Ivermectin and outcomes from Covid‐19 pneumonia: A systematic review and meta‐analysis of randomized clinical trial studies

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Abstract

Ivermectin is an FDA‐approved drug for a parasitic disease that has broad antiviral activity. This study aims to analyse the efficacy of ivermectin in improving the Covid‐19 outcomes. We systematically searched the PubMed, Europe PMC and ClinicalTrials.gov database using specific keywords related to our aims until 10th May 2021. All published randomized clinical trial studies on Covid‐19 and ivermectin were retrieved. The quality of the study was assessed using Jadad scale assessment tool for clinical trial studies. Statistical analysis was done using Review Manager 5.4 software. A total of 19 studies with 2768 Covid‐19 patients were included in this meta‐analysis. This meta‐analysis showed that ivermectin was associated with reduction in severity of Covid‐19 (RR 0.43 [95% CI 0.23–0.81], p = 0.008), reduction of mortality (RR 0.31 [95% CI 0.15–0.62], p = 0.001), higher negative RT‐PCR test results rate (RR 1.23 [95% CI 1.01–1.51], p = 0.04), shorter time to negative RT‐PCR test results (mean difference [MD] −3.29 [95% CI −5.69, −0.89], p = 0.007), higher symptoms alleviations rate (RR 1.23 [95% CI 1.03−1.46], p = 0.02), shorter time to symptoms alleviations (MD −0.68 [95% CI −1.07, −0.29], p = 0.0007) and shorter time to hospital discharge (MD −2.66 [95% CI −4.49, −0.82], p = 0.004). Our study suggests that ivermectin may offer beneficial effects towards Covid‐19 outcomes. More randomized clinical trial studies are still needed to confirm the results of our study.

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Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

Xiang Wan, Wenqian Wang, Jiming Liu … (2014)

Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. Results We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. Conclusions In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-135) contains supplementary material, which is available to authorized users.

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Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis

Alfonso J. Rodríguez-Morales, Jaime A. Cardona-Ospina, Estefanía Gutiérrez-Ocampo … (2020)

Introduction An epidemic of Coronavirus Disease 2019 (COVID-19) began in December 2019 in China leading to a Public Health Emergency of International Concern (PHEIC). Clinical, laboratory, and imaging features have been partially characterized in some observational studies. No systematic reviews on COVID-19 have been published to date. Methods We performed a systematic literature review with meta-analysis, using three databases to assess clinical, laboratory, imaging features, and outcomes of COVID-19 confirmed cases. Observational studies and also case reports, were included, and analyzed separately. We performed a random-effects model meta-analysis to calculate pooled prevalences and 95% confidence intervals (95%CI). Results 660 articles were retrieved for the time frame (1/1/2020-2/23/2020). After screening, 27 articles were selected for full-text assessment, 19 being finally included for qualitative and quantitative analyses. Additionally, 39 case report articles were included and analyzed separately. For 656 patients, fever (88.7%, 95%CI 84.5–92.9%), cough (57.6%, 95%CI 40.8–74.4%) and dyspnea (45.6%, 95%CI 10.9–80.4%) were the most prevalent manifestations. Among the patients, 20.3% (95%CI 10.0–30.6%) required intensive care unit (ICU), 32.8% presented with acute respiratory distress syndrome (ARDS) (95%CI 13.7–51.8), 6.2% (95%CI 3.1–9.3) with shock. Some 13.9% (95%CI 6.2–21.5%) of hospitalized patients had fatal outcomes (case fatality rate, CFR). Conclusion COVID-19 brings a huge burden to healthcare facilities, especially in patients with comorbidities. ICU was required for approximately 20% of polymorbid, COVID-19 infected patients and hospitalization was associated with a CFR of >13%. As this virus spreads globally, countries need to urgently prepare human resources, infrastructure and facilities to treat severe COVID-19.

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The FDA-approved Drug Ivermectin inhibits the replication of SARS-CoV-2 in vitro

Leon Caly, Julian Druce, Mike Catton … (2020)

Although several clinical trials are now underway to test possible therapies, the worldwide response to the COVID-19 outbreak has been largely limited to monitoring/containment. We report here that Ivermectin, an FDA-approved anti-parasitic previously shown to have broad-spectrum anti-viral activity in vitro, is an inhibitor of the causative virus (SARS-CoV-2), with a single addition to Vero-hSLAM cells 2 hours post infection with SARS-CoV-2 able to effect ∼5000-fold reduction in viral RNA at 48 h. Ivermectin therefore warrants further investigation for possible benefits in humans.