Dataset Information

Antiviral drugs for coronavirus disease 2019 (COVID-19): a systematic review with network meta-analysis.

ABSTRACT:

Background

To better inform clinical practice, we summarized the findings from randomized controlled trials (RCTs) of antivirals for COVID-19.

Methods

We systematically searched for literature up to September 2020, and included English-language publications of RCTs among hospitalized COVID-19 patients. We conducted network meta-analysis combining results of both the direct and indirect comparisons of interventions. The efficacy outcomes were clinical progression, all-cause mortality, and viral clearance, and safety outcomes were diarrhea, nausea, and vomiting. We generated treatment rankings (best to worst) and summarized rank probabilities using rankogram.

Results

We included 15 RCTs (14,418 patients) from 7,237 retrieved citations. There was no evidence for efficacy of the assessed antivirals compared with placebo/no treatment or with another antiviral for all efficacy outcomes. Lopinavir (400 mg)/ritonavir (100 mg) significantly increased diarrhea, nausea, and vomiting compared with placebo/no treatment and other antivirals, and was ranked worst for these outcomes, while triazavirin (250 mg), baloxavir marboxil (80 mg), and remdesivir (100 mg - 10 days) ranked best, respectively.

Conclusions and relevance

The available evidence does not support the use of any antiviral drugs for COVID-19. Cautious interpretations of the findings are, however, advised considering the paucity of the evidence. More RCTs are needed for a stronger evidence base.

SUBMITTER: Okoli GN

PROVIDER: S-EPMC8477589 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Publications

Antiviral drugs for coronavirus disease 2019 (COVID-19): a systematic review with network meta-analysis.

Okoli George N GN Rabbani Rasheda R Al-Juboori Amenah A Copstein Leslie L Askin Nicole N Abou-Setta Ahmed M AM

Expert review of anti-infective therapy 20210817 2

<h4>Background</h4>To better inform clinical practice, we summarized the findings from randomized controlled trials (RCTs) of antivirals for COVID-19.<h4>Methods</h4>We systematically searched for literature up to September 2020, and included English-language publications of RCTs among hospitalized COVID-19 patients. We conducted network meta-analysis combining results of both the direct and indirect comparisons of interventions. The efficacy outcomes were clinical progression, all-cause mortali ...[more]

PMID: 34323632

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Project description:Objective:Clinical and laboratory biomarkers to predict the severity of coronavirus disease 2019 (COVID-19) are essential in this pandemic situation of which resource allocation must be urgently prepared especially in the context of respiratory support readiness. Lymphocyte count has been a marker of interest since the first COVID-19 publication. We conducted a systematic review and meta-analysis in order to investigate the association of lymphocyte count on admission and the severity of COVID-19. We would also like to analyze whether patient characteristics such as age and comorbidities affect the relationship between lymphocyte count and COVID-19. Methods:Comprehensive and systematic literature search was performed from PubMed, SCOPUS, EuropePMC, ProQuest, Cochrane Central Databases, and Google Scholar. Research articles in adult patients diagnosed with COVID-19 with information on lymphocyte count and several outcomes of interest, including mortality, acute respiratory distress syndrome (ARDS), intensive care unit (ICU) care, and severe COVID-19, were included in the analysis. Inverse variance method was used to obtain mean differences and its standard deviations. Maentel-Haenszel formula was used to calculate dichotomous variables to obtain odds ratios (ORs) along with its 95% confidence intervals. Random-effect models were used for meta-analysis regardless of heterogeneity. Restricted-maximum likelihood random-effects meta-regression was performed for age, gender, cardiac comorbidity, hypertension, diabetes mellitus, COPD, and smoking. Results:There were a total of 3099 patients from 24 studies. Meta-analysis showed that patients with poor outcome have a lower lymphocyte count (mean difference - 361.06 μL [- 439.18, - 282.95], p < 0.001; I 2 84%) compared to those with good outcome. Subgroup analysis showed lower lymphocyte count in patients who died (mean difference - 395.35 μL [- 165.64, - 625.07], p < 0.001; I 2 87%), experienced ARDS (mean difference - 377.56 μL [- 271.89, - 483.22], p < 0.001; I 2 0%), received ICU care (mean difference - 376.53 μL [- 682.84, - 70.22], p = 0.02; I 2 89%), and have severe COVID-19 (mean difference - 353.34 μL [- 250.94, - 455.73], p < 0.001; I 2 85%). Lymphopenia was associated with severe COVID-19 (OR 3.70 [2.44, 5.63], p < 0.001; I 2 40%). Meta-regression showed that the association between lymphocyte count and composite poor outcome was affected by age (p = 0.034). Conclusion:This meta-analysis showed that lymphopenia on admission was associated with poor outcome in patients with COVID-19.

Project description:Importance: Coronavirus disease 2019 (COVID-19) is a newly emerging infectious disease that has caused a global pandemic. The presenting symptoms are mainly respiratory symptom, yet studies have reported nervous system involvement in the disease. A systematic review and meta-analysis of these studies are required to understanding the neurologic characteristic of the disease and help physicians with early diagnosis and management. Objective: To conduct a systematic review and meta-analysis on the neurologic characteristics in patients with COVID-19. Evidence Review: Authors conducted a literature search through PubMed from January 1st, 2020 to April 8th, 2020. Furthermore, the authors added additional sources by reviewing related references. Studies presenting the neurologic features of COVID-19 patients in their data were included. Case reports and case series were also included in this review. The quality of the studies was assessed based on the Oxford Center for Evidence-Based Medicine guidelines. Selected studies were included in the meta-analysis of proportion and the heterogeneity test. Finding: From 280 identified studies, 33 were eligible, with 7,559 participants included. Most of the included studies were from China (29 [88%]). Muscle injury or myalgia was the most common (19.2%, 95%CI 15.4-23.2%) neurologic symptom of COVID-19, followed by headache (10.9%, 95%CI 8.62-13.51%); dizziness (8.7%, 95%CI 5.02-13.43%); nausea with or without vomiting (4.6%, 95%CI 3.17-6.27%); concurrent cerebrovascular disease (4.4%, 95%CI 1.92-7.91%); and impaired consciousness (3.8%, 95%CI 0.16-12.04%). Underlying cerebrovascular disease was found in 8.5% (95%CI 4.5-13.5%) of the studies. Conclusion: Neurologic findings vary from non-specific to specific symptoms in COVID-19 patients. Some severe symptoms or diseases can present in the later stage of the disease. Physicians should be aware of the presence of neurologic signs and symptoms as a chief complaint of COVID-19, in order to improve management and prevent a worsening outcome of the patients.

Dataset Information

Antiviral drugs for coronavirus disease 2019 (COVID-19): a systematic review with network meta-analysis.

Background

Methods

Results

Conclusions and relevance

Publications

Antiviral drugs for coronavirus disease 2019 (COVID-19): a systematic review with network meta-analysis.

Similar Datasets

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