{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T02:08:19Z","timestamp":1793326099759,"version":"4.5.0"},"reference-count":33,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Therapeutic Advances in Drug Safety"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Adverse drug reactions (ADRs) are a leading cause of morbidity and mortality worldwide. Despite advances in pharmacovigilance, population-level evidence on long-term trends and disparities in ADR-related mortality in the United States remains limited.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>This study aimed to characterize national temporal trends and demographic, geographic, and drug-class disparities in ADR-related mortality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design:<\/jats:title>\n                    <jats:p>Population-based, cross-sectional analysis of US death certificate data using age-adjusted mortality rates (AAMRs) and log-linear estimated annual percentage changes (EAPCs) to assess temporal trends.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>ADR-related deaths were identified using International Classification of Diseases, Tenth Revision (ICD-10) codes Y40\u2013Y59. AAMRs and EAPCs were calculated to assess temporal trends. Frontier analysis evaluated the relationship between AAMR and the Socio-Demographic Index (SDI) across states, and the leading drug categories contributing to ADR-related deaths were identified.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>A total of 8425 ADR-related deaths were recorded over the study period. The national AAMR increased from 0.086 per 100,000 in 1999 to 0.140 in 2020 (EAPC: 1.49). Men, older adults, Black individuals, and rural residents experienced disproportionately high AAMRs. The West and Midwest regions exhibited steeper increases than other regions. Frontier analysis identified high-SDI states performing comparatively better. Among specific drug classes, anticoagulants were the leading contributors to ADR-related deaths, followed by immunosuppressive agents, antineoplastic drugs, and opioids.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>ADR-related mortality in the United States rose steadily, with pronounced disparities by sex, age, race, geography, and rurality. These findings should be interpreted with caution, given the observational study design and reliance on death certificate-based data.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20420986261421278","type":"journal-article","created":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T11:56:46Z","timestamp":1770983806000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Disparities and trends in drug-related adverse reaction mortality in the United States, 1999\u20132020"],"prefix":"10.1177","volume":"17","author":[{"given":"Liwei","family":"Guo","sequence":"first","affiliation":[{"name":"Department of General Practice, The Affiliated Huaian No.1 People\u2019s Hospital of Nanjing Medical University, Huaian, Jiangsu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0539-9051","authenticated-orcid":false,"given":"Xiuxun","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Clinical Nutrition, The Affiliated Huaian No.1 People\u2019s Hospital of Nanjing Medical University, 1 Huanghe West Road, Huaian, Jiangsu 223300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,2,13]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.2196\/27714"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.279.15.1200"},{"key":"e_1_3_4_4_2","article-title":"Professional, structural and organisational interventions in primary care for reducing medication errors","volume":"10","author":"Khalil H","year":"2017","unstructured":"Khalil H, Bell B, Chambers H, et al. 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