{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T08:56:19Z","timestamp":1791276979334,"version":"4.1.0"},"reference-count":50,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R01AG077620"],"award-info":[{"award-number":["R01AG077620"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R01AG065722"],"award-info":[{"award-number":["R01AG065722"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R01AG088522"],"award-info":[{"award-number":["R01AG088522"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["RF1AG089541"],"award-info":[{"award-number":["RF1AG089541"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R01AG060975"],"award-info":[{"award-number":["R01AG060975"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pharmacoepidemiology and Drug"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Nursing home (NH) residents are at high risk for major bleeding and are frequently exposed to complex medication regimens that may increase the likelihood of clinically important drug\u2013drug interactions (DDIs). However, DDI evidence from community\u2010dwelling populations may not generalize to NH residents, and real\u2010world signals involving clopidogrel and oral anticoagulants remain incompletely characterized in this setting. We aimed to identify and interpret candidate DDI signals for major bleeding involving clopidogrel and oral anticoagulants among NH residents.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using linked Minimum Data Set assessments and Medicare fee\u2010for\u2010service claims (2013\u20132020), we conducted high\u2010throughput, self\u2010controlled case series (SCCS) screening analyses for four object drugs (clopidogrel, apixaban, rivaroxaban, and warfarin) paired with candidate precipitant medications. We estimated rate ratios (RRs) and 95% confidence intervals (CIs) comparing periods of concomitant use versus object drug use alone, applying semi\u2010Bayes shrinkage to reduce false\u2010positive signals. To aid interpretation, we incorporated two negative controls: a negative\u2010control object drug (pravastatin) and a negative\u2010control outcome (fall\u2010related injury). A panel of experts evaluated signals for biological plausibility and potential bias.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>After semi\u2010Bayes adjustment, 5\/40 clopidogrel, 1\/29 apixaban, 2\/15 rivaroxaban, and 6\/22 warfarin signals remained significant, and none did for pravastatin. Signals were also observed for fall\u2010related injury. Experts identified only clopidogrel\/sertraline and warfarin with cephalexin, sulfamethoxazole\u2010trimethoprim, and furosemide as biologically plausible signals.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>SCCS screening for DDIs in NH residents identified bleeding signals for clopidogrel and oral anticoagulants, but few were mechanistically coherent and fall\u2010related injury signals suggested residual bias.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/pds.70441","type":"journal-article","created":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T05:54:47Z","timestamp":1784872487000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Drug\u2013Drug Interaction Signals for Major Bleeding in Nursing Home Residents: High\u2010Throughput Screening of Clopidogrel and Oral Anticoagulants"],"prefix":"10.1002","volume":"35","author":[{"given":"Adam M.","family":"D'Amico","sequence":"first","affiliation":[{"name":"Center for Gerontology and Health Care Research, Brown University School of Public Health  Providence Rhode Island USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melissa R.","family":"Riester","sequence":"additional","affiliation":[{"name":"Center for Gerontology and Health Care Research, Brown University School of Public Health  Providence Rhode Island USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5092-9657","authenticated-orcid":false,"given":"Charles E.","family":"Leonard","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel A.","family":"Harris","sequence":"additional","affiliation":[{"name":"Department of Epidemiology College of Health Sciences, University of Delaware  Newark Delaware USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lori A.","family":"Daiello","sequence":"additional","affiliation":[{"name":"Center for Gerontology and Health Care Research, Brown University School of Public Health  Providence Rhode Island USA"},{"name":"Department of Neurology Warren Alpert Medical School, Brown University  Providence Rhode Island USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8848-8658","authenticated-orcid":false,"given":"Yu\u2010Chia (Sam)","family":"Hsu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Douglas 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