Randomised controlled trials for COVID-19: evaluation of optimal randomisation methodologies-need for data validation of the completed trials and to improve ongoing and future randomised trial designs

The 100 most-cited articles in COVID-19: a bibliometric analysis

Corona virus disease 2019 (COVID-19) pandemic, sparked by the emergence of a novel coronavirus in early 2020, has prompted a surge in published articles. This study aims to systematically analyse the characteristics and trends of impactful research in the field. The 100 most-cited publications associated with COVID-19 were identified by two independent reviewers using the 'Web of Science' database across all available journals up to the year 2023. Data collected include country, citation count, subject, level of evidence (using Oxford Centre for Evidence-Based Medicine System 2011), impact factor, funding, and study design. We identified 394 038 publications, and the 100 most-cited publications were ranked. These were cited by a total of 283 034 articles (median citation = 767), median impact factor of 66.9 and 72 articles with fundings. China (n = 44), USA (n = 19), and UK (n = 13) were the three highest contributors (n = 220 505). Most articles were level 5 evidence (n = 48), followed by level 3 (n = 28), 4 (n = 14), 2 (n = 7), and 1 (n = 3). The main subjects were mechanism of action and structures of SARS-CoV-2 virus (n = 18) and impact of COVID-19 on public health (n = 18). Publications in 2022 and 2023 predominantly focused on the impact of COVID-19. Majority of the highly cited studies were of low-to-moderate quality, with only 10 consisting of randomized controlled trials or systematic reviews with or without meta-analysis. These findings reflect a growing interest in understanding the impact of COVID-19 pandemic on public and mental health. This analysis found the potential for future double-blinded randomized controlled trials to validate existing findings.

Global landscape of COVID-19 research: a visualization analysis of randomized clinical trials

The emergence of COVID-19 in 2019 has resulted in a significant global health crisis. Consequently, extensive research was published to understand and mitigate the disease. In particular, randomized controlled trials (RCTs) have been considered the benchmark for assessing the efficacy and safety of interventions. Hence, the present study strives to present a comprehensive overview of the global research landscape pertaining to RCTs and COVID-19. A bibliometric analysis was performed using the Scopus database. The search parameters included articles published from 2020 to 2022 using keywords specifically related to COVID-19 and RCTs. The data were analyzed using various bibliometric indicators. The volume of publications, contributions of countries and institutions, funding agencies, active journals, citation analysis, co-occurrence analysis, and future research direction analysis were specifically analyzed. A total of 223,480 research articles concerning COVID-19 were published, with 3,727 of them related to RCTs and COVID-19. The ten most productive countries collectively produced 75.8% of the documents, with the United States leading the way by contributing 31.77%, followed by the UK with 14.03% (n = 523), China with 12.96% (n = 483) and Canada with 7.16% (n = 267). Trials (n = 173, 4.64%), BMJ Open (n = 81, 2.17%), PLOS One (n = 73, 1.96%) and JAMA Network Open (n = 53, 1.42%) were the most active journals in publishing articles related to COVID-19 RCTs. The co-occurrence analysis identified four clusters of research areas: the safety and effectiveness of COVID-19 vaccines, mental health strategies to cope with the impact of the pandemic, the use of monoclonal antibodies to treat patients with COVID-19, and systematic reviews and meta-analyses of COVID-19 research. This paper offers a detailed examination of the global research environment pertaining to RCTs and their use in the context of the COVID-19 pandemic. The comprehensive body of research findings was found to have been generated by the collaborative efforts of multiple countries, institutions, and funding organizations. The predominant research areas encompassed COVID-19 vaccines, strategies for mental health, monoclonal antibodies, and systematic reviews. This information has the potential to aid researchers, policymakers, and funders in discerning areas of weakness and establishing areas of priority.

Towards precise PICO extraction from abstracts of randomized controlled trials using a section-specific learning approach

MOTIVATION

Automated extraction of participants, intervention, comparison/control, and outcome (PICO) from the randomized controlled trial (RCT) abstracts is important for evidence synthesis. Previous studies have demonstrated the feasibility of applying natural language processing (NLP) for PICO extraction. However, the performance is not optimal due to the complexity of PICO information in RCT abstracts and the challenges involved in their annotation.

RESULTS

We propose a two-step NLP pipeline to extract PICO elements from RCT abstracts: (i) sentence classification using a prompt-based learning model and (ii) PICO extraction using a named entity recognition (NER) model. First, the sentences in abstracts were categorized into four sections namely background, methods, results, and conclusions. Next, the NER model was applied to extract the PICO elements from the sentences within the title and methods sections that include >96% of PICO information. We evaluated our proposed NLP pipeline on three datasets, the EBM-NLPmoddataset, a randomly selected and reannotated dataset of 500 RCT abstracts from the EBM-NLP corpus, a dataset of 150 COVID-19 RCT abstracts, and a dataset of 150 Alzheimer's disease (AD) RCT abstracts. The end-to-end evaluation reveals that our proposed approach achieved an overall micro F1 score of 0.833 on the EBM-NLPmod dataset, 0.928 on the COVID-19 dataset, and 0.899 on the AD dataset when measured at the token-level and an overall micro F1 score of 0.712 on EBM-NLPmod dataset, 0.850 on the COVID-19 dataset, and 0.805 on the AD dataset when measured at the entity-level.

AVAILABILITY

Our codes and datasets are publicly available at https://github.com/BIDS-Xu-Lab/section_specific_annotation_of_PICO.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Robustness of Significant Dichotomous Outcomes in Randomized Controlled Trials in the Treatment of Patients with COVID-19: A Systematic Analysis

Purpose

Significant results of randomized controlled trials (RCTs) should be properly weighed. This study adopted fragility index (FI) to evaluate the robustness of significant dichotomous outcomes from RCTs on coronavirus disease 2019 (COVID-19) treatment.

Materials and methods

ClinicalTrials.gov and PubMed were searched from inception to July 31, 2021. FIs were calculated and their distribution was depicted. FI's categorical influential factors were analyzed. Spearman correlation coefficient (r _s) was reported for the relationship between FI and the continuous characteristics of RCTs.

Results

Fifty RCTs with 120 outcomes in 7869 patients were included. The FI distribution was abnormal with median 3 (interquartile range 1-7, P = 0.0001). The FIs and robustness were affected by the outcomes of interest, various patient populations, and interventions (T = 18.215,16.667, 23.107; P = 0.02,0.0001, 0.001, respectively). A cubic relationship between the FIs and absolute difference of events between groups with R square of 0.848 (T = 215.828, P = 0.0001, R square = 0.865) was observed. A strong negative logarithmic relationship existed between FI and the P value with R square = - 0.834.

Conclusion

The robustness of significant dichotomous outcomes of COVID-19 treatments was fragile and affected by the outcomes of interest, patients, interventions, P value, and absolute difference of events between the groups. FI was an useful quantitative metric for the binary significant outcomes on COVID-19 treatments.

Registration

PROSPERO (CRD42021272455).

Supplementary Information

The online version contains supplementary material available at 10.1007/s44231-022-00027-y.

Research methodology in acupuncture and moxibustion for managing primary dysmenorrhea: A scoping review

BACKGROUND

Acupuncture and moxibustion have promising effects in managing primary dysmenorrhea. However, some evidence from clinical trials remains controversial due to methodological flaws in study designs that involve acupuncture and its related modalities and require urgent attention and dialogue.

METHODS

Allied and Complementary Medicine Database (AMED), Cochrane Library, Excerpta Medica database (EMBASE), PubMed, Web of Sciences, Chinese Biological Medicine (CBM), China National Knowledge Infrastructure (CNKI), VIP Database for Chinese Technical Periodicals (VIP), and Wanfang database were searched from their inception to July 2021. Data were extracted based on the types of study design, primary outcome measures, adverse events (AEs), and participants' subjective views.

RESULTS

Most studies (n = 282, 93 %) were published in Chinese and 21 (7 %) in English. Among these, there were 209 (69 %) randomized controlled trials (RCTs), 39 (13 %) non-randomized controlled trials (nRCTs), 30 (10 %) case-series reports, 15 (5 %) cohort studies, and 10 (3 %) case reports. The most frequent reported outcome was pain, followed by emotion, sleeping quality, quality of life, skin temperature, changes in brain function, uterine and ovarian blood flow, and reproductive endocrine level. AEs were reported in 37 studies with mild events, and all recovered without actions taken; 31 trials reported no AEs; 235 failed to report any AEs. One RCT found that the satisfaction rate of the intervention group was statistically significantly higher than the control group.

CONCLUSION

Clinical studies on acupuncture and its related modalities face methodological challenges and require urgent attention. RCT with blinding and sham control might be the gold standard trial design. However, it may not be the most suitable research method for these modalities. We recommend using pragmatic RCTs in this field, where trial protocol registration on the trial registry platforms and detailed safety reporting should be mandatory.

Ethical challenges of prospective clinical trials during the COVID-19 pandemic

INTRODUCTION

The COVID-19 pandemic has created an unprecedented opportunity to reimagine clinical research. While much has been written about the challenges associated with generating real-world evidence during the COVID-19 pandemic, comparatively little attention has been paid to the ethical challenges facing patients, clinicians, researchers, and regulatory bodies.

AREAS COVERED

In this manuscript, we examine these challenges through the lens of informed consent and explore how the consenting process changes as our understanding of the disease is altered.

EXPERT OPINION

We also suggest ways to limit these ethical hurdles through the use of embedded pragmatic clinical trials, which generate real-world data without the limitations associated with observational trials or the resources and lack of generalizability that are obstacles to conducting conventional randomized clinical trials. We argue that clinical research must become more nimble, and must include embedded researchers to ensure that relevant questions and ethical issues are properly addressed.

The Association Between Proton Pump Inhibitors and COVID-19 is Confounded by Hyperglycemia in a Population-Based Study

Background and Aims: There is conflicting evidence regarding the association between proton pump inhibitors (PPI) and the risk of acquisition and severity of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

Aim: To evaluate the association between PPI exposure and infection and development of severe disease in patients infected with SARS-CoV2in a large population-based historical cohort.

Methods: Data were extracted from a health maintenance organization database in Israel that insures over 1,200,000 individuals from across the country. All patients who underwent SARS-CoV-2 testing between March and November 2020 were included. Logistic regression and matched analyses were used to compare patients prescribed and exposed to PPIs to those not prescribed PPIs regarding SARS-CoV-2 positivity. In addition, among SARS-CoV-2 positive patients (n = 44,397) the likelihood of developing severe disease, defined by a composite endpoint of death, ICU admission and prolonged hospitalization, was compared in those exposed and not exposed to PPIs.

Results: Among 255,355 adult patients who underwent SARS-CoV-2 testing by PCR, 44,397 (17.4%) were positive for SARS-CoV-2 and 12,066 (4.7%) patients were prescribed PPIs in the 3 months before testing. In a multivariable logistic regression model controlling for age, gender, smoking status, BMI, diabetes mellitus, hypertension, COPD, history of ischemic heart disease and fasting blood glucose (FBG) levels, no significant association was found between PPIs and SARS-CoV-2 positivity (p = 0.09 aOR 0.94, 95% CI – 0.88–1.01). Among SARS-CoV-2 positive patients, 910 (2%) had a severe infection. Multivariate logistic regression controlling for the abovementioned confounders, showed no such association between PPIs and severe COVID-19 (p = 0.28). Elevated FBG levels were significantly associated with both PPI exposure (p < 0.001) and severe COVID-19 infection (p < 0.001). These results were reinforced by a matched analysis (n = 655 pairs).

Conclusion: PPIs are spuriously associated with severe COVID-19 due to the presence of elevated FBG as a confounder. Our study accounted for the FBG levels of patients and known risk factors for severe COVID-19 infection, which may be the reason for the discrepancy in prior studies. These results may aid in understanding potential confounders when evaluating potential associations of PPIs with other respiratory or viral diseases.

Antiviral activity of molnupiravir against COVID-19: a schematic review of evidences

BACKGROUND

The study was aimed at encapsulating the evidence of in vitro and in vivo antiviral activities of molnupiravir and its active form against highly pathogenic SARS-CoV-2, the pathogen responsible for COVID-19, and finding out the efficacy and safety of molnupiravir in clinical trials.

MAIN BODY

Information on publications was explored on several databases, gray literature was reviewed, and the outcomes were discussed narratively. Molnupiravir's antiviral efficacy and associated mechanism of action have been verified in vitro against both non-COVID and multiple coronaviruses. Molnupiravir has been tried in preclinical investigations in numerous animal models against non-coronaviruses. Clinical studies in several countries are now being conducted to evaluate its antiviral efficacy in persons infected with COVID-19. The medication displays antiviral effect via generation of copying mistakes during viral RNA replication.

CONCLUSIONS

Molnupiravir is the first oral antiviral medicine to show considerable and convincing antiviral activity in vitro and in animal models. Molnupiravir stops the spread of SARS-CoV-2 in animals that have been infected and in cells grown in a lab. In a clinical research, early molnupiravir treatment reduced hospitalization and death risk in unvaccinated individuals with COVID-19. In the battle against SARS-CoV-2, it could be a potent weapon. However, its role in COVID-19 in moderate to severe cases is still up in the air, and more research is needed.

Efficacy and safety of current treatment interventions for patients with severe COVID-19 infection: A network meta-analysis of randomized controlled trials

This study aimed to assess the efficacy and safety of different medications available at present for severe coronavirus disease 2019 (COVID‐19) infection. We searched databases for randomized controlled trials (RCTs) published up to April 30, 2021, with Chinese or English language restriction, of medications recommended for patients (aged 18 years or older) with severe COVID‐19 infection. We extracted data on trials and patient characteristics, and the following primary outcomes: all‐cause mortality (ACM), and treatment‐emergent adverse events (TEAEs). We identified 1855 abstracts and of these included 15 RCTs comprising 3073 participants through database searches and other sources. In terms of efficacy, compared with the standard of care (SOC) group, no significant decrease in ACM was found in α‐lipoic acid, convalescent plasma (CP), azithromycin, tocilizumab, methylprednisolone, interferon beta, CP/SOC, high dosage sarilumab, low dosage sarilumab, remdesivir, lopinavir–ritonavir, auxora, and placebo group. Compared with placebo, we found that a significant decrease in ACM was only found in methylprednisolone (odds ratio [OR]: 0.16, 95% confidence interval [CI]: 0.03–0.75]. With respect to TEAEs, the CP group showed lower TEAEs than placebo (OR: 0.07, 95% CI: 0.01–0.58) or SOC (OR: 0.05, 95% CI: 0.01–0.42) group for the therapy of severe COVID‐19 patients. This study only demonstrated that methylprednisolone was superior to placebo in treating patients with severe COVID‐19 infection. Meanwhile, this further confirmed that the safety of other treatment interventions might be inferior to CP for the therapy of severe COVID‐19 patients.

We considered addressing direct and indirect comparisons of medications from the angle of severe COVID‐19 infection based on random controlled trials (RCTs)

We explored the difference of efficacy and safety of for the pharmaceutical interventions of severe COVID‐19 patients from different control conditions (i.e., placebo and SOC).

To date, the findings from this network meta‐analysis may represent much more comprehensive analysis for the medications of severe COVID‐19 infection.

Applications of laboratory findings in the prevention, diagnosis, treatment, and monitoring of COVID-19

The worldwide pandemic of coronavirus disease 2019 (COVID-19) presents us with a serious public health crisis. To combat the virus and slow its spread, wider testing is essential. There is a need for more sensitive, specific, and convenient detection methods of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Advanced detection can greatly improve the ability and accuracy of the clinical diagnosis of COVID-19, which is conducive to the early suitable treatment and supports precise prophylaxis. In this article, we combine and present the latest laboratory diagnostic technologies and methods for SARS-CoV-2 to identify the technical characteristics, considerations, biosafety requirements, common problems with testing and interpretation of results, and coping strategies of commonly used testing methods. We highlight the gaps in current diagnostic capacity and propose potential solutions to provide cutting-edge technical support to achieve a more precise diagnosis, treatment, and prevention of COVID-19 and to overcome the difficulties with the normalization of epidemic prevention and control.

Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features

Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important tools for evaluating of lung lesions. The aim of this study was to use a deep learning approach for predicting the outcome of patients with COVID-19 into two groups of critical and non-critical according to their CT features. Methods This was carried out as a retrospective study from March to April 2020 in Baqiyatallah Hospital, Tehran, Iran. From total of 1078 patients with COVID-19 pneumonia who underwent chest CT, 169 were critical cases and 909 were non-critical. Deep learning neural networks were used to classify samples into critical or non-critical ones according to the chest CT results. Results The best accuracy of prediction was seen by the presence of diffuse opacities and lesion distribution (both=0.91, 95% CI: 0.83-0.99). The largest sensitivity was achieved using lesion distribution (0.74, 95% CI: 0.55-0.93), and the largest specificity was for presence of diffuse opacities (0.95, 95% CI: 0.9-1). The total model showed an accuracy of 0.89 (95% CI: 0.79-0.99), and the corresponding sensitivity and specificity were 0.71 (95% CI: 0.51-0.91) and 0.93 (95% CI: 0.87-0.96), respectively. Conclusions The results showed that CT scan can accurately classify and predict critical and non-critical COVID-19 cases.

Disentangling the Association of Hydroxychloroquine Treatment with Mortality in Covid-19 Hospitalized Patients through Hierarchical Clustering

The efficacy of hydroxychloroquine (HCQ) in treating SARS-CoV-2 infection is harshly debated, with observational and experimental studies reporting contrasting results. To clarify the role of HCQ in Covid-19 patients, we carried out a retrospective observational study of 4,396 unselected patients hospitalized for Covid-19 in Italy (February–May 2020). Patients' characteristics were collected at entry, including age, sex, obesity, smoking status, blood parameters, history of diabetes, cancer, cardiovascular and chronic pulmonary diseases, and medications in use. These were used to identify subtypes of patients with similar characteristics through hierarchical clustering based on Gower distance. Using multivariable Cox regressions, these clusters were then tested for association with mortality and modification of effect by treatment with HCQ. We identified two clusters, one of 3,913 younger patients with lower circulating inflammation levels and better renal function, and one of 483 generally older and more comorbid subjects, more prevalently men and smokers. The latter group was at increased death risk adjusted by HCQ (HR[CI95%] = 3.80[3.08-4.67]), while HCQ showed an independent inverse association (0.51[0.43-0.61]), as well as a significant influence of cluster∗HCQ interaction (p < 0.001). This was driven by a differential association of HCQ with mortality between the high (0.89[0.65-1.22]) and the low risk cluster (0.46[0.39-0.54]). These effects survived adjustments for additional medications in use and were concordant with associations with disease severity and outcome. These findings suggest a particularly beneficial effect of HCQ within low risk Covid-19 patients and may contribute to clarifying the current controversy on HCQ efficacy in Covid-19 treatment.

Recent breakthroughs of antibacterial and antiviral protective polymeric materials during COVID-19 pandemic and after pandemic: Coating, packaging, and textile applications

The global epidemic owing to COVID-19 has generated awareness to ensuring best practices for avoiding the microorganism spread. Indeed, because of the increase in infections caused by bacteria and viruses such as SARS-CoV-2, the global demand for antimicrobial materials is growing. New technologies by using polymeric systems are of great interest. Virus transmission by contaminated surfaces leads to the spread of infectious diseases, so antimicrobial coatings are significant in this regard. Moreover, antimicrobial food packaging is beneficial to prevent the spread of microorganisms during food processing and transportation. Furthermore, antimicrobial textiles show an effective role. We aim to provide a review of prepared antimicrobial polymeric materials for use in coating, food packaging, and textile during the COVID-19 pandemic and after pandemic.

Comparison of the clinical performance and usefulness of five SARS-CoV-2 antibody tests

We examined the usefulness of five COVID-19 antibody detection tests using 114 serum samples at various time points from 34 Japanese COVID-19 patients. We examined Elecsys Anti-SARS-CoV-2 from Roche, and four immunochromatography tests from Hangzhou Laihe Biotech, Artron Laboratories, Chil, and Nadal. In the first week after onset, Elecsys had 40% positivity in Group S (severe cases) but was negative in Group M (mild-moderate cases). The immunochromatography kits showed 40–60% and 0–8% positivity in Groups S and M, respectively. In the second week, Elecsys showed 75% and 50% positivity, and the immunochromatography tests showed 5–80% and 50–75% positivity in Groups S and M, respectively. After the third week, Elecsys showed 100% positivity in both groups. The immunochromatography kits showed 100% positivity in Group S. In Group M, positivity decreased to 50% for Chil and 75–89% for Artron and Lyher. Elecsys and immunochromatography kits had 91–100% specificity. Elecsys had comparable chronological change of cut-off index values in the two groups from the second week to the sixth week. The current SARS-CoV-2 antibody detection tests do not provide meaningful interpretation of severity and infection status. Its use might be limited to short-term epidemiological studies.

Pre-Exposure Prophylaxis for COVID-19 in Pregnant Women

Pregnant women are at higher risk for developing severe complications of COVID-19 including preterm delivery, respiratory failure, and death. Although vaccines to prevent COVID-19 are being developed, pregnant women are not included in the current COVID-19 vaccine trials and initially this population may not be eligible for COVID-19 vaccines due to lack of safety testing in pregnancy. As an alternate approach, we discuss the concept of pre-exposure prophylaxis (PrEP) using medications that are approved for use in pregnant women to prevent gestational problems and severe illness in this high-risk population. In particular, the use of hydroxychloroquine PrEP affords a safe and readily available means to avoid COVID-19 complications in pregnancy.