Coronavirus Disease 2019 Related Clinical Studies: A Cross-Sectional Analysis

Lü, Lin; Xia, Yin; Li, Bing Hui; Yang, Jia; Jin, Ying; Huang, Di; Deng, Tao; Wang, Yun Yun; Ren, Xue Qun; Ji, Jianguang; Zeng, Xi

doi:10.3389/fphar.2020.540187

Cited by 4 publications

(5 citation statements)

References 44 publications

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“…In initial phases of CEST (late March 2020), the chief focus was on the rapid synthesis of the evidence. In the more recent period, weaknesses have been identified in the design and conduct of some of the published and pre‐print literature 30‐32 . Especially in the initial phases of COVID‐19, for example, many of the COVID‐19 clinical trials lacked critical design features such as standard sample size, randomized allocation, the use of control groups, and double blinding 30,32 .…”

Section: Discussionmentioning

confidence: 99%

Developing a rapid evidence response toCOVID‐19: The collaborative approach of Saskatchewan, Canada

Groot

Baer

Badea

et al. 2021

Learning Health Systems

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Introduction The COVID‐19 Evidence Support Team (CEST) was a provincial initiative that combined the support of policymakers, researchers, and clinical practitioners to initiate a new learning health cycle (LHS) in response to the pandemic. The primary aim of CEST was to produce and sustain the best available COVID‐19 evidence to facilitate decision‐making in Saskatchewan, Canada. To achieve this objective, four provincial organizations partnered to establish a single, data‐driven system. Methods The CEST partnership was driven by COVID‐19 questions from Emergency Operational Committee (EOC) of the Saskatchewan Health Authority. CEST included three processes: (a) clarifying the nature and priority of COVID‐19 policy and clinical questions; (b) providing Rapid Reviews (RRR) and Evidence Search Reports (ESR); and (c) seeking the requestors' evaluation of the product. A web‐based repository, including a dashboard and database, was designed to house ESRs and RRRs and offered a common platform for clinicians, academics, leaders, and policymakers to find COVID‐19 evidence. Results In CEST's first year, 114 clinical and policy questions have been posed resulting in 135 ESRs and 108 RRRs. While most questions (41.3%) originated with the EOC, several other teams were assembled to address a myriad of questions related to areas such as long‐term care, public health and prevention, infectious diseases, personal protective equipment, vulnerable populations, and Indigenous health. Initial challenges were mobilization of diverse partners and teams, remote work, lack of public access, and quality of emerging COVID‐19 literature. Current challenges indicate the need for institutional commitment for CEST sustainability. Despite these challenges, the CEST provided the Saskatchewan LHS with a template for successful collaboration. Conclusions The urgency of COVID‐19 pandemic and the implementation of the CEST served to catalyze collaboration between different levels of a Saskatchewan LHS.

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Section: Discussionmentioning

confidence: 99%

Developing a rapid evidence response toCOVID‐19: The collaborative approach of Saskatchewan, Canada

Groot

Baer

Badea

et al. 2021

Learning Health Systems

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“…A few already available antimicrobial drugs such as hydroxychloroquine, azithromycin, chloroquine, remdesivir (RDV), lopinavir, ritonavir, oseltamivir, umifenovir, dexamethasone and favipiravir are under investigation for the treatment of COVID-19. Even though drugs like dexamethasone and RDV have proven to be effective for the treatment of COVID-19, their use is still considered to be controversial ( Ma et al, 2020 ). Moreover, antimicrobial drug resistance (ADR) is an emerging threat to the world due to a variety of technological, socio-economic, microbial, and environmental factors.…”

Section: Introductionmentioning

confidence: 99%

Antimicrobial peptides: A promising tool to combat multidrug resistance in SARS CoV2 era

Saini

Kaur

Malik

et al. 2022

Microbiological Research

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“…To date, 12 other studies have analyzed registered COVID-19 clinical studies [11][12][13][14][15][16][17][18][19][20][21][22] (see Supplementary Material I for details). For example, Wang et in Columbia University Irving Medical Center [22].…”

Section: Introductionmentioning

confidence: 99%

“…For example, Wang et in Columbia University Irving Medical Center [22]. While most of these studies analyzed the basic characteristics of the included trials, some studies further analyzed the interventions [18][19][20][21], locations [13,14,18], data monitoring characteristics [14], timing of the registration and enrollment [15,21], outcomes [19,20], risk of biases [16], Medical Subject Heading (MeSH) keywords (Words or phrases that best describe the protocol) [19],…”

Section: Introductionmentioning

confidence: 99%

How the clinical research community responded to the COVID-19 pandemic: an analysis of the COVID-19 clinical studies in ClinicalTrials.gov

Erdengasileng

Luo

et al. 2021

JAMIA Open

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Objective In the past few months, a large number of clinical studies on the novel coronavirus disease (COVID-19) have been initiated worldwide to find effective therapeutics, vaccines, and preventive strategies for COVID-19. In this study, we aim to understand the landscape of COVID-19 clinical research and identify the issues that may cause recruitment difficulty or reduce study generalizability. Methods We analyzed 3,765 COVID-19 studies registered in the largest public registry - ClinicalTrials.gov, leveraging natural language processing and using descriptive, association, and clustering analyses. We first characterized COVID-19 studies by study features such as phase and tested intervention. We then took a deep dive and analyzed their eligibility criteria to understand whether these studies: (1) considered the reported underlying health conditions that may lead to severe illnesses, and (2) excluded older adults, either explicitly or implicitly, which may reduce the generalizability of these studies to the older adults population. Results Our analysis included 2295 interventional studies and 1470 observational studies. Most trials did not explicitly exclude older adults with common chronic conditions. However, known risk factors such as diabetes and hypertension were considered by less than 5% of trials based on their trial description. Pregnant women were excluded by 34.9% of the studies. Conclusions Most COVID-19 clinical studies included both genders and older adults. However, risk factors such as diabetes, hypertension, and pregnancy were under-represented, likely skewing the population that was sampled. A careful examination of existing COVID-19 studies can inform future COVID-19 trial design towards balanced internal validity and generalizability. Lay Summary Since the outbreak of COVID-19 in early 2020, thousands of clinical studies have been conducted to evaluate the efficacy and safety of various types of treatments and vaccines in human. COVID-19 clinical studies play a crucial role in controlling the virus. Yet it is unclear what types of patients were considered by these studies. This study analyzed 3,765 COVID-19 clinical study summaries downloaded from a major clinical trial registry ClinicalTrials.gov. We employed natural language processing techniques to parse the study description and eligibility criteria of these studies and then performed descriptive and clustering analysis on the parsing results. We found that older adults were not systematically excluded but pregnant women were often excluded. It was also found that the known risk factors such as diabetes, hypertension, obesity, and asthma, which may lead to serious illnesses, were considered by less than 5% of the studies according to their study description and eligibility criteria. This study provides an evidence that natural language processing can be applied to examine the design of clinical studies and identify issues that may cause delays in patient recruitment and the lack of real-world population representativeness.

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Coronavirus Disease 2019 Related Clinical Studies: A Cross-Sectional Analysis

Cited by 4 publications

References 44 publications

Developing a rapid evidence response toCOVID‐19: The collaborative approach of Saskatchewan, Canada

Developing a rapid evidence response toCOVID‐19: The collaborative approach of Saskatchewan, Canada

Antimicrobial peptides: A promising tool to combat multidrug resistance in SARS CoV2 era

How the clinical research community responded to the COVID-19 pandemic: an analysis of the COVID-19 clinical studies in ClinicalTrials.gov

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