COVID-19 Trials Research Articles

Impact of Consensus Guidelines, Clinical Trials, and COVID-19 on Fractionation Practices for Node-negative Intact Breast Cancer.

To evaluate whether hypofractionated radiotherapy (HF-RT) in node-negative intact breast cancer significantly increased after guideline updates, trial publications, and COVID-19. Patients with node-negative breast cancer undergoing lumpectomy and adjuvant RT were identified in the National Cancer Database. Receiving ≥25 and <50 Gy in 5-20 fractions defined HF-RT. Receiving 50 to 66 Gy in >20 fractions defined conventional RT (CF-RT). Patient characteristics were compared with X2 testing. Joinpoint analysis identified when fractionation significantly changed. Variables associated with HF-RT were identified by univariate and multivariate (MVA) logistic regression. Two-sided P-value <0.05 was significant. Patients meeting criteria totaled 236,336; 54.8% received CF-RT and 45.2% HF-RT. HF-RT and 5-fraction RT significantly increased after 2015 and 2019, respectively (P<0.05). On MVA, HF-RT was positively associated with: age older than or equal to 65 years (OR 2.14, P<0.001); private insurance (OR 1.27, P=0.03); treatment in Midwest (OR 1.66, P<0.001) or Western United States (US) (OR 3.77, P<0.001); distance ≥50 miles (OR 1.16, P=0.001); later year of diagnosis (OR 1.44, P<0.001); and partial breast irradiation (OR 2.08, P<0.001). HF-RT was negatively associated with: community (OR 0.49, P<0.001) or integrated network (0.55, P<0.001) centers; grade 2 (OR 0.83, P<0.001) or 3 (OR 0.49, P<0.001), hormone receptor negative (OR 0.66, P<0.001), and HER2+ (OR 0.74, P<0.001) disease; positive surgical margins (OR 0.61, P<0.001); and presence of lympho-vascular invasion (OR 0.86, P<0.001). HF-RT in node-negative intact breast cancer increased after 2015, coinciding with US and European guideline updates. Five-fraction RT increased after 2019, coinciding with COVID-19 and FAST-Forward trial results.

Demographic disparities in access to COVID-19 clinical trial sites across the United States: a geospatial analysis

Throughout the COVID-19 pandemic, underserved populations, such as racial and ethnic minority communities, were disproportionately impacted by illness and death. Ensuring people from diverse backgrounds have the ability to participate in clinical trials is key to advancing health equity. We sought to analyze the spatial variability in locations of COVID-19 trials sites and to test associations with demographic correlates. All available and searchable COVID-19 studies listed on ClinicalTrials.gov until 04/04/2022 and conducted in the United States were extracted at the trial-level, and locations were geocoded using the Microsoft Bing API. Publicly available demographic data were available at the county level for national analysis and the census tract level for local analysis. Independent variables included eight racial and ethnic covariates, both sexes, and twelve age categories, all of which were population-normalized. The county-level, population-normalized count of study site locations, by type, was used as the outcome for national analysis, thereby enabling the determination of demographic associations with geospatial availability to enroll as a participant in a COVID-19 study. Z-scores of the Getis-Ord Gi statistic were used as the outcome for local analysis in order to account for areas close to those with clinical study sites. For both national (p < 0.001) and local analysis (p = 0.006 for Los Angeles, p = 0.030 for New York), areas with greater proportions of men had significantly fewer studies. Sites were more likely to be found in counties with higher proportions of Asian (p < 0.001) and American Indian or Alaska Native residents (p < 0.001). Areas with greater concentrations of Black or African American residents had significantly lower concentrations of observational (p < 0.001) and government-sponsored COVID-19 studies (p = 0.003) in national analysis and significantly fewer concentrations of study sites in both Los Angeles (p < 0.001) and New York (p = 0.007). Though there appear to be a large number of COVID-19 studies that commenced in the US, they are distributed unevenly, both nationally and locally.

Features and results availability of non-commercial Spanish COVID-19 trials: a systematic review of clinical trial registers and corresponding literature.

This study aimed to characterize non-commercial Spanish COVID-19 trials and to determine the availability of results. Differences in outcomes according to the interventions assessed (medicines, non-medicines) will also be determined. This systematic review was conducted in March 2024 by searching non-commercial Spanish COVID-19 trials on four registers (EUCTR, Clinical. gov, ISRCTN, DRKS) and the WHO ICTRP. Phase-1 medicines trials were excluded. Several variables were retrieved from registers. Publication of main trial results were searched on PubMed, Cochrane COVID-19 Study Register, and Google Scholar. Journals' impact factor and articles' citations on Google Scholar were also registered. Results from medicines and non-medicines trials extracted from registers and articles were compared. A total of 170 trials (57.1% medicines trials) were identified. These 170 trials were randomized (87.1%), masked (41.8%), or multicenter (39.4%); a total of 15,555 participants were enrolled, mostly in small trials (median, n = 88). Only 8.8% (15/170) of trials posted results on the registers; only 47.6% (81/170) of trials had either published results or posted them on registers. Publications accounted for 92.6% (75/81) of these. Articles were published in 56 different journals, had a median impact factor of 4.4 and a median of 10 citations. Most (58.7%, 44/75) described negative results. There were statistically significant differences (p < 0.001) between medicines and non-medicines trials on timely registration and on being multicenter. This was also the case among published trials with respect to negative results of the primary endpoint. Although most trials were randomized, a minority were multicenter, large, or masked. Trial results should be posted on the registers to make them accessible to everyone.

In-vivo implementation of the HPTLC methodology to rat plasma for the concurrent determination of a novel combination therapy for the management of COVID-19 (favipiravir and nitazoxanide).

The 2019 coronavirus outbreak has prompted scientists to investigate pharmaceuticals to prevent the spread of the disease. Favipiravir (FAV) has received Food and Drug Administration FDA approval for the treatment of various viral infections with notable efficacy in clinical trials for COVID-19. Nitazoxanide (NTZ) is a broad-spectrum antiparasitic and antiviral agent used for the treatment of parasitic illnesses. Recently, the antiviral medications FAV and NTZ have been utilized therapeutically as early antiviral combination therapy for COVID-19, highlighting their safety, efficacy, and immunomodulatory effects. Despite several clinical studies on both FAV and NTZ, no analytical method has been developed for their concurrent detection. The objective of this study is to develop a TLC-densitometric method for their assessment and application to rat plasma. FAV, NTZ, and tizoxanide (the active metabolite of nitazoxanide (TZM)) were simultaneously determined using an HPTLC method embracing sulfasalazine as an internal standard (IS). Silica gel 60 F254 used as the stationary phase for chromatographic separation, the mobile phase consisted of chloroform-methanol-formic acid (9.5:0.5:0.2, v/v/v), with UV detection at 230 nm demonstrating linearity within the range of 0.5-5 μg/band. The proposed methodology has been shown to effectively measure the analyzed elements in both pure form and in-vivo rat plasma.

Phosphatidylethanol measures in patients with severe COVID-19-associated respiratory failure identify a subset with alcohol misuse.

Clinical trials in patients with COVID-19 have exclusively used self- or proxy-reporting to characterize alcohol consumption. The aim of this study was to measure an objective biomarker of recent alcohol use in patients hospitalized with severe COVID-19-associated respiratory failure who were enrolled in an investigational clinical trial to determine the prevalence of alcohol misuse, and to explore the relationship of alcohol use with outcomes. We conducted a substudy of patients enrolled in the multicenter, phase 2, adaptive platform design, Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging And molecular Analysis in COVID-19 trial (ClinicalTrials.gov: NCT04488081), conducted at 20 hospital systems across the United States. Three hundred and fifty-five patients with available red blood cell (RBC) samples and 60-day follow-up assessments were included. RBCs were utilized to measure phosphatidylethanol (PEth). Prespecified thresholds of PEth were utilized to stratify patients into groups: low/no alcohol use (PEth < 20 ng/mL), significant alcohol use (PEth 20-200 ng/mL), and heavy alcohol use (PEth ≥ 200 ng/mL). In this cohort, 17% of patients met criteria for significant alcohol use, while 4% met criteria for heavy alcohol use. Alcohol misuse was associated with diminished odds for home discharge, though this finding did not achieve statistical significance. In a cohort of patients with severe COVID-19 enrolled in a clinical trial, alcohol consumption of two or more standard drinks per day was present among 21%, approximating the proportion of patients with diabetes, and raising the possibility that alcohol consumption alters risk for severe viral pneumonia. Undetected alcohol misuse among clinical trial participants has the potential to influence study outcomes or contribute to adverse events.

Longitudinal Benefit:risk Analysis through the Desirability of Outcome Ranking (DOOR) with Application to ACTT-1 Trial

A clinical trial aims to uncover high-quality evidence for both efficacy and safety for an experimental treatment. Traditionally, statisticians evaluate the two aspects marginally, where, for example, efficacy considers the proportion of patients cured and safety considers the proportion of patients not showing adverse events. However, separate analyses could end up with misleading results, as the cumulative nature of clinical outcomes and the correlation between efficacy and safety endpoints are neglected. The desirability of outcome ranking (DOOR) method addresses such issues and provides a patient-centric approach to benefit:risk evaluation. A patient’s outcome is ranked based on pre-specified clinical criteria, where the most desirable rank represents a good outcome with no side effects and the least desirable rank is the worst possible clinical outcome. As the DOOR outcome is a temporal state that can have repeated measures, we propose a longitudinal approach that estimates and infers the temporal treatment effects. We develop a methodology for constructing simultaneous confidence bands by accounting for the correlations across time points. Additionally, we propose a weighted Mann-Whitney-U statistic to evaluate the treatment effect over the entire trial period. The performance of the proposed methodologies is examined through simulations and an application to a COVID-19 trial.

Completion and reporting of COVID-19 clinical trials registered on ClinicalTrials.gov during the first 6 months of the pandemic: cohort study

BackgroundEarly in the COVID-19 pandemic, numerous clinical trials were initiated. Although concerns were raised regarding the quality of the trials, the eventual research output yielded from the trials remains unknown....

Challenges and prospects of clinical trials in Nigeria - Lessons from the WHO COVID-19 solidarity plus trial

Conducting randomized clinical trials (RCTs) during a pandemic is essential for obtaining timely evidence on safe and effective treatments, but it presents numerous obstacles. During the COVID-19 pandemic, the World Health Organization (WHO) sponsored multinational RCTs investigating repurposed drugs among hospitalized COVID-19 patients across countries with varying clinical research capacities. In Nigeria, several challenges hindered our progress, including inadequate infrastructure, initial insufficient investigator certification and expertise, and delays in securing regulatory approvals due to bureaucratic hurdles. Despite these challenges, the WHO-sponsored Solidarity Plus Trial (SPT) offered valuable opportunities to enhance research capacity, streamline participant enrolment through electronic randomization, and bolster infection prevention and control measures for healthcare workers. Moreover, the trial enabled us to upgrade infrastructure at multiple sites, facilitating improved case detection through more testing and data collection. A crucial lesson learned was the importance of expediting trial initiation to capitalize on the limited window for data collection during an outbreak. To optimize RCTs during pandemics, we advocate for enhanced community engagement, collaborative efforts across sectors, strengthened research capacity, flexible regulatory frameworks, and the establishment of adaptive clinical trial units. By addressing these challenges and leveraging opportunities, we can significantly enhance the efficiency and impact of RCTs during public health emergencies.

Evaluating the Risk-Benefit Profile of Corticosteroid Therapy for COVID-19 Patients: A Scoping Review.

The 2019 coronavirus (COVID-19) outbreak was declared a global pandemic in March 2020. It quickly spread across all continents, causing significant social, environmental, health, and economic impacts. During the pandemic, there has been consideration of repurposing and repositioning of medications, such as corticosteroids, for the treatment of hospitalised COVID-19 patients. To assess and summarise corticosteroid regimens used for hospitalised COVID-19 patients, focusing on dosage, route of administration, and clinical outcome from clinical trials. PubMed and Embase databases and the grey literature were searched to identify randomised controlled trials (RCTs) that evaluated the efficacy of corticosteroids in hospitalised patients with COVID-19 between January 2020 and January 2023. This scoping review was conducted in line with the PRISMA extension for scoping reviews (PRISMA-ScR) checklist. A total of 24 RCTs were eligible for inclusion. There was variation in the steroid regimens used for treatment across COVID-19 trials. Despite the heterogeneity of included RCTs, the overall results have shown the benefits of improving lung function and a lower all-cause mortality rate in hospitalised COVID-19 patients treated with systematic corticosteroids. Corticosteroids have proven to be an effective treatment for COVID-19 patients in critical condition. However, comparative effectiveness studies should be conducted to assess the efficacy and safety of optimal corticosteroid treatment at the population level. Moreover, the global burden of long COVID is significant, affecting millions with persistent symptoms and long-term health complications. Thus, it is also necessary to evaluate the optimal steroid regimen for long COVID treatment.

Group sequential designs for clinical trials when the maximum sample size is uncertain.

Motivated by the experience of COVID-19 trials, we consider clinical trials in the setting of an emerging disease in which the uncertainty of natural disease course and potential treatment effects makes advance specification of a sample size challenging. One approach to such a challenge is to use a group sequential design to allow the trial to stop on the basis of interim analysis results as soon as a conclusion regarding the effectiveness of the treatment under investigation can be reached. As such a trial may be halted before a formal stopping boundary is reached, we consider the final analysis under such a scenario, proposing alternative methods for when the decision to halt the trial is made with or without knowledge of interim analysis results. We address the problems of ensuring that the type I error rate neither exceeds nor falls unnecessarily far below the nominal level. We also propose methods in which there is no maximum sample size, the trial continuing either until the stopping boundary is reached or it is decided to halt the trial.

Convalescent Plasma and Other Antibody Therapies for Infectious Diseases-Lessons Learned from COVID-19 and Future Prospects.

Antiviral passive antibody therapy includes convalescent plasma, hyperimmune globulin, and monoclonal antibodies. Passive antibodies have proven effective in reducing morbidity and mortality for SARS-CoV-2 and other infectious diseases when given early in the disease course with sufficiently high specific total and neutralizing antibody levels. Convalescent plasma can be delivered to patients before vaccination implementation or novel drug production. Carefully designed and executed randomized controlled trials near the pandemic outset are important for regulatory bodies, healthcare workers, guideline committees, the public, and the government. Unfortunately, many otherwise well-designed antibody-based clinical trials in COVID-19 were futile, either because they intervened too late in the disease or provided plasma with insufficient antibodies. The need for early treatment mandates outpatient clinical trials in parallel with inpatient trials. Early outpatient COVID-19 convalescent plasma transfusion with high antibody content within 9days of symptom onset has proven effective in blunting disease progression and reducing hospitalization, thus reducing hospital overcrowding in a pandemic. Convalescent plasma offers the opportunity for hope by enabling community participation in outpatient curative therapy while monoclonal therapies, vaccines, and drugs are being developed. Maintaining the appropriate infrastructure for antibody infusion in both outpatient and inpatient facilities is critical for future pandemic readiness.

Pharmacological inhibition of CK2 by silmitasertib mitigates sepsis-induced circulatory collapse, thus improving septic outcomes in mice

Casein kinase II (CK2) has recently emerged as a pivotal mediator in the propagation of inflammation across various diseases. Nevertheless, its role in the pathogenesis of sepsis remains unexplored. Here, we investigated the involvement of CK2 in sepsis progression and the potential beneficial effects of silmitasertib, a selective and potent CK2α inhibitor, currently under clinical trials for COVID-19 and cancer. Sepsis was induced by caecal ligation and puncture (CLP) in four-month-old C57BL/6OlaHsd mice. One hour after the CLP/Sham procedure, animals were assigned to receive silmitasertib (50 mg/kg/i.v.) or vehicle. Plasma/organs were collected at 24 h for analysis. A second set of experiments was performed for survival rate over 120 h. Septic mice developed multiorgan failure, including renal dysfunction due to hypoperfusion (reduced renal blood flow) and increased plasma levels of creatinine. Renal derangements were associated with local overactivation of CK2, and downstream activation of the NF-ĸB-iNOS-NO axis, paralleled by a systemic cytokine storm. Interestingly, all markers of injury/inflammation were mitigated following silmitasertib administration. Additionally, when compared to sham-operated mice, sepsis led to vascular hyporesponsiveness due to an aberrant systemic and local release of NO. Silmitasertib restored sepsis-induced vascular abnormalities. Overall, these pharmacological effects of silmitasertib significantly reduced sepsis mortality. Our findings reveal, for the first time, the potential benefits of a selective and potent CK2 inhibitor to counteract sepsis-induced hyperinflammatory storm, vasoplegia, and ultimately prolonging the survival of septic mice, thus suggesting a pivotal role of CK2 in sepsis and silmitasertib as a novel powerful pharmacological tool for drug repurposing in sepsis.

Effectiveness of seven oral traditional Chinese medicines against mild or moderate COVID-19: An updated systematic review and network meta-analysis

BackgroundSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for the outbreak of COVID-19 in Wuhan, China. As a highly infectious epidemic, SARS-CoV-2 rapidly evolves. Presently, COVID-19 coexists with humans, mainly with mild or moderate disease. The latest Guidelines for the Diagnosis and Treatment of COVID-19 (trial version of the 10th Edition) recommend several oral traditional Chinese medicines (TCMs) for treatment. This study aims to evaluate the evidence-based benefits of these TCMs as adjunctive therapies to conventional western medicine (CWM) for patients with mild or moderate COVID-19. MethodsWe conducted a systematic review and meta-analysis adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, utilizing the PRISMA checklist. We searched PubMed, Cochrane Library, Embase, CNKI, and Wan-Fang databases to retrieve randomized controlled trials and retrospective cohort studies of TCM in combination with CWM on the treatment of mild or moderate COVID-19 that were published as of December 25, 2023. A network meta-analysis using the frequency model was employed to evaluate the benefits of different interventions. ResultsA total of 30 eligible studies, enrolling 4144 participants, utilized 7 marketed oral TCMs in China. Compared with CWM alone, the integration of TCMs with CWM can significantly reduce severe conversion rate. This combined approach also enhances the clinical effective rate, shortens the negative conversion time of nucleic acid, and improves both symptoms and blood biochemical markers in patients. The network meta-analysis provided preliminary evidence of the superiority of specific TCMs for various outcomes: Qingfei Paidu for raising the CT improvement rate and clinical effective rate, and shortening the negative conversion time of nucleic acid; Huashi Baidu for reducing severe conversion and improving cough; Xuanfei Baidu for improving fatigue; Jinhua Qinggan for improving fever; Lianhua Qingwen for shortening the recovery time of fatigue and cough; and Shufeng Jiedu for shortening the recovery time of fever. ConclusionsTCM in combination with CWM may be beneficial for patients with mild or moderate COVID-19. Each TCM may have distinct benefits in COVID-19.

Effectiveness of Pelvic Floor Strengthening Exercises in Females with Stress Urinary Incontinence – A Systematic Review

Abstract Background: Urinary incontinence (UI) is an unpleasant and socially constrained disorder that affects one in three women. Stress UI (SUI) is the most prevalent type of UI and is identified in 50% of affected women. The main objective of this systematic review was to evaluate the updated literature exploring the effectiveness of pelvic floor strengthening exercises and their dosimetry in women with SUI. Methods: Randomized controlled trials published between January 2013 and February 2023 and in English were included in this review. Case reports, systematic reviews, meta-analyses, and studies published in languages other than English were excluded from the study. Databases such as PubMed, Cochrane Library, and Physiotherapy Evidence Database (PEDro) were used to locate the literature. The quality of the data included was evaluated using PEDro scoring, and the risk of bias in the included studies was evaluated using RoB 2, a modified Cochrane risk-of-bias tool. Results: After screening, 12 studies were selected and included for qualitative analysis for the review. The findings of this review showed that pelvic floor muscle training (PFMT) exercises are an effective intervention for treating symptoms of SUI and improving quality of life whether used in combination or isolation. It is also suggested that a minimum of 12 supervised sessions of PFMT with a frequency of three times a week is suggestive to be an effective intervention and can be seen as a first line of treatment of SUI. It can be concluded that the PFMT is an effective intervention to treat the symptoms of SUI in females. Registration and Protocol: The systematic review applied for registration in PROSPERO but declined the registration because of an excessive inflow of trials that needed to be registered in PROSPERO as it was not accepting trials other than COVID-19 trials.

Publication of observational studies making claims of causation over time

To examine methodology characteristics over time and investigate research impact before and after the start of the COVID-19 era, we analyzed original articles published in The New England Journal of Medicine between October 26, 2017 and August 27, 2022. April 1, 2020 was used as the defining date dividing before and after the COVID-19 era. Out of 1051 original articles, 515 (49 %) were before and 536 (51 %) were after the COVID-19 era. Two independent reviewers categorized and reconciled methodology into groups: “randomized trial” (715 articles), “uncontrolled experimental study” (128), “descriptive observational study” (168), and “observational study making a causal claim” (40). We extracted subsequent citations and Altmetric data for each article to assess impact.The median number of social media shares was 2272 (IQR: 743–7821) for observational studies making a causal conclusion, compared to 306 (IQR: 70–606) for randomized trials (p-value=<0.001). The median Altmetric score for randomized COVID-19 trials (2421, IQR: 1063–3920) was not significantly different than that of COVID-19 observational studies making a causal claim (2583, IQR: 1513–6197, p-value = 0.42), but it was significantly lower than descriptive observational COVID-19 studies (4093, IQR: 2545–6823, p-value = 0.04).We conclude that there has been a steady increase in the number and percentage of observational studies that make causal conclusions about the efficacy of an intervention. Research concerning COVID-19, regardless of methodology, has seen a sharp rise in dissemination as measured through Altmetric's social media score and subsequent citations.

Temporal trends and characteristics associated with racial, ethnic, and sex representation in COVID-19 clinical trials: A systematic review and meta-analysis

BackgroundEarly in the pandemic, extensive attention was cast on limited inclusion of historically underrepresented patient populations in COVID-19 clinical trials. How diverse representation improved following these initial reports remains unclear. MethodsPubMed, Embase and the Cochrane Library were searched (through April 2024) for US-based COVID-19 trials. Utilizing random-effects, we compared expected proportions of trial participants from racial and ethnic groups and of female sex between trials enrolling primarily in 2020 versus primarily 2021–2022. Meta-regression was performed to assess associations between trial characteristics and group representation. ResultsWe retrieved 157 studies comprising 198,012 participants. White (2020: 63.1% [95% CI, 60.8%–67.3%]; 2021–2022: 73.8% [95% CI, 71.5%–76.0%]) and female representation (2020: 46.1% [95% CI, 44.7%–47.4%)]; 2021–2022: 51.1% [95% CI, 49.3%–52.8%) increased across enrollment periods. Industry-sponsored trials were associated with higher White (coefficient, 0.10 [95% CI, 0.03–0.18]) and Hispanic or Latinx representation (coefficient, 0.16 [95% CI, 0.08–0.25]) and lower Asian (coefficient, −0.03 [95% CI, −0.06– –0.003]) and female representation (coefficient, −0.03 [95% CI, −0.07– –0.002]). Outpatient trials were associated with higher White (coefficient, 0.20 [95% CI, 0.13–0.26]) and female representation (coefficient, 0.16 [95% CI, 0.13–0.18]), and lower Black representation (coefficient, −0.10 [95% CI, −0.10– –0.08]). ConclusionsDespite improved female representation in COVID-19 trials over time, there was no clear increase in non-White representation. Trial characteristics such as primary sponsor, clinical setting, and intervention type correlate with representation of specific demographic groups and should be considered in future efforts to improve participant diversity.

A Systematic Analysis of COVID-19 Clinical Trials Registered in the Clinical Trials Registry of India.

The Clinical Trials Registry - India (CTRI) database is a registry of various trials conducted in India and this study scrutinized the studies registered for COVID-19 from the database to detect patterns in trial design, appraising the target regions of therapiesand comprehending the terrain of research endeavors. This was a cross-sectional study that analyzed the registered trials for COVID-19 between March 2020 and September 2023. A trial search was conducted on the CTRI database to include all types of studies registered for COVID-19 with keywords like "COVID" and "coronavirus" and studies conducted on conditions other than COVID-19 were excluded. The data regarding study characteristics were noted under various sections in a preformed proforma. A total of 807 trials were taken for final analysis and there were about 344 prospective and 260 retrospective interventional trials, 35 prospective and 165 retrospective observational studies, and two prospective and one retrospective post-marketing surveillance study. The majority of the studies had duration under 12 months (91%). The maximum number of studies were registered from AYUSH (Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy) and allied therapies (n = 283), with about 104 types of interventions, followed by the drug category having 119 trials registered and about 57 types of interventions. Kabasura Kudineer and yoga in the AYUSH category, molnupiravir, colchicine, and favipiravir in the drug category, and tocilizumaband convalescent plasma among biologics were some common interventions used. The majority of trials did not mention the trial phase and declared it as not applicable (54%), whereas 15% were registered as phase 2 and 13% as phase 3. About 54% of the studies were randomized and randomized parallel-group design (20%) was the most common study design. Only 6% of the trials were post-graduate thesis and the majority of the trials (n = 535) denied sharing their individual participant data. Only 0.86% and 0.61% of the trials were terminated and suspended, respectively, denoting proper design and conduct of the trials. In the CTRI database, the majority of trials were prospective interventional studies, with a predominance of AYUSH therapies and drug interventions. Common interventions included Kabasura Kudineer and yoga in AYUSH, and molnupiravir, colchicine, and favipiravir in drugs. Most studies had durations under 12 months and randomized parallel-group design was the most common study design. The intention to use and promote an indigenous system of medicine looks promising in the absence of any definite therapy. A minute number of registered suspended and terminated trials might bea positive picture of meticulously designed and executed trials even during a pandemic situation in India.

Reporting of health equity considerations in vaccine trials for COVID-19: a methodological review

Background and ObjectivesAn emerging body of randomized controlled trials (RCTs) on COVID-19 vaccines has served as the evidence base for public health decision-making. While it is recommended that RCTs report results by health equity stratifiers to reduce bias in health care and gaps in research, it is unknown whether this was done in COVID-19 vaccine trials. To critically examine the use of health equity stratifiers in COVID-19 vaccine trials. Study Design and SettingWe conducted a methodological review of published COVID-19 vaccine trials available in the COVID-19 living Network Meta-Analysis systematic review database through February 8, 2023. Based on the PROGRESS-Plus framework, we examined the following health equity stratifiers: place of residence, race/ethnicity, occupation, gender/sex, religion, education, socio-economic status, social capital, age, disability, features of relationships, and temporary situations. We assessed each study in duplicate according to three criteria for comprehensive health-equity reporting: 1) describing participants, 2) reporting equity-relevant results, and 3) discussing equity-relevant implications of trial findings. ResultsWe reviewed 144 trial manuscripts. The most frequently used PROGRESS-Plus stratifiers to describe participants were age (100%), place of residence (100%), gender/sex (99%), and race/ethnicity (64%). Age was most often used to disaggregate or adjust results (67%), followed by gender or sex (35%). Discussions of equity-relevant implications often indicated limited generalizability of results concerning age (40% of studies). Half (47%) of the studies considered at least one health equity stratifier for all three criteria. No trials included stratifiers related to religion, socioeconomic status, sexual orientation, or features of relationships. ConclusionCOVID-19 vaccine trials provided a limited description of health equity stratifiers as defined by PROGRESS-Plus and infrequently disaggregated results or discussed the study implications as they related to health equity. Considering the health disparities exacerbated during the pandemic, increased uptake of PROGRESS-Plus in RCTs would support a more nuanced understanding of health disparities and better inform actions to improve health equity.

Interleukin 6 Antagonists in Severe COVID-19 Disease: Cardiovascular and Respiratory Outcomes.

Inhibitors of interleukin 6 [IL-6] have been utilized to treat severe COVID-19 disease. Their immunosuppressive or immunomodulating impact may be beneficial in COVID-19. To discuss the role of IL-6 inhibitors and assess various trials conducted to evaluate the efficacy of IL-6 inhibitors in COVID-19 disease. Two of the most common causes of mortality in COVID-19-infected critically ill individuals are acute respiratory distress syndrome (ARDS) and multiorgan failure. Increased levels of inflammatory cytokines suggest that a cytokine storm, also known as cytokine release syndrome (CRS), is involved in the etiology of COVID-19. Most tissue damage, sepsis, and pulmonary and cardiovascular problems are caused mainly by the host defense system. Therefore, regulating this inflammatory cascade using immunomodulators is a prudent strategy. Although corticosteroids, as immunomodulators, are routinely used in COVID-19 management, interleukin (IL) inhibitors, especially IL-6 inhibitors, are also tested in many trials. Many studies have demonstrated that IL-6 inhibitors improve disease outcomes and decrease mortality, whereas others have shown that they are ineffective. In this paper, we briefly examined the role of IL-6 in COVID-19 pathogenesis and trials that support or refute the use of IL-6 inhibitors in treating COVID-19 disease. Though mixed results are coming from trials regarding the adjuvant use of IL-6 inhibitors and standard anti-viral therapy with dexamethasone, a consensus favors using IL-6 inhibitors in severely ill COVID-19 patients regardless of the outcome.

A clustering and graph deep learning-based framework for COVID-19 drug repurposing

Drug repurposing (or repositioning) is the process of finding new therapeutic uses for drugs already approved by drug regulatory authorities (e.g., the Food and Drug Administration (FDA) and Therapeutic Goods Administration (TGA)) for other diseases. This involves analysing the interactions between different biological entities, such as drug targets (genes/proteins and biological pathways) and drug properties, to discover novel drug–target or drug–disease relations. Machine learning and deep learning models have successfully analysed complex heterogeneous data with applications in the biomedical domain, and have also been used for drug repurposing. This study presents a novel unsupervised machine learning framework that utilizes a graph-based autoencoder for multi-feature type clustering on heterogeneous drug data. The dataset consists of 438 drugs, of which 224 are under clinical trials for COVID-19 (category A). The rest are systematically filtered to ensure the safety and efficacy of the treatment (category B). The framework solely relies on reported drug data, including its pharmacological properties, chemical/physical properties, interaction with the host, and efficacy in different publicly available COVID-19 assays. Our machine-learning framework revealed three clusters of interest and provided recommendations featuring the top 15 drugs for COVID-19 drug repurposing, which were shortlisted based on the predicted clusters that were dominated by category A drugs. Our framework can be extended to support other datasets and drug repurposing studies with the availability of our open-source code.