{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:30:56Z","timestamp":1781109056589,"version":"3.54.1"},"reference-count":64,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T00:00:00Z","timestamp":1765411200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Pharmacol."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to detect tirofiban-related adverse event (AE) signals using the FAERS and WHO-VigiAccess databases to support safer clinical use.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>All tirofiban-related AE reports were retrieved from FAERS (2004Q1 to 2024Q4) and WHO-VigiAccess (Retrieval date 2024.12.15). Disproportionality analyses were performed using ROR (Reporting Odds Ratio), PRR (Proportional Reporting Ratio), BCPNN (Bayesian Confidence Propagation Neural Network), and MGPS (Multi-item Gamma Poisson Shrinker) to detect potential drug-AE associations. Time - to - onset was assessed with Weibull distribution and Kaplan-Meier methods. Sensitivity analyses were performed according to reporter type, age group, and sex to assess the robustness of the findings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 2,421 reports from FAERS and 3,485 from WHO-VigiAccess were identified. Bleeding and thrombocytopenia were the most frequent AEs, consistent with drug labeling. Notably, 21 AE signals suggestive of possible associations not listed in the current drug label were observed, such as vascular stent thrombosis and cardiogenic death, which require further studies to verify their causal relationship with tirofiban. The mean onset time was 12\u00a0h, and 96.49% occurred within 1\u00a0month of exposure. Subgroup analyses showed that male patients exhibited a stronger signal for thrombocytopenia, whereas female patients had a higher risk of ischemic heart disease. Elderly patients (\u226565\u00a0years) more frequently experienced hemoglobin decreased, while younger patients (&amp;lt;65years) had a higher risk of thrombosis in device.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study identified both known and potentially novel tirofiban-related AEs. The rapid onset, particularly of bleeding and thrombocytopenia, highlights the importance of early monitoring. Management strategies, such as dose adjustment, temporary discontinuation, or supportive treatment including platelet transfusion, may help mitigate severe complications. These findings provide real-world evidence to guide safer tirofiban use, although further studies are required to confirm causality.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fphar.2025.1713141","type":"journal-article","created":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T06:32:30Z","timestamp":1765434750000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Real-world safety of tirofiban: a disproportionality analysis using data from FAERS and WHO-VigiAccess"],"prefix":"10.3389","volume":"16","author":[{"given":"Jia","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingquan","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaiyun","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,12,11]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1007\/s002280050466","article-title":"A Bayesian neural network method for adverse drug reaction signal generation","volume":"54","author":"Bate","year":"1998","journal-title":"Eur. 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