WITHDRAWN: The comparison of the effectiveness of lincocin® and azitro® in the treatment of covid-19-associated pneumonia: A prospective study

Clinical trials in COVID-19 management & prevention: A meta-epidemiological study examining methodological quality

OBJECTIVE

To describe the characteristics of Covid-19 randomized clinical trials (RCTs) and examine the association between trial characteristics and the likelihood of finding a significant effect.

STUDY DESIGN

We conducted a systematic review to identify RCTs (up to October 21, 2020) evaluating drugs or blood products to treat or prevent Covid-19. We extracted trial characteristics (number of centers, funding sources, and sample size) and assessed risk of bias (RoB) using the Cochrane RoB 2.0 tool. We performed logistic regressions to evaluate the association between RoB due to randomization, single vs. multicentre, funding source, and sample size, and finding a statistically significant effect.

RESULTS

We included 91 RCTs (n = 46,802); 40 (44%) were single-center, 23 (25.3%) enrolled <50 patients, 28 (30.8%) received industry funding, and 75 (82.4%) had high or probably high RoB. Thirty-eight trials (41.8%) reported a statistically significant effect. RoB due to randomization and being a single-center trial were associated with increased odds of finding a statistically significant effect.

CONCLUSIONS

There is high variability in RoB among Covid-19 trials. Researchers, funders, and knowledge-users should be cognizant of the impact of RoB due to randomization and single-center trial status in designing, evaluating, and interpreting the results of RCTs.

REGISTRATION

CRD42020192095.

Antibiotics for the treatment of COVID-19

BACKGROUND

The effect of antibiotics with potential antiviral and anti-inflammatory properties are being investigated in clinical trials as treatment for COVID-19. The use of antibiotics follows the intention-to-treat the viral disease and not primarily to treat bacterial co-infections of individuals with COVID-19. A thorough understanding of the current evidence regarding effectiveness and safety of antibiotics as anti-viral treatments for COVID-19 based on randomised controlled trials (RCTs) is required.

OBJECTIVES

To assess the efficacy and safety of antibiotics compared to each other, no treatment, standard of care alone, placebo, or any other active intervention with proven efficacy for treatment of COVID-19 outpatients and inpatients.  SEARCH METHODS: We searched the Cochrane COVID-19 Study Register (including MEDLINE, Embase, ClinicalTrials.gov, WHO ICTRP, medRxiv, CENTRAL), Web of Science and WHO COVID-19 Global literature on coronavirus disease to identify completed and ongoing studies to 14 June 2021.

SELECTION CRITERIA

RCTs were included that compared antibiotics with each other, no treatment, standard of care alone, placebo, or another proven intervention, for treatment of people with confirmed COVID-19, irrespective of disease severity, treated in the in- or outpatient settings. Co-interventions had to be the same in both study arms. We excluded studies comparing antibiotics to other pharmacological interventions with unproven efficacy.

DATA COLLECTION AND ANALYSIS

We assessed risk of bias of primary outcomes using the Cochrane risk of bias tool (ROB 2) for RCTs. We used GRADE to rate the certainty of evidence for the following primary outcomes: 1. to treat inpatients with moderate to severe COVID-19: mortality, clinical worsening defined as new need for intubation or death, clinical improvement defined as being discharged alive, quality of life, adverse and serious adverse events, and cardiac arrhythmias; 2. to treat outpatients with asymptomatic or mild COVID-19: mortality, clinical worsening defined as hospital admission or death, clinical improvement defined as symptom resolution, quality of life, adverse and serious adverse events, and cardiac arrhythmias.

MAIN RESULTS

We included 11 studies with 11,281 participants with an average age of 54 years investigating antibiotics compared to placebo, standard of care alone or another antibiotic. No study was found comparing antibiotics to an intervention with proven efficacy. All studies investigated azithromycin, two studies investigated other antibiotics compared to azithromycin. Seven studies investigated inpatients with moderate to severe COVID-19 and four investigated mild COVID-19 cases in outpatient settings. Eight studies had an open-label design, two were blinded with a placebo control, and one did not report on blinding. We identified 19 ongoing and 15 studies awaiting classification pending publication of results or clarification of inconsistencies. Of the 30 study results contributing to primary outcomes by included studies, 17 were assessed as overall low risk and 13 as some concerns of bias. Only studies investigating azithromycin reported data eligible for the prioritised primary outcomes. Azithromycin doses and treatment duration varied among included studies.  Azithromycin for the treatment of COVID-19 compared to placebo or standard of care alone in inpatients We are very certain that azithromycin has little or no effect on all-cause mortality at day 28 compared to standard of care alone (risk ratio (RR) 0.98; 95% confidence interval (CI) 0.90 to 1.06; 8600 participants; 4 studies; high-certainty evidence). Azithromycin probably has little or no effect on clinical worsening or death at day 28 (RR 0.95; 95% CI 0.87 to 1.03; 7311 participants; 1 study; moderate-certainty evidence), on clinical improvement at day 28 (RR 0.96; 95% CI 0.84 to 1.11; 8172 participants; 3 studies; moderate-certainty evidence), on serious adverse events during the study period (RR 1.11; 95% CI 0.89 to 1.40; 794 participants; 4 studies; moderate-certainty evidence), and cardiac arrhythmias during the study period (RR 0.92; 95% CI 0.73 to 1.15; 7865 participants; 4 studies; moderate-certainty evidence) compared to placebo or standard of care alone. Azithromycin may increase any adverse events slightly during the study period (RR 1.20; 95% CI 0.92 to 1.57; 355 participants; 3 studies; low-certainty evidence) compared to standard of care alone. No study reported quality of life up to 28 days. Azithromycin for the treatment of COVID-19 compared to placebo or standard of care alone in outpatients Azithromycin may have little or no effect compared to placebo or standard of care alone on all-cause mortality at day 28 (RR 1.00 ; 95% CI 0.06 to 15.69; 876 participants; 3 studies; low-certainty evidence), on admission to hospital or death within 28 days (RR 0.94 ; 95% CI 0.57 to 1.56; 876 participants; 3 studies; low-certainty evidence), and on symptom resolution at day 14 (RR 1.03; 95% CI 0.95 to 1.12; 138 participants; 1 study; low-certainty evidence). We are uncertain whether azithromycin increases or reduces serious adverse events compared to placebo or standard of care alone (0 participants experienced serious adverse events; 454 participants; 2 studies; very low-certainty evidence). No study reported on adverse events, cardiac arrhythmias during the study period or quality of life up to 28 days. Azithromycin for the treatment of COVID-19 compared to any other antibiotics in inpatients and outpatients One study compared azithromycin to lincomycin in inpatients, but did not report any primary outcome. Another study compared azithromycin to clarithromycin in outpatients, but did not report any relevant outcome for this review.

AUTHORS' CONCLUSIONS

We are certain that risk of death in hospitalised COVID-19 patients is not reduced by treatment with azithromycin after 28 days. Further, based on moderate-certainty evidence, patients in the inpatient setting with moderate and severe disease probably do not benefit from azithromycin used as potential antiviral and anti-inflammatory treatment for COVID-19 regarding clinical worsening or improvement. For the outpatient setting, there is currently low-certainty evidence that azithromycin may have no beneficial effect for COVID-19 individuals. There is no evidence from RCTs available for other antibiotics as antiviral and anti-inflammatory treatment of COVID-19. With accordance to the living approach of this review, we will continually update our search and include eligible trials to fill this evidence gap. However, in relation to the evidence for azithromycin and in the context of antimicrobial resistance, antibiotics should not be used for treatment of COVID-19 outside well-designed RCTs.

Interactive Mechanism of Potential Inhibitors with Glycosyl for SARS-CoV-2 by Molecular Dynamics Simulation

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a type of Ribonucleic Acid (RNA) coronavirus and it has infected and killed many people around the world. It is reported that the receptor binding domain of the spike protein (S_RBD) of the SARS-CoV-2 virus is responsible for attachment to human angiotensin converting enzyme II (ACE2). Many researchers are attempting to search potential inhibitors for fighting SARS-CoV-2 infection using theoretical or experimental methods. In terms of experimental and theoretical research, Cefuroxime, Erythromycin, Lincomycin and Ofloxacin are the potential inhibitors of SARS-CoV-2. However, the interactive mechanism of the protein SARS-CoV-2 and the inhibitors are still elusive. Here, we investigated the interactions between S_RBD and the inhibitors using molecular dynamics (MD) simulations. Interestingly, we found that there are two binding sites of S_RBD for the four small molecules. In addition, our analysis also illustrated that hydrophobic and π-π stacking interactions play crucial roles in the interactions between S_RBD and the small molecules. In our work, we also found that small molecules with glycosyl group have more effect on the conformation of S_RBD than other inhibitors, and they are also potential inhibitors for the genetic variants of SARS-CoV-2. This study provides in silico-derived mechanistic insights into the interactions of S_RBD and inhibitors, which may provide new clues for fighting SARS-CoV-2 infection.

Comparative effectiveness and safety of 32 pharmacological interventions recommended by guidelines for coronavirus disease 2019: a systematic review and network meta-analysis combining 66 trials

BACKGROUND

The global pandemic coronavirus disease 2019 (COVID-19) has become a major public health problem and presents an unprecedented challenge. However, no specific drugs were currently proven. This study aimed to evaluate the comparative efficacy and safety of pharmacological interventions in patients with COVID-19.

METHODS

Medline, Embase, the Cochrane Library, and clinicaltrials.gov were searched for randomized controlled trials (RCTs) in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/SARS-CoV. Random-effects network meta-analysis within the Bayesian framework was performed, followed by the Grading of Recommendations Assessment, Development, and Evaluation system assessing the quality of evidence. The primary outcome of interest includes mortality, cure, viral negative conversion, and overall adverse events (OAEs). Odds ratio (OR) with 95% confidence interval (CI) was calculated as the measure of effect size.

RESULTS

Sixty-six RCTs with 19,095 patients were included, involving standard of care (SOC), eight different antiviral agents, six different antibiotics, high and low dose chloroquine (CQ_HD, CQ_LD), traditional Chinese medicine (TCM), corticosteroids (COR), and other treatments. Compared with SOC, a significant reduction of mortality was observed for TCM (OR = 0.34, 95% CI: 0.20-0.56, moderate quality) and COR (OR = 0.84, 95% CI: 0.75-0.96, low quality) with improved cure rate (OR = 2.16, 95% CI: 1.60-2.91, low quality for TCM; OR = 1.17, 95% CI: 1.05-1.30, low quality for COR). However, an increased risk of mortality was found for CQ_HD vs. SOC (OR = 3.20, 95% CI: 1.18-8.73, low quality). TCM was associated with decreased risk of OAE (OR = 0.52, 95% CI: 0.38-0.70, very low quality) but CQ_HD (OR = 2.51, 95% CI: 1.20-5.24) and interferons (IFN) (OR = 2.69, 95% CI: 1.02-7.08) vs. SOC with very low quality were associated with an increased risk.

CONCLUSIONS

COR and TCM may reduce mortality and increase cure rate with no increased risk of OAEs compared with standard care. CQ_HD might increase the risk of mortality. CQ, IFN, and other antiviral agents could increase the risk of OAEs. The current evidence is generally uncertain with low-quality and further high-quality trials are needed.

How COVID-19 has fundamentally changed clinical research in global health

COVID-19 has had negative repercussions on the entire global population. Despite there being a common goal that should have unified resources and efforts, there have been an overwhelmingly large number of clinical trials that have been registered that are of questionable methodological quality. As the final paper of this Series, we discuss how the medical research community has responded to COVID-19. We recognise the incredible pressure that this pandemic has put on researchers, regulators, and policy makers, all of whom were doing their best to move quickly but safely in a time of tremendous uncertainty. However, the research community's response to the COVID-19 pandemic has prominently highlighted many fundamental issues that exist in clinical trial research under the current system and its incentive structures. The COVID-19 pandemic has not only re-emphasised the importance of well designed randomised clinical trials but also highlighted the need for large-scale clinical trials structured according to a master protocol in a coordinated and collaborative manner. There is also a need for structures and incentives to enable faster data sharing of anonymised datasets, and a need to provide similar opportunities to those in high-income countries for clinical trial research in low-resource regions where clinical trial research receives considerably less research funding.

Interventions for treatment of COVID-19: A living systematic review with meta-analyses and trial sequential analyses (The LIVING Project)

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a rapidly spreading disease that has caused extensive burden to individuals, families, countries, and the world. Effective treatments of COVID-19 are urgently needed.

METHODS AND FINDINGS

This is the first edition of a living systematic review of randomized clinical trials comparing the effects of all treatment interventions for participants in all age groups with COVID-19. We planned to conduct aggregate data meta-analyses, trial sequential analyses, network meta-analysis, and individual patient data meta-analyses. Our systematic review is based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and Cochrane guidelines, and our 8-step procedure for better validation of clinical significance of meta-analysis results. We performed both fixed-effect and random-effects meta-analyses. Primary outcomes were all-cause mortality and serious adverse events. Secondary outcomes were admission to intensive care, mechanical ventilation, renal replacement therapy, quality of life, and nonserious adverse events. We used Grading of Recommendations Assessment, Development and Evaluation (GRADE) to assess the certainty of evidence. We searched relevant databases and websites for published and unpublished trials until August 7, 2020. Two reviewers independently extracted data and assessed trial methodology. We included 33 randomized clinical trials enrolling a total of 13,312 participants. All trials were at overall high risk of bias. We identified one trial randomizing 6,425 participants to dexamethasone versus standard care. This trial showed evidence of a beneficial effect of dexamethasone on all-cause mortality (rate ratio 0.83; 95% confidence interval [CI] 0.75-0.93; p < 0.001; low certainty) and on mechanical ventilation (risk ratio [RR] 0.77; 95% CI 0.62-0.95; p = 0.021; low certainty). It was possible to perform meta-analysis of 10 comparisons. Meta-analysis showed no evidence of a difference between remdesivir versus placebo on all-cause mortality (RR 0.74; 95% CI 0.40-1.37; p = 0.34, I2 = 58%; 2 trials; very low certainty) or nonserious adverse events (RR 0.94; 95% CI 0.80-1.11; p = 0.48, I2 = 29%; 2 trials; low certainty). Meta-analysis showed evidence of a beneficial effect of remdesivir versus placebo on serious adverse events (RR 0.77; 95% CI 0.63-0.94; p = 0.009, I2 = 0%; 2 trials; very low certainty) mainly driven by respiratory failure in one trial. Meta-analyses and trial sequential analyses showed that we could exclude the possibility that hydroxychloroquine versus standard care reduced the risk of all-cause mortality (RR 1.07; 95% CI 0.97-1.19; p = 0.17; I2 = 0%; 7 trials; low certainty) and serious adverse events (RR 1.07; 95% CI 0.96-1.18; p = 0.21; I2 = 0%; 7 trials; low certainty) by 20% or more, and meta-analysis showed evidence of a harmful effect on nonserious adverse events (RR 2.40; 95% CI 2.01-2.87; p < 0.00001; I2 = 90%; 6 trials; very low certainty). Meta-analysis showed no evidence of a difference between lopinavir-ritonavir versus standard care on serious adverse events (RR 0.64; 95% CI 0.39-1.04; p = 0.07, I2 = 0%; 2 trials; very low certainty) or nonserious adverse events (RR 1.14; 95% CI 0.85-1.53; p = 0.38, I2 = 75%; 2 trials; very low certainty). Meta-analysis showed no evidence of a difference between convalescent plasma versus standard care on all-cause mortality (RR 0.60; 95% CI 0.33-1.10; p = 0.10, I2 = 0%; 2 trials; very low certainty). Five single trials showed statistically significant results but were underpowered to confirm or reject realistic intervention effects. None of the remaining trials showed evidence of a difference on our predefined outcomes. Because of the lack of relevant data, it was not possible to perform other meta-analyses, network meta-analysis, or individual patient data meta-analyses. The main limitation of this living review is the paucity of data currently available. Furthermore, the included trials were all at risks of systematic errors and random errors.

CONCLUSIONS

Our results show that dexamethasone and remdesivir might be beneficial for COVID-19 patients, but the certainty of the evidence was low to very low, so more trials are needed. We can exclude the possibility of hydroxychloroquine versus standard care reducing the risk of death and serious adverse events by 20% or more. Otherwise, no evidence-based treatment for COVID-19 currently exists. This review will continuously inform best practice in treatment and clinical research of COVID-19.

Drug treatments for covid-19: living systematic review and network meta-analysis

OBJECTIVE

To compare the effects of treatments for coronavirus disease 2019 (covid-19).

DESIGN

Living systematic review and network meta-analysis.

DATA SOURCES

WHO covid-19 database, a comprehensive multilingual source of global covid-19 literature, up to 3 December 2021 and six additional Chinese databases up to 20 February 2021. Studies identified as of 1 December 2021 were included in the analysis.

STUDY SELECTION

Randomised clinical trials in which people with suspected, probable, or confirmed covid-19 were randomised to drug treatment or to standard care or placebo. Pairs of reviewers independently screened potentially eligible articles.

METHODS

After duplicate data abstraction, a bayesian network meta-analysis was conducted. Risk of bias of the included studies was assessed using a modification of the Cochrane risk of bias 2.0 tool, and the certainty of the evidence using the grading of recommendations assessment, development, and evaluation (GRADE) approach. For each outcome, interventions were classified in groups from the most to the least beneficial or harmful following GRADE guidance.

RESULTS

463 trials enrolling 166 581 patients were included; 267 (57.7%) trials and 89 814 (53.9%) patients are new from the previous iteration; 265 (57.2%) trials evaluating treatments with at least 100 patients or 20 events met the threshold for inclusion in the analyses. Compared with standard care, three drugs reduced mortality in patients with mostly severe disease with at least moderate certainty: systemic corticosteroids (risk difference 23 fewer per 1000 patients, 95% credible interval 40 fewer to 7 fewer, moderate certainty), interleukin-6 receptor antagonists when given with corticosteroids (23 fewer per 1000, 36 fewer to 7 fewer, moderate certainty), and Janus kinase inhibitors (44 fewer per 1000, 64 fewer to 20 fewer, high certainty). Compared with standard care, two drugs probably reduce hospital admission in patients with non-severe disease: nirmatrelvir/ritonavir (36 fewer per 1000, 41 fewer to 26 fewer, moderate certainty) and molnupiravir (19 fewer per 1000, 29 fewer to 5 fewer, moderate certainty). Remdesivir may reduce hospital admission (29 fewer per 1000, 40 fewer to 6 fewer, low certainty). Only molnupiravir had at least moderate quality evidence of a reduction in time to symptom resolution (3.3 days fewer, 4.8 fewer to 1.6 fewer, moderate certainty); several others showed a possible benefit. Several drugs may increase the risk of adverse effects leading to drug discontinuation; hydroxychloroquine probably increases the risk of mechanical ventilation (moderate certainty).

CONCLUSION

Corticosteroids, interleukin-6 receptor antagonists, and Janus kinase inhibitors probably reduce mortality and confer other important benefits in patients with severe covid-19. Molnupiravir and nirmatrelvir/ritonavir probably reduce admission to hospital in patients with non-severe covid-19.

SYSTEMATIC REVIEW REGISTRATION

This review was not registered. The protocol is publicly available in the supplementary material.

READERS' NOTE

This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This is the fifth version of the original article published on 30 July 2020 (BMJ 2020;370:m2980), and previous versions can be found as data supplements. When citing this paper please consider adding the version number and date of access for clarity.