{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T07:23:30Z","timestamp":1773213810146,"version":"3.50.1"},"reference-count":45,"publisher":"eLife Sciences Publications, Ltd","license":[{"start":{"date-parts":[[2021,11,23]],"date-time":"2021-11-23T00:00:00Z","timestamp":1637625600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2021,11,23]],"date-time":"2021-11-23T00:00:00Z","timestamp":1637625600000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2021,11,23]],"date-time":"2021-11-23T00:00:00Z","timestamp":1637625600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"BioNexus KC","award":["20-7"],"award-info":[{"award-number":["20-7"]}]}],"content-domain":{"domain":["elifesciences.org"],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2021,11,21]]},"abstract":"<jats:sec id=\"abs1\">\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Potential therapy and confounding factors including typical co\u2010administered medications, patient\u2019s disease states, disease prevalence, patient demographics, medical histories, and reasons for prescribing a drug often are incomplete, conflicting, missing, or uncharacterized in spontaneous adverse drug event (ADE) reporting systems. These missing or incomplete features can affect and limit the application of quantitative methods in pharmacovigilance for meta-analyses of data during randomized clinical trials.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"abs2\">\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Data from patients with hypertension were retrieved and integrated from the FDA Adverse Event Reporting System; 134 antihypertensive drugs out of 1131 drugs were filtered and then evaluated using the empirical Bayes geometric mean (EBGM) of the posterior distribution to build ADE-drug profiles with an emphasis on the pulmonary ADEs. Afterward, the graphical least absolute shrinkage and selection operator (GLASSO) captured drug associations based on pulmonary ADEs by correcting hidden factors and confounder misclassification. Selected drugs were then compared using the Friedman test in drug classes and clusters obtained from GLASSO.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"abs3\">\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Following multiple filtering stages to exclude insignificant and noise-driven reports, we found that drugs from antihypertensives agents, urologicals, and antithrombotic agents (macitentan, bosentan, epoprostenol, selexipag, sildenafil, tadalafil, and beraprost) form a similar class with a significantly higher incidence of pulmonary ADEs. Macitentan and bosentan were associated with 64% and 56% of pulmonary ADEs, respectively. Because these two medications are prescribed in diseases affecting pulmonary function and may be likely to emerge among the highest reported pulmonary ADEs, in fact, they serve to validate the methods utilized here. Conversely, doxazosin and rilmenidine were found to have the least pulmonary ADEs in selected drugs from hypertension patients. Nifedipine and candesartan were also found by signal detection methods to form a drug cluster, shown by several studies an effective combination of these drugs on lowering blood pressure and appeared an improved side effect profile in comparison with single-agent monotherapy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"abs4\">\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>We consider pulmonary ADE profiles in multiple long-standing groups of therapeutics including antihypertensive agents, antithrombotic agents, beta-blocking agents, calcium channel blockers, or agents acting on the renin-angiotensin system, in patients with hypertension associated with high risk for coronavirus disease 2019 (COVID-19). We found that several individual drugs have significant differences between their drug classes and compared to other drug classes. For instance, macitentan and bosentan from endothelin receptor antagonists show major concern while doxazosin and rilmenidine exhibited the least pulmonary ADEs compared to the outcomes of other drugs. Using techniques in this study, we assessed and confirmed the hypothesis that drugs from the same drug class could have very different pulmonary ADE profiles affecting outcomes in acute respiratory illness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"abs5\">\n                    <jats:title>Funding:<\/jats:title>\n                    <jats:p>GJW and MJD accepted funding from BioNexus KC for funding on this project, but BioNexus KC had no direct role in this article.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.7554\/elife.70734","type":"journal-article","created":{"date-parts":[[2021,11,22]],"date-time":"2021-11-22T11:15:12Z","timestamp":1637579712000},"update-policy":"https:\/\/doi.org\/10.7554\/elife.70734","source":"Crossref","is-referenced-by-count":6,"title":["Data mining methodology for response to hypertension symptomology\u2014application to COVID-19-related pharmacovigilance"],"prefix":"10.7554","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3349-7183","authenticated-orcid":true,"given":"Xuan","family":"Xu","sequence":"first","affiliation":[{"name":"1DATA Consortium, www.1DATA.life","place":["Olathe, United States"]},{"name":"Department of Mathematics, Kansas State University","place":["Kansas City, United States"]},{"name":"Kansas State University Olathe","place":["Olathe, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7141-5698","authenticated-orcid":true,"given":"Jessica","family":"Kawakami","sequence":"additional","affiliation":[{"name":"1DATA Consortium, www.1DATA.life","place":["Olathe, United States"]},{"name":"School of Pharmacy, Division of Pharmacology and Pharmaceutical Sciences, University of Missouri-Kansas City","place":["Kansas City, United States"]},{"name":"Molecular Biology and Biochemistry, School of Biological and Chemical Sciences, University of Missouri-Kansas City","place":["Kansas City, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nuwan Indika","family":"Millagaha Gedara","sequence":"additional","affiliation":[{"name":"1DATA Consortium, www.1DATA.life","place":["Olathe, United States"]},{"name":"Kansas State University Olathe","place":["Olathe, United States"]},{"name":"Department of Business Economics, University of Colombo","place":["Colombo, Sri Lanka"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jim E","family":"Riviere","sequence":"additional","affiliation":[{"name":"1DATA Consortium, www.1DATA.life","place":["Olathe, United States"]},{"name":"Kansas State University and North Carolina State University","place":["Kansas city, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emma","family":"Meyer","sequence":"additional","affiliation":[{"name":"1DATA Consortium, www.1DATA.life","place":["Olathe, United States"]},{"name":"School of Pharmacy, Division of Pharmacology and Pharmaceutical Sciences, University of Missouri-Kansas City","place":["Kansas City, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gerald J","family":"Wyckoff","sequence":"additional","affiliation":[{"name":"1DATA Consortium, www.1DATA.life","place":["Olathe, United States"]},{"name":"School of Pharmacy, Division of Pharmacology and Pharmaceutical Sciences, University of Missouri-Kansas City","place":["Kansas City, United States"]},{"name":"Molecular Biology and Biochemistry, School of Biological and Chemical Sciences, University of Missouri-Kansas City","place":["Kansas City, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8505-6550","authenticated-orcid":true,"given":"Majid","family":"Jaberi-Douraki","sequence":"additional","affiliation":[{"name":"1DATA Consortium, www.1DATA.life","place":["Olathe, United States"]},{"name":"Department of Mathematics, Kansas State University","place":["Kansas City, United States"]},{"name":"Kansas State University Olathe","place":["Olathe, United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"4374","published-online":{"date-parts":[[2021,11,23]]},"reference":[{"key":"bib1","doi-asserted-by":"publisher","first-page":"696","DOI":"10.2337\/diacare.22.5.696","article-title":"Is there a glycemic threshold for mortality risk?","volume":"22","author":"Balkau","year":"1999","journal-title":"Diabetes Care"},{"key":"bib2","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1002\/pds.1742","article-title":"Quantitative signal detection using spontaneous ADR reporting","volume":"18","author":"Bate","year":"2009","journal-title":"Pharmacoepidemiology and Drug Safety"},{"key":"bib3","article-title":"Package \u201cedgebundleR.\u201d","volume-title":"Circle Plot with Bundled Edges","author":"Bostock","year":"2016","unstructured":"Bostock MP, Ellis RK, Tarr G. 2016. 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