What are the long-term symptoms and complications of COVID-19: a protocol for a living systematic review

Melina Michelen; Vincent Cheng; Lakshmi Manoharan; Natalie Elkheir; Drew Dagens; Claire Hastie; Margaret O'Hara; Jake C. Suett; Dania Dahmash; Paulina Bugaeva; Ishmaela Rigby; Daniel Munblit; Eli Harriss; Amanda Burls; Carol Foote; Janet Scott; Gail Carson; Piero Olliaro; Louise Sigfrid; Charitini Stavropoulou

doi:10.12688/f1000research.27284.2

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Study Protocol

Revised

What are the long-term symptoms and complications of COVID-19: a protocol for a living systematic review

[version 2; peer review: 2 approved]

Melina Michelen¹, Vincent Cheng², Lakshmi Manoharan³, [...] Natalie Elkheir^3,4, Drew Dagens³, Claire Hastie⁵, Margaret O'Hara⁵, Jake C. Suett^5,6, Dania Dahmash³, Paulina Bugaeva³, Ishmaela Rigby³, Daniel Munblit^7-9, Eli Harriss¹⁰, Amanda Burls¹, Carol Foote¹¹, Janet Scott¹², Gail Carson³, Piero Olliaro³, Louise Sigfrid³, Charitini Stavropoulou ¹

Melina Michelen¹, Vincent Cheng², [...] Lakshmi Manoharan³, Natalie Elkheir^3,4, Drew Dagens³, Claire Hastie⁵, Margaret O'Hara⁵, Jake C. Suett^5,6, Dania Dahmash³, Paulina Bugaeva³, Ishmaela Rigby³, Daniel Munblit^7-9, Eli Harriss¹⁰, Amanda Burls¹, Carol Foote¹¹, Janet Scott¹², Gail Carson³, Piero Olliaro³, Louise Sigfrid³, Charitini Stavropoulou ¹

PUBLISHED 27 Aug 2021

Author details Author details

¹ School of Health Sciences, City, University of London, London, UK
² Bristol Medical School, University of Bristol, Bristol, UK
³ ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
⁴ Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
⁵ Long Covid Support, Birmingham, UK
⁶ Queen Elizabeth Hospital Kings Lynn, Norfolk, UK
⁷ Department of Paediatrics and Paediatric Infectious Diseases, Institute of Child’s Health, Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russian Federation
⁸ Inflammation, Repair and Development Section, National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, UK
⁹ Research and Clinical Center for Neuropsychiatry, Moscow, Russian Federation
¹⁰ Bodleian Health Care Libraries, University of Oxford, Oxford, UK
¹¹ Freelance, Soquel, California, USA
¹² MRC-University of Glasgow Centre for Virus Research, Glasgow, UK

Melina Michelen
Roles: Data Curation, Formal Analysis, Investigation, Methodology, Validation, Writing – Review & Editing

Vincent Cheng
Roles: Data Curation, Formal Analysis, Investigation, Methodology, Validation, Writing – Review & Editing

Lakshmi Manoharan
Roles: Data Curation, Formal Analysis, Methodology, Validation, Writing – Review & Editing

Natalie Elkheir
Roles: Data Curation, Investigation, Methodology, Validation, Writing – Review & Editing

Drew Dagens
Roles: Data Curation, Investigation, Methodology, Writing – Review & Editing

Claire Hastie
Roles: Investigation, Validation, Writing – Review & Editing

Margaret O'Hara
Roles: Investigation, Validation, Writing – Review & Editing

Jake C. Suett
Roles: Investigation, Methodology, Validation, Writing – Review & Editing

Dania Dahmash
Roles: Data Curation, Formal Analysis, Validation, Writing – Review & Editing

Paulina Bugaeva
Roles: Data Curation, Formal Analysis, Validation, Writing – Review & Editing

Ishmaela Rigby
Roles: Data Curation, Formal Analysis, Validation, Writing – Review & Editing

Daniel Munblit
Roles: Formal Analysis, Validation, Writing – Review & Editing

Eli Harriss
Roles: Data Curation, Writing – Review & Editing

Amanda Burls
Roles: Investigation, Validation, Writing – Review & Editing

Carol Foote
Roles: Investigation, Validation, Writing – Review & Editing

Janet Scott
Roles: Writing – Review & Editing

Gail Carson
Roles: Funding Acquisition, Validation, Writing – Review & Editing

Piero Olliaro
Roles: Funding Acquisition, Validation, Writing – Review & Editing

Louise Sigfrid
Roles: Funding Acquisition, Methodology, Validation, Writing – Review & Editing

Charitini Stavropoulou
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Supervision, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Emerging Diseases and Outbreaks gateway.

This article is included in the Pathogens gateway.

This article is included in the Coronavirus (COVID-19) collection.

This article is included in the Living Evidence collection.

Abstract

Although the majority of people with Covid-19 will experience mild to moderate symptoms and will recover fully, there is now increasing evidence that a significant proportion will experience persistent symptoms for months after the acute phase of the illness. These symptoms include, among others, fatigue, problems breathing, lack of smell and taste, headaches, and depression and anxiety. It is also clear the virus has lasting fluctuating multiorgan sequelae, including affecting not only the respiratory system but also the heart, liver, and nervous system.
We present a protocol for a living systematic review that aims to synthesize the evidence on the prevalence and characteristics of post-acute COVID-19.
The living systematic review will be updated regularly, approximately every 6 months, as new evidence emerges. We will include studies that follow up at least 100 people with Covid-19 at 12 or more weeks post Covid-19 onset, with no restrictions regarding country, setting, or language.
We will use descriptive statistics and, for outcomes reported in two or more studies, we will use meta-analyses to estimate prevalence with 95% confidence intervals (CIs) using the exact method. Heterogeneity between estimates will be assessed using the I2 statistic. Our findings will also be presented as infographics to facilitate transcription to lay audiences. Ultimately, we aim to support the work of policy makers, practitioners, and patients when planning rehabilitation for those recovering from Covid-19.
The protocol has been registered with PROSPERO ( CRD42020211131, 25/09/2020).

Keywords

Living systematic review, COVID-19, long covid, lasting effects

Corresponding author: Charitini Stavropoulou

Competing interests: No competing interests were disclosed.

Grant information: This work was supported by the Department for International Development and Wellcome [215091] and the Bill and Melinda Gates Foundation [OPP1209135].
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2021 Michelen M et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Michelen M, Cheng V, Manoharan L et al. What are the long-term symptoms and complications of COVID-19: a protocol for a living systematic review [version 2; peer review: 2 approved]. F1000Research 2021, 9:1455 (https://doi.org/10.12688/f1000research.27284.2) First published: 14 Dec 2020, 9:1455 (https://doi.org/10.12688/f1000research.27284.1) Latest published: 27 Aug 2021, 9:1455 (https://doi.org/10.12688/f1000research.27284.2)

Revised Amendments from Version 1

In the updated version, we have taken into consideration every point that each reviewer has made and responded to them in detail.

The main changes are as follows. We now explicitly state the primary and secondary outcomes we are interested in, the specific inclusion/exclusion criteria and the data that we will extract. In addition, we now clarify that the analysis will go beyond descriptive statistics and when possible, it will include a meta-analysis. The choice of groups for our subgroup analysis will depend on discussions with our clinical experts, patient advocates and by reviewing the literature. In addition, we further justify the choice of Hoy et al risk of bias assessment checklist, a validated tool for assessing risk of bias in prevalence studies, which can also be used with cohort studies. Finally, we clarify issues that relate to how we dealt with different languages and how often we will be updating the review. Given the fast increasing literature on Long Covid, we have had to add more co-authors to the paper to allow us to cope with the continuous updates of the living systematic review.

See the authors' detailed response to the review by Johannes Siegrist
See the authors' detailed response to the review by Madelon van Wely

Background

The range of documented Covid-19 infections vary from asymptomatic to severe, but the vast majority of patients experience mild to moderate symptoms and do not require hospitalisation¹. We have previously conducted a rapid review of the literature to identify which symptoms and signs might differentiate mild and moderate from severe Covid-19². Since then, and as more data are being gathered, there is increasing evidence of a “long-tail” of Covid-19 illness, but limited information about the range and duration of symptoms experienced³ or longer term health complications. A community app developed at King’s College London, which tracks self-reported symptoms, has shown that about one in ten will be sick for three weeks or more (https://covid.joinzoe.com/post/covid-long-term). Some individuals with Covid-19 have reported “fatigue, headaches and tingling nerves” that lasted months after symptom onset⁴. A recent longitudinal cohort of 143 patients followed after hospitalisation from Covid-19 in Italy reported that 87% had at least one ongoing symptom, most (55%) reporting three or more, at 60 day follow up. Fatigue (53%), dyspnoea (43%), joint pain (27%) and chest pain (22%) were the most common ongoing symptoms⁵, but there is a variety of other symptoms and complications that have been reported including neurocognitive difficulties, muscle pains and weakness, gastrointestinal upset, rashes, metabolic disruption, thromboembolic conditions and mental health conditions⁶. A prolonged course of illness has also been reported among people with mild Covid-19 who did not require hospitalisation^3,7,8.

The evidence to date remains fragmented as to the onset of symptoms and clinical features, how long symptoms may last, how this relates to the severity of the initial illness, and further lasting impacts to health. A better understanding of patients’ projected recovery from Covid-19 is helpful to patients, healthcare professionals, policymakers and commissioners. The clinical management of persisting symptoms of Covid-19 has started to be addressed in the clinical literature⁶ and NHS England has issued guidance for the multisystem needs of patients recovering from Covid-19⁹. Our findings could help identify people requiring additional rehabilitation services and, where necessary, specialist referral to establish a secondary cause of their symptoms. Our findings will also be relevant to organisations such as NHS England, which have recently launched an online Covid-19 rehab service supporting patients suffering long-term effects of the disease (https://www.yourcovidrecovery.nhs.uk/) or the British Society of Immunologists, which recently released a briefing note recommending research into the long-term immunological health consequences of Covid-19¹⁰.

The aim of this review is to synthesize and continually update the evidence on the characteristics, including prevalence and duration of symptoms and clinical features of post-acute COVID-19, as well as risk factors for developing Long Covid. This will inform clinical and public health management, prevention, and rehabilitation policies.

Methods

To address the aim of this study we will conduct a living systematic review (LSR). LSRs are used in areas where research evidence is emerging rapidly, current evidence is uncertain, and new research may influence policy or practice decisions¹¹. These are all features of Covid-19 research, where much about the long-term effects of the disease are still unknown and policy makers are calling for more evidence. The review will be updated approximately every six months, with update cycles under continuous review as the pace of new evidence generated develops through the pandemic. We aim to continue to update the review for up to two years. Our study methodology has been developed and strengthened through consultation with Long Covid Support (a patient support network).

Inclusion/exclusion criteria

We will include studies that meet the follow criteria:

• Studies following up with at least 100 people with suspected, laboratory confirmed, and/or clinically diagnosed Covid-19
• Studies assessing symptoms or outcomes at 12 or more weeks post Covid-19 onset
• Peer reviewed articles published since 1 January 2020
• No restriction regarding country, setting, or language

We will exclude:

• Studies that focus only on acute Covid-19
• Editorials and opinion papers

Search strategy

A search of the following databases will be conducted: Pubmed and CINAHL through the EBSCO database host for general health peer-reviewed articles and Global Health for global peer-reviewed articles through the Ovid database host. In addition, we will search Google Scholar for grey literature. We will also conduct complementary searches using the WHO Global Research Database on Covid-19 and LitCOVID as two databases that bring together evidence on Covid-19 from a worldwide dataset. A ‘backwards’ snowball search will be conducted for the references of systematic reviews. Finally, we will contact experts in the field and use social media to identify relevant studies.

We will search using controlled subject headings and keywords of the following concepts: Terms related to 1) COVID-19 OR COVID OR SARS-CoV-2; 2) symptoms OR clinical features OR signs OR characteristics OR sequelae OR complications; 3) long-term OR post-acute OR long-tail OR persistent OR chronic COVID OR long COVID OR post discharge OR prolonged symptoms OR long haul. The search terms were piloted on Pubmed and CINAHL through the EBSCO database host the week starting 14^th September 2020 to ensure that high profile research articles on long covid were included. No important studies were missed.

An example is shown below:

MEDLINE Search (16/3/2021)
S1. COVID-19 OR OR covid OR SARS-CoV-2. ab
S2. symptom* OR "clinical features" OR signs OR characteristic* OR sequelae OR complication*.ab
S3. "long-term Covid" OR long-term N2 consequence* OR "long-term impact" OR "long-term effect" OR "post- acute" OR long-tail OR persist* OR "chronic-COVID" OR "long-COVID" OR post-discharge OR postdischarge OR "prolonged symptom" OR "long-haul" .ab
S4. S1 AND S2 AND S3	1952

Screening

Search results will be managed and screened using a review online platform, Rayyan¹². Initial screening of titles and abstracts as well as full text screening against the inclusion criteria will be done by two reviewers independently. Non-English articles will be translated using Google Translate or reviewed by a reviewer with good knowledge of the language. Disagreements for inclusion will be resolved by consensus. Where disagreements cannot be resolved, a third researcher will review the papers to make the final decision.

Risk of bias

We will be using the Hoy et al. checklist¹³ to critically appraise the studies included in the review, a validated tool for assessing risk of bias in prevalence studies.

Data extraction

The following information will be extracted from each study based on an extraction form informed by a previous review²: study aim, country of study, setting, method, study design, population size and characteristics, types and frequency of symptoms reported, onset and duration of symptoms, treatment and possible risk factors. Data extraction will be performed by one reviewer and checked by a second reviewer. Disagreements will be resolved through discussion and consensus.

Outcomes

The primary outcome is to characterise the prevalence of symptoms and complications of long term Covid-19 in different populations. Secondary outcomes include diagnostics and risk factors for developing different sequelae.

Data analysis

We will use descriptive analysis, and present proportion of symptoms and estimate their 95% confidence intervals (CIs) using the exact method. When more than two studies provide information on a symptom, we will perform a meta-analysis using a random intercept logistic regression model. Heterogeneity between estimates will be assessed using the I² statistic.

Where data is available, we will explore key factors that affect prevalence estimates, e.g. hospitalisation, settings, location of the study, sex and follow-up timing using subgroup analysis and meta-regression analysis. We will identify these factors by discussing with our clinical experts and patient advocates and by reviewing the literature. The division for key factors used in subgroup analysis will depend on the availability of reported data across studies. We will align the division with the literature and expert opinions to form exploratory analysis and to help the interpretation.

We will also conduct sensitivity analysis to examine the impact of high risk of bias studies and conventional statistical methods on the prevalence estimates, e.g. Freeman-Tukey Double arcsine transformation using inverse variance meta-analysis. All analysis and data presentation will be performed using meta and ggplot2 in R (version 4.0.5 or above) via RStudio (version 1.3.1093 or above).

We will work with patient advocates to present the data to facilitate transcription to lay audiences.

Protocol registration

This protocol report is structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement guidelines¹⁴, was registered with PROSPERO (CRD42020211131, 25 September 2020). The protocol will be updated as we progress with the living review as and if needed. CS is the guarantor for this study.

Data availability

Underlying data

No underlying data are associated with this article.

Reporting guidelines

Figshare: PRISMA-P checklist for “What are the long-term symptoms and complications of COVID-19: a protocol for a living systematic review”. https://doi.org/10.25383/city.13187456.v1¹⁵.

Faculty Opinions recommended

References

1. CDC: Coronavirus Disease 2019 (COVID-19). Cent Dis Control Prev. 2020; (accessed 6 Aug 2020). Reference Source
2. Michelen M, Jones N, Stavropoulou C: In patients of COVID-19, what are the symptoms and clinical features of mild and moderate cases? (accessed 6 Aug 2020). Reference Source
3. Rayner C, Lokugamage AU, Molokhia M: Covid-19: Prolonged and relapsing course of illness has implications for returning workers. 2020; (accessed 6 Aug 2020). Reference Source
4. Garner P: Paul Garner: Covid-19 at 14 weeks—phantom speed cameras, unknown limits, and harsh penalties. The BMJ. (accessed 6 Aug 2020). Reference Source
5. Carfì A, Bernabei R, Landi F, et al.: Persistent Symptoms in Patients After Acute COVID-19. JAMA. 2020; 324(6): 603–5. PubMed Abstract | Publisher Full Text | Free Full Text
6. Greenhalgh T, Knight M, A’Court C, et al.: Management of post-acute covid-19 in primary care. BMJ. 2020; 370: m3026. PubMed Abstract | Publisher Full Text
7. Tenforde MW: Symptom Duration and Risk Factors for Delayed Return to Usual Health Among Outpatients with COVID-19 in a Multistate Health Care Systems Network — United States, March–June 2020. MMWR Morb Mortal Wkly Rep. 2020; 69: 993–998. Publisher Full Text
8. Sigfrid L, Cevik M, Jesudason E, et al.: What is the recovery rate and risk of long-term consequences following a diagnosis of COVID-19? - A harmonised, global longitudinal observational study. medRxiv. 2020. Publisher Full Text
9. NHS England and NHS Improvement: After-care needs of inpatients recovering from COVID-19. 2020; (accessed 24 Sep 2020). Reference Source
10. British Society for Immunology: COVID-19 immunology briefing note: What we know about long-term health consequences and priorities for research. Immunology. 2020. Reference Source
11. Elliott JH, Synnot A, Turner T, et al.: Living systematic review: 1. Introduction-the why, what, when, and how. J Clin Epidemiol. 2017; 91: 23–30. PubMed Abstract | Publisher Full Text
12. Ouzzani M, Hammady H, Fedorowicz Z, et al.: Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016; 5(1): 210. PubMed Abstract | Publisher Full Text | Free Full Text
13. Hoy D, Brooks P, Woolf A, et al.: Assessing risk of bias in prevalence studies: modification of an existing tool and evidence of interrater agreement. J Clin Epidemiol. 2012; 65(9): 934–9. PubMed Abstract | Publisher Full Text
14. Moher D, Shamseer L, Clarke M, et al.: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015; 4(1): 1. PubMed Abstract | Publisher Full Text | Free Full Text
15. Michelen M, Sigfrid L, Manoharan L, et al.: What are the long-term symptoms and complications of COVID-19: a protocol for a living systematic review. City, University of London. Journal contribution. 2020. http://www.doi.org/10.25383/city.13187456.v1

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Version 2

VERSION 2 PUBLISHED 14 Dec 2020