To identify natural bioactive compounds (NBCs) as potential inhibitors of spike (S1) by means of in silico assays. NBCs with previously proven biological in vitro activity were obtained from the ZINC database and analyzed through virtual screening and molecular docking to identify those with higher affinity to the spike protein. Eight machine learning models were used to validate the results: Principal Component Analysis (PCA), Artificial Neural Network (ANN), Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Partial Least Squares-Discriminant Analysis (PLS-DA), Gradient Boosted Tree Discriminant Analysis (XGBoostDA), Soft Independent Modelling of Class Analogies (SIMCA) and Logistic Regression Discriminate Analysis (LREG). Selected NBCs were submitted to drug-likeness prediction using Lipinski’s and Veber’s rule of five. A prediction of pharmacokinetic parameters and toxicity was also performed (ADMET). Antivirals currently used for COVID-19 (remdesivir and molnupiravir) were used as a comparator. A total of 170,906 compounds were analyzed. Of these, 34 showed greater affinity with the S1 (affinity energy < -7 kcal mol-1). Most of these compounds belonged to the class of coumarins (benzopyrones), presenting a benzene ring fused to a lactone (group of heterosides). The PLS-DA model was able to reproduce the results of the virtual screening and molecular docking (accuracy of 97.0%). Of the 34 compounds, only NBC5 (feselol), NBC14, NBC15 and NBC27 had better results in ADMET predictions. These had similar binding affinity to S1 when compared to remdesivir and molnupirvir. Feselol and three other NBCs were the most promising candidates for treating COVID-19. In vitro and in vivo studies are needed to confirm these findings.

ABSTRACT Introduction: Oral anticoagulants are the treatment of choice for diverse types of coagulation disorders. Warfarin is widely used by the Brazilian population, possibly due to its lower cost than other oral anticoagulants. However, it has a high risk of serious adverse effects if used incorrectly. The Anticoagulation Knowledge Tool (AKT) can assess a patient’s knowledge about her/his oral anticoagulant therapy and can assist health professionals in identifying patients with difficulties in adherence. This study aimed to translate, culturally adapt, and validate the AKT into Brazilian Portuguese. Methods: After a standard forward-backward procedure to translate the AKT into Brazilian Portuguese (AKT-Br), a version of the instrument was applied in three groups (patients, pharmacists, and the general population). The reliability of the AKT-Br was tested using an internal consistency measure and test-retest. The validity of the instrument was confirmed with data from the contrasted groups. All statistical analyses were performed with RStudio. Results: The median scores obtained with the AKT-Br were 29.0, 17.0, and 7.5 for pharmacists, patients, and the general population, respectively (maximum score of 35 points). There was moderate internal consistency for the instrument and test-retest reliability was satisfactory. Analysis of variance for validity of the groups revealed a significant relationship between the total score and the evaluated groups. Conclusion: The ATK-Br is a reliable and valid tool to assess knowledge about oral anticoagulants. AKT-Br can be used in clinical practice as an auxiliary tool to improve patient care through personalised educational interventions.

Resumo A artrite reumatóide (AR) está entre as doenças autoimunes e inflamatórias crônicas mais prevalentes no mundo. O objetivo deste estudo foi estabelecer uma estimativa conjunta da prevalência da AR na América do Sul por meio de uma meta-análise dos estudos epidemiológicos disponíveis. Buscas sistemáticas nas bases de dados PubMed, Lilacs, SciELO, Scopus e Web of Science (atualizado em maio de 2019) foram seguidas por uma busca sistemática na literatura cinzenta para identificar artigos e relatórios de pesquisa originais, publicados após 2000, fornecendo dados de prevalência de AR em qualquer país da América do Sul. Foi realizada uma meta-análise da proporção de dados agrupados ponderados, com heterogeneidade entre experimentos avaliada pelo índice relativo de inconsistência. Análises de sensibilidade e de subgrupos também foram realizadas. Foram incluídos um total de 25 artigos, representando 27 estudos de base populacional. A prevalência agrupada de AR resultou em 0,48% com 591.981 casos em uma população de 114.537.812 indivíduos (I2=99%). Brasil e Colômbia apresentaram as menores taxas de prevalência de AR 0,22% e 0,24%, respectivamente. A prevalência da AR na população indígena foi maior 1,45%, e estudos pelo método COPCORD relataram também as maiores taxas 1,07%.

Abstract Rheumatoid arthritis (RA) is among the most prevalent chronic autoimmune and inflammatory diseases worldwide. The aim of this study was to establish a pooled estimate of the RA prevalence in South America by means of a meta-analysis of the available epidemiologic studies. Systematic searches in PubMed, Lilacs, SciELO, Scopus, and Web of Science databases (updated May 2019) were done followed by a systematic grey literature search to identify original research articles and reports, published after 2000, providing data of RA prevalence in any South American country. Proportion meta-analysis of weighted pooled was performed, with between-trial heterogeneity assessed by the inconsistency relative index. Sensitivity analyses and sub-group analyses were also done. A total of 25 articles, representing 27 population-based studies were included. Pooled prevalence of RA resulted in 0.48% with 591,981 cases in a population of 114,537,812 individuals (I2=99%). Brazil and Colombia presented the lowest rates of RA prevalence 0.22%, and 0.24%, respectively. RA prevalence in indigenous population was higher 1.45%, and studies using COPCORD method reported also the highest rates 1.07%.

Resumo A artrite reumatóide (AR) está entre as doenças autoimunes e inflamatórias crônicas mais prevalentes no mundo. O objetivo deste estudo foi estabelecer uma estimativa conjunta da prevalência da AR na América do Sul por meio de uma meta-análise dos estudos epidemiológicos disponíveis. Buscas sistemáticas nas bases de dados PubMed, Lilacs, SciELO, Scopus e Web of Science (atualizado em maio de 2019) foram seguidas por uma busca sistemática na literatura cinzenta para identificar artigos e relatórios de pesquisa originais, publicados após 2000, fornecendo dados de prevalência de AR em qualquer país da América do Sul. Foi realizada uma meta-análise da proporção de dados agrupados ponderados, com heterogeneidade entre experimentos avaliada pelo índice relativo de inconsistência. Análises de sensibilidade e de subgrupos também foram realizadas. Foram incluídos um total de 25 artigos, representando 27 estudos de base populacional. A prevalência agrupada de AR resultou em 0,48% com 591.981 casos em uma população de 114.537.812 indivíduos (I2=99%). Brasil e Colômbia apresentaram as menores taxas de prevalência de AR 0,22% e 0,24%, respectivamente. A prevalência da AR na população indígena foi maior 1,45%, e estudos pelo método COPCORD relataram também as maiores taxas 1,07%.

Abstract Rheumatoid arthritis (RA) is among the most prevalent chronic autoimmune and inflammatory diseases worldwide. The aim of this study was to establish a pooled estimate of the RA prevalence in South America by means of a meta-analysis of the available epidemiologic studies. Systematic searches in PubMed, Lilacs, SciELO, Scopus, and Web of Science databases (updated May 2019) were done followed by a systematic grey literature search to identify original research articles and reports, published after 2000, providing data of RA prevalence in any South American country. Proportion meta-analysis of weighted pooled was performed, with between-trial heterogeneity assessed by the inconsistency relative index. Sensitivity analyses and sub-group analyses were also done. A total of 25 articles, representing 27 population-based studies were included. Pooled prevalence of RA resulted in 0.48% with 591,981 cases in a population of 114,537,812 individuals (I2=99%). Brazil and Colombia presented the lowest rates of RA prevalence 0.22%, and 0.24%, respectively. RA prevalence in indigenous population was higher 1.45%, and studies using COPCORD method reported also the highest rates 1.07%.

Abstract Systematic reviews and pairwise meta-analyses of randomized controlled trials, at the intersection of clinical medicine, epidemiology and statistics, are positioned at the top of evidence-based practice hierarchy. These are important tools to base drugs approval, clinical protocols and guidelines formulation and for decision-making. However, this traditional technique only partially yield information that clinicians, patients and policy-makers need to make informed decisions, since it usually compares only two interventions at the time. In the market, regardless the clinical condition under evaluation, usually many interventions are available and few of them have been studied in head-to-head studies. This scenario precludes conclusions to be drawn from comparisons of all interventions profile (e.g. efficacy and safety). The recent development and introduction of a new technique – usually referred as network meta-analysis, indirect meta-analysis, multiple or mixed treatment comparisons – has allowed the estimation of metrics for all possible comparisons in the same model, simultaneously gathering direct and indirect evidence. Over the last years this statistical tool has matured as technique with models available for all types of raw data, producing different pooled effect measures, using both Frequentist and Bayesian frameworks, with different software packages. However, the conduction, report and interpretation of network meta-analysis still poses multiple challenges that should be carefully considered, especially because this technique inherits all assumptions from pairwise meta-analysis but with increased complexity. Thus, we aim to provide a basic explanation of network meta-analysis conduction, highlighting its risks and benefits for evidence-based practice, including information on statistical methods evolution, assumptions and steps for performing the analysis.

Objective: The aim of this study is to characterize the patterns and trends in the editorial process and features of the first decade of Pharmacy Practice, with the final goal of initiating a benchmarking process to enhance the quality of the journal. Methods: Metadata of all of the articles published from 2006 issue #3 to 2016 issue #2 were extracted from PubMed and complemented by a manual data extraction process on the full-text articles. Citations of these articles were retrieved from Web of Science (WOS), Scopus, and Google Scholar on August 15, 2016. The references from all of the articles published by Pharmacy Practice in 2015 were also extracted. International collaboration was explored with a network analysis. Results: A total of 40 issues were published in this timespan, including 349 articles, 91.1% of which were original research articles. The number of citations received by these articles varies from 809, as reported by the WOS, to the 1162 reported by Scopus and the 2610 reported by Google Scholar. The journals cited by Pharmacy Practice are mainly pharmacy journals, including Pharm Pract (Granada), Int J Clin Pharm, Am J Health-Syst Pharm, Am J Pharm Educ, and Ann Pharmacother. Only 17.3% of the articles involved international collaboration. Delays in the editorial process increased in 2013, mainly due to an increase in acceptance delay (mean=138 days). Conclusion: Pharmacy Practice has improved its visibility and impact over the past decade, especially after 2014, when the journal became indexed in PubMed Central. The editorial process duration is one of the weaknesses that should be tackled. Further studies should investigate if the low international collaboration rate is common across other pharmacy journals.