL;DR: In this paper , the authors conducted a study to determine symptoms associated with confirmed SARS-CoV-2 infection beyond 12 weeks in non-hospitalized adults and the risk factors associated with developing persistent symptoms.
Abstract: Abstract Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is associated with a range of persistent symptoms impacting everyday functioning, known as post-COVID-19 condition or long COVID. We undertook a retrospective matched cohort study using a UK-based primary care database, Clinical Practice Research Datalink Aurum, to determine symptoms that are associated with confirmed SARS-CoV-2 infection beyond 12 weeks in non-hospitalized adults and the risk factors associated with developing persistent symptoms. We selected 486,149 adults with confirmed SARS-CoV-2 infection and 1,944,580 propensity score-matched adults with no recorded evidence of SARS-CoV-2 infection. Outcomes included 115 individual symptoms, as well as long COVID, defined as a composite outcome of 33 symptoms by the World Health Organization clinical case definition. Cox proportional hazards models were used to estimate adjusted hazard ratios (aHRs) for the outcomes. A total of 62 symptoms were significantly associated with SARS-CoV-2 infection after 12 weeks. The largest aHRs were for anosmia (aHR 6.49, 95% CI 5.02–8.39), hair loss (3.99, 3.63–4.39), sneezing (2.77, 1.40–5.50), ejaculation difficulty (2.63, 1.61–4.28) and reduced libido (2.36, 1.61–3.47). Among the cohort of patients infected with SARS-CoV-2, risk factors for long COVID included female sex, belonging to an ethnic minority, socioeconomic deprivation, smoking, obesity and a wide range of comorbidities. The risk of developing long COVID was also found to be increased along a gradient of decreasing age. SARS-CoV-2 infection is associated with a plethora of symptoms that are associated with a range of sociodemographic and clinical risk factors.
225 citations
TL;DR: In this paper , the authors conducted a study to determine symptoms associated with confirmed SARS-CoV-2 infection beyond 12 weeks in non-hospitalized adults and the risk factors associated with developing persistent symptoms.
Abstract: Abstract Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is associated with a range of persistent symptoms impacting everyday functioning, known as post-COVID-19 condition or long COVID. We undertook a retrospective matched cohort study using a UK-based primary care database, Clinical Practice Research Datalink Aurum, to determine symptoms that are associated with confirmed SARS-CoV-2 infection beyond 12 weeks in non-hospitalized adults and the risk factors associated with developing persistent symptoms. We selected 486,149 adults with confirmed SARS-CoV-2 infection and 1,944,580 propensity score-matched adults with no recorded evidence of SARS-CoV-2 infection. Outcomes included 115 individual symptoms, as well as long COVID, defined as a composite outcome of 33 symptoms by the World Health Organization clinical case definition. Cox proportional hazards models were used to estimate adjusted hazard ratios (aHRs) for the outcomes. A total of 62 symptoms were significantly associated with SARS-CoV-2 infection after 12 weeks. The largest aHRs were for anosmia (aHR 6.49, 95% CI 5.02–8.39), hair loss (3.99, 3.63–4.39), sneezing (2.77, 1.40–5.50), ejaculation difficulty (2.63, 1.61–4.28) and reduced libido (2.36, 1.61–3.47). Among the cohort of patients infected with SARS-CoV-2, risk factors for long COVID included female sex, belonging to an ethnic minority, socioeconomic deprivation, smoking, obesity and a wide range of comorbidities. The risk of developing long COVID was also found to be increased along a gradient of decreasing age. SARS-CoV-2 infection is associated with a plethora of symptoms that are associated with a range of sociodemographic and clinical risk factors.
194 citations
TL;DR: It is demonstrated that a sizeable proportion of COVID-19 survivors still experience residual symptoms involving various body systems one year later, suggesting an urgent need for elucidating the pathophysiologic mechanisms and developing and testing targeted interventions for long-COVID patients.
Abstract: Emerging evidence has shown that COVID-19 survivors could suffer from persistent symptoms. However, it remains unclear whether these symptoms persist over the longer term. This study aimed to systematically synthesise evidence on post-COVID symptoms persisting for at least 12 months. We searched PubMed and Embase for papers reporting at least one-year follow-up results of COVID-19 survivors published by 6 November 2021. Random-effects meta-analyses were conducted to estimate pooled prevalence of specific post-COVID symptoms. Eighteen papers that reported one-year follow-up data from 8591 COVID-19 survivors were included. Fatigue/weakness (28%, 95% CI: 18–39), dyspnoea (18%, 95% CI: 13–24), arthromyalgia (26%, 95% CI: 8–44), depression (23%, 95% CI: 12–34), anxiety (22%, 95% CI: 15–29), memory loss (19%, 95% CI: 7–31), concentration difficulties (18%, 95% CI: 2–35), and insomnia (12%, 95% CI: 7–17) were the most prevalent symptoms at one-year follow-up. Existing evidence suggested that female patients and those with more severe initial illness were more likely to suffer from the sequelae after one year. This study demonstrated that a sizeable proportion of COVID-19 survivors still experience residual symptoms involving various body systems one year later. There is an urgent need for elucidating the pathophysiologic mechanisms and developing and testing targeted interventions for long-COVID patients.
187 citations
TL;DR: The likelihood of long covid symptoms was observed to decrease after covid-19 vaccination and evidence suggested sustained improvement after a second dose, at least over the median follow-up of 67 days, although longer follow- up is needed.
Abstract: Abstract Objective To estimate associations between covid-19 vaccination and long covid symptoms in adults with SARS-CoV-2 infection before vaccination. Design Observational cohort study. Setting Community dwelling population, UK. Participants 28 356 participants in the Office for National Statistics COVID-19 Infection Survey aged 18-69 years who received at least one dose of an adenovirus vector or mRNA covid-19 vaccine after testing positive for SARS-CoV-2 infection. Main outcome measure Presence of long covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021. Results Mean age of participants was 46 years, 55.6% (n=15 760) were women, and 88.7% (n=25 141) were of white ethnicity. Median follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (83.8% of participants). 6729 participants (23.7%) reported long covid symptoms of any severity at least once during follow-up. A first vaccine dose was associated with an initial 12.8% decrease (95% confidence interval −18.6% to −6.6%, P<0.001) in the odds of long covid, with subsequent data compatible with both increases and decreases in the trajectory (0.3% per week, 95% confidence interval −0.6% to 1.2% per week, P=0.51). A second dose was associated with an initial 8.8% decrease (95% confidence interval −14.1% to −3.1%, P=0.003) in the odds of long covid, with a subsequent decrease by 0.8% per week (−1.2% to −0.4% per week, P<0.001). Heterogeneity was not found in associations between vaccination and long covid by sociodemographic characteristics, health status, hospital admission with acute covid-19, vaccine type (adenovirus vector or mRNA), or duration from SARS-CoV-2 infection to vaccination. Conclusions The likelihood of long covid symptoms was observed to decrease after covid-19 vaccination and evidence suggested sustained improvement after a second dose, at least over the median follow-up of 67 days. Vaccination may contribute to a reduction in the population health burden of long covid, although longer follow-up is needed.
176 citations
TL;DR: In this paper , the prevalence of persistent symptoms and signs at least 12 weeks after acute COVID-19 at different follow-up periods was estimated using a random-effect meta-analysis.
176 citations
References
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Book•
13 Aug 2009
TL;DR: This book describes ggplot2, a new data visualization package for R that uses the insights from Leland Wilkisons Grammar of Graphics to create a powerful and flexible system for creating data graphics.
Abstract: This book describes ggplot2, a new data visualization package for R that uses the insights from Leland Wilkisons Grammar of Graphics to create a powerful and flexible system for creating data graphics. With ggplot2, its easy to: produce handsome, publication-quality plots, with automatic legends created from the plot specification superpose multiple layers (points, lines, maps, tiles, box plots to name a few) from different data sources, with automatically adjusted common scales add customisable smoothers that use the powerful modelling capabilities of R, such as loess, linear models, generalised additive models and robust regression save any ggplot2 plot (or part thereof) for later modification or reuse create custom themes that capture in-house or journal style requirements, and that can easily be applied to multiple plots approach your graph from a visual perspective, thinking about how each component of the data is represented on the final plot. This book will be useful to everyone who has struggled with displaying their data in an informative and attractive way. You will need some basic knowledge of R (i.e. you should be able to get your data into R), but ggplot2 is a mini-language specifically tailored for producing graphics, and youll learn everything you need in the book. After reading this book youll be able to produce graphics customized precisely for your problems,and youll find it easy to get graphics out of your head and on to the screen or page.
29,504 citations
TL;DR: It is concluded that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity, and one or both should be presented in publishedMeta-an analyses in preference to the test for heterogeneity.
Abstract: The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity.
25,460 citations
Monash University1, University of Amsterdam2, University of Paris3, Bond University4, University of Texas Health Science Center at San Antonio5, University of Ottawa6, American University of Beirut7, Oregon Health & Science University8, University of York9, Ottawa Hospital Research Institute10, University of Southern Denmark11, Johns Hopkins University12, Brigham and Women's Hospital13, Indiana University14, University of Bristol15, University College London16, University of Toronto17
TL;DR: The preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement as discussed by the authors was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found.
Abstract: The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
16,613 citations
TL;DR: The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users.
Abstract: Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (
http://rayyan.qcri.org
), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.
7,527 citations
4,095 citations