Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review

Background. Hundreds of coronavirus disease 2019 (COVID-19) clinical practice guidelines (CPGs) and expert consensus statements have been developed and published since the outbreak of the epidemic. However, these CPGs are of widely variable quality. So, this review is aimed at systematically evaluat...

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Main Authors: Siya Zhao, Shuya Lu, Shouyuan Wu, Zijun Wang, Qiangqiang Guo, Qianling Shi, Hairong Zhang, Juanjuan Zhang, Hui Liu, Yunlan Liu, Xianzhuo Zhang, Ling Wang, Mengjuan Ren, Ping Wang, Hui Lan, Qi Zhou, Yajia Sun, Jin Cao, Qinyuan Li, Janne Estill, Joseph L. Mathew, Hyeong Sik Ahn, Myeong Soo Lee, Xiaohui Wang, Chenyan Zhou, Yaolong Chen
Format: Article
Language:English
Published: American Association for the Advancement of Science (AAAS) 2021-01-01
Series:Health Data Science
Online Access:http://dx.doi.org/10.34133/2021/9806173
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author Siya Zhao
Siya Zhao
Shuya Lu
Shuya Lu
Shouyuan Wu
Zijun Wang
Qiangqiang Guo
Qianling Shi
Hairong Zhang
Juanjuan Zhang
Hui Liu
Yunlan Liu
Xianzhuo Zhang
Ling Wang
Mengjuan Ren
Ping Wang
Hui Lan
Qi Zhou
Yajia Sun
Jin Cao
Qinyuan Li
Janne Estill
Janne Estill
Joseph L. Mathew
Hyeong Sik Ahn
Hyeong Sik Ahn
Hyeong Sik Ahn
Hyeong Sik Ahn
Myeong Soo Lee
Myeong Soo Lee
Myeong Soo Lee
Myeong Soo Lee
Xiaohui Wang
Chenyan Zhou
Chenyan Zhou
Yaolong Chen
Yaolong Chen
Yaolong Chen
Yaolong Chen
Yaolong Chen
Yaolong Chen
spellingShingle Siya Zhao
Siya Zhao
Shuya Lu
Shuya Lu
Shouyuan Wu
Zijun Wang
Qiangqiang Guo
Qianling Shi
Hairong Zhang
Juanjuan Zhang
Hui Liu
Yunlan Liu
Xianzhuo Zhang
Ling Wang
Mengjuan Ren
Ping Wang
Hui Lan
Qi Zhou
Yajia Sun
Jin Cao
Qinyuan Li
Janne Estill
Janne Estill
Joseph L. Mathew
Hyeong Sik Ahn
Hyeong Sik Ahn
Hyeong Sik Ahn
Hyeong Sik Ahn
Myeong Soo Lee
Myeong Soo Lee
Myeong Soo Lee
Myeong Soo Lee
Xiaohui Wang
Chenyan Zhou
Chenyan Zhou
Yaolong Chen
Yaolong Chen
Yaolong Chen
Yaolong Chen
Yaolong Chen
Yaolong Chen
Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review
Health Data Science
author_facet Siya Zhao
Siya Zhao
Shuya Lu
Shuya Lu
Shouyuan Wu
Zijun Wang
Qiangqiang Guo
Qianling Shi
Hairong Zhang
Juanjuan Zhang
Hui Liu
Yunlan Liu
Xianzhuo Zhang
Ling Wang
Mengjuan Ren
Ping Wang
Hui Lan
Qi Zhou
Yajia Sun
Jin Cao
Qinyuan Li
Janne Estill
Janne Estill
Joseph L. Mathew
Hyeong Sik Ahn
Hyeong Sik Ahn
Hyeong Sik Ahn
Hyeong Sik Ahn
Myeong Soo Lee
Myeong Soo Lee
Myeong Soo Lee
Myeong Soo Lee
Xiaohui Wang
Chenyan Zhou
Chenyan Zhou
Yaolong Chen
Yaolong Chen
Yaolong Chen
Yaolong Chen
Yaolong Chen
Yaolong Chen
author_sort Siya Zhao
title Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review
title_short Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review
title_full Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review
title_fullStr Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review
title_full_unstemmed Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review
title_sort analysis of covid-19 guideline quality and change of recommendations: a systematic review
publisher American Association for the Advancement of Science (AAAS)
series Health Data Science
issn 2765-8783
publishDate 2021-01-01
description Background. Hundreds of coronavirus disease 2019 (COVID-19) clinical practice guidelines (CPGs) and expert consensus statements have been developed and published since the outbreak of the epidemic. However, these CPGs are of widely variable quality. So, this review is aimed at systematically evaluating the methodological and reporting qualities of COVID-19 CPGs, exploring factors that may influence their quality, and analyzing the change of recommendations in CPGs with evidence published. Methods. We searched five electronic databases and five websites from 1 January to 31 December 2020 to retrieve all COVID-19 CPGs. The assessment of the methodological and reporting qualities of CPGs was performed using the AGREE II instrument and RIGHT checklist. Recommendations and evidence used to make recommendations in the CPGs regarding some treatments for COVID-19 (remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir) were also systematically assessed. And the statistical inference was performed to identify factors associated with the quality of CPGs. Results. We included a total of 92 COVID-19 CPGs developed by 19 countries. Overall, the RIGHT checklist reporting rate of COVID-19 CPGs was 33.0%, and the AGREE II domain score was 30.4%. The overall methodological and reporting qualities of COVID-19 CPGs gradually improved during the year 2020. Factors associated with high methodological and reporting qualities included the evidence-based development process, management of conflicts of interest, and use of established rating systems to assess the quality of evidence and strength of recommendations. The recommendations of only seven (7.6%) CPGs were informed by a systematic review of evidence, and these seven CPGs have relatively high methodological and reporting qualities, in which six of them fully meet the Institute of Medicine (IOM) criteria of guidelines. Besides, a rapid advice CPG developed by the World Health Organization (WHO) of the seven CPGs got the highest overall scores in methodological (72.8%) and reporting qualities (83.8%). Many CPGs covered the same clinical questions (it refers to the clinical questions on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir in COVID-19 patients) and were published by different countries or organizations. Although randomized controlled trials and systematic reviews on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir for patients with COVID-19 have been published, the recommendations on those treatments still varied greatly across COVID-19 CPGs published in different countries or regions, which may suggest that the CPGs do not make sufficient use of the latest evidence. Conclusions. Both the methodological and reporting qualities of COVID-19 CPGs increased over time, but there is still room for further improvement. The lack of effective use of available evidence and management of conflicts of interest were the main reasons for the low quality of the CPGs. The use of formal rating systems for the quality of evidence and strength of recommendations may help to improve the quality of CPGs in the context of the COVID-19 pandemic. During the pandemic, we suggest developing a living guideline of which recommendations are supported by a systematic review for it can facilitate the timely translation of the latest research findings to clinical practice. We also suggest that CPG developers should register the guidelines in a registration platform at the beginning for it can reduce duplication development of guidelines on the same clinical question, increase the transparency of the development process, and promote cooperation among guideline developers all over the world. Since the International Practice Guideline Registry Platform has been created, developers could register guidelines prospectively and internationally on this platform.
url http://dx.doi.org/10.34133/2021/9806173
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spelling doaj-1cb045648bbc4f54a63d5141e2b4e3e32021-10-07T07:59:46ZengAmerican Association for the Advancement of Science (AAAS)Health Data Science2765-87832021-01-01202110.34133/2021/9806173Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic ReviewSiya Zhao0Siya Zhao1Shuya Lu2Shuya Lu3Shouyuan Wu4Zijun Wang5Qiangqiang Guo6Qianling Shi7Hairong Zhang8Juanjuan Zhang9Hui Liu10Yunlan Liu11Xianzhuo Zhang12Ling Wang13Mengjuan Ren14Ping Wang15Hui Lan16Qi Zhou17Yajia Sun18Jin Cao19Qinyuan Li20Janne Estill21Janne Estill22Joseph L. Mathew23Hyeong Sik Ahn24Hyeong Sik Ahn25Hyeong Sik Ahn26Hyeong Sik Ahn27Myeong Soo Lee28Myeong Soo Lee29Myeong Soo Lee30Myeong Soo Lee31Xiaohui Wang32Chenyan Zhou33Chenyan Zhou34Yaolong Chen35Yaolong Chen36Yaolong Chen37Yaolong Chen38Yaolong Chen39Yaolong Chen40School of Public Health,Lanzhou University,Lanzhou,ChinaInstitute of Health Data Science,Lanzhou University,Lanzhou,ChinaDepartment of Pediatric,Sichuan Provincial People’s Hospital,University of Electronic Science and Technology of China,Chengdu,ChinaChinese Academy of Sciences Sichuan Translational Medicine Research Hospital,Chengdu,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaEvidence-Based Medicine Center,School of Basic Medical Sciences,Lanzhou University,Lanzhou,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaThe First School of Clinical Medicine,Lanzhou University,Lanzhou,ChinaEvidence-Based Medicine Center,School of Basic Medical Sciences,Lanzhou University,Lanzhou,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaThe First School of Clinical Medicine,Lanzhou University,Lanzhou,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaEvidence-Based Medicine Center,School of Basic Medical Sciences,Lanzhou University,Lanzhou,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaEvidence-Based Medicine Center,School of Basic Medical Sciences,Lanzhou University,Lanzhou,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaNational Clinical Research Center for Child Health and Disorders,Ministry of Education Key Laboratory of Child Development and Disorders,China International Science and Technology Cooperation Base of Child Development and Critical Disorders,Children’s Hospital of Chongqing Medical University, Chongqing,ChinaInstitute of Global Health,University of Geneva,Geneva,SwitzerlandInstitute of Mathematical Statistics and Actuarial Science,University of Bern,Bern,SwitzerlandAdvanced Pediatrics Centre,PGIMER Chandigarh,Chandigarh,IndiaDepartment of Preventive Medicine,Korea University,Seoul,Republic of KoreaKorea Cochrane Centre,Seoul,Republic of KoreaEvidence Based Medicine,Seoul,Republic of KoreaKorea University School of Medicine,Seoul,Republic of KoreaKorea Institute of Oriental Medicine,Daejeon,Republic of KoreaUniversity of Science and Technology,Daejeon,Republic of KoreaLondon Southbank University,London,UKTianjin University of Traditional Chinese Medicine,Tianjin,ChinaSchool of Public Health,Lanzhou University,Lanzhou,ChinaDepartment of Pediatric,Sichuan Provincial People’s Hospital,University of Electronic Science and Technology of China,Chengdu,ChinaChinese Academy of Sciences Sichuan Translational Medicine Research Hospital,Chengdu,ChinaInstitute of Health Data Science,Lanzhou University,Lanzhou,ChinaEvidence-Based Medicine Center,School of Basic Medical Sciences,Lanzhou University,Lanzhou,ChinaWHO Collaborating Centre for Guideline Implementation and Knowledge Translation,Lanzhou,ChinaGuideline International Network Asia,ChinaKey Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province,Lanzhou University,Lanzhou,ChinaLanzhou University GRADE Center,ChinaBackground. Hundreds of coronavirus disease 2019 (COVID-19) clinical practice guidelines (CPGs) and expert consensus statements have been developed and published since the outbreak of the epidemic. However, these CPGs are of widely variable quality. So, this review is aimed at systematically evaluating the methodological and reporting qualities of COVID-19 CPGs, exploring factors that may influence their quality, and analyzing the change of recommendations in CPGs with evidence published. Methods. We searched five electronic databases and five websites from 1 January to 31 December 2020 to retrieve all COVID-19 CPGs. The assessment of the methodological and reporting qualities of CPGs was performed using the AGREE II instrument and RIGHT checklist. Recommendations and evidence used to make recommendations in the CPGs regarding some treatments for COVID-19 (remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir) were also systematically assessed. And the statistical inference was performed to identify factors associated with the quality of CPGs. Results. We included a total of 92 COVID-19 CPGs developed by 19 countries. Overall, the RIGHT checklist reporting rate of COVID-19 CPGs was 33.0%, and the AGREE II domain score was 30.4%. The overall methodological and reporting qualities of COVID-19 CPGs gradually improved during the year 2020. Factors associated with high methodological and reporting qualities included the evidence-based development process, management of conflicts of interest, and use of established rating systems to assess the quality of evidence and strength of recommendations. The recommendations of only seven (7.6%) CPGs were informed by a systematic review of evidence, and these seven CPGs have relatively high methodological and reporting qualities, in which six of them fully meet the Institute of Medicine (IOM) criteria of guidelines. Besides, a rapid advice CPG developed by the World Health Organization (WHO) of the seven CPGs got the highest overall scores in methodological (72.8%) and reporting qualities (83.8%). Many CPGs covered the same clinical questions (it refers to the clinical questions on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir in COVID-19 patients) and were published by different countries or organizations. Although randomized controlled trials and systematic reviews on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir for patients with COVID-19 have been published, the recommendations on those treatments still varied greatly across COVID-19 CPGs published in different countries or regions, which may suggest that the CPGs do not make sufficient use of the latest evidence. Conclusions. Both the methodological and reporting qualities of COVID-19 CPGs increased over time, but there is still room for further improvement. The lack of effective use of available evidence and management of conflicts of interest were the main reasons for the low quality of the CPGs. The use of formal rating systems for the quality of evidence and strength of recommendations may help to improve the quality of CPGs in the context of the COVID-19 pandemic. During the pandemic, we suggest developing a living guideline of which recommendations are supported by a systematic review for it can facilitate the timely translation of the latest research findings to clinical practice. We also suggest that CPG developers should register the guidelines in a registration platform at the beginning for it can reduce duplication development of guidelines on the same clinical question, increase the transparency of the development process, and promote cooperation among guideline developers all over the world. Since the International Practice Guideline Registry Platform has been created, developers could register guidelines prospectively and internationally on this platform.http://dx.doi.org/10.34133/2021/9806173