{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T13:01:22Z","timestamp":1771333282685,"version":"3.50.1"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T00:00:00Z","timestamp":1771286400000},"content-version":"vor","delay-in-days":41,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>The aim of this study was to evaluate the impact of switching population pharmacokinetic models used for model-informed precision dosing (MIPD) of vancomycin on target attainment, acute kidney injury rates, dosing, and sampling burden in 90\u200a295 patients across nineteen hospital systems.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We assessed sites that changed their default vancomycin MIPD model on primary endpoints, including vancomycin area under the concentration\u2013time curve (AUC) target attainment, time to target attainment, and vancomycin-associated AKI rates using an interrupted time series model. Secondary endpoints included vancomycin dosing (day 1 and total course) and sampling frequency. Hospital systems that did not change models served as controls.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In BMI &amp;lt; 40\u2005kg\/m\u00b2 patients, the Goti-to-Thomson model transition significantly improved AUC target attainment on day 1 (+2.1%, P\u200a&amp;lt;\u200a0.001), day 2 (+3.1%, P\u200a&amp;lt;\u200a0.001), and across the whole treatment course (+2.7%, P\u200a&amp;lt;\u200a0.001). Small increases occurred in vancomycin sampling per course (+0.06 samples\/course, P\u200a&amp;lt;\u200a0.05) and time to target attainment (+0.26\u2005hours, P\u200a&amp;lt;\u200a0.05). AUC improvements occurred without statistically significant increases in AKI incidence (KDIGO Stage 1: +0.314%, P\u200a&amp;gt;\u200a0.05\/3; Stage 2: +0.347%, P\u200a&amp;gt;\u200a0.05\/3, Stage 3: +0.034%, P\u200a&amp;gt;\u200a0.05\/3). No significant differences were observed in the BMI \u2265 40\u2005kg\/m2 or control cohorts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This large quasi-experimental study shows that switching from one pair of well-validated and highly predictive models to another improves vancomycin target attainment while maintaining low adverse event rates.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/jacamr\/dlag016","type":"journal-article","created":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T12:40:56Z","timestamp":1769776856000},"source":"Crossref","is-referenced-by-count":0,"title":["Vancomycin target attainment improved following population pharmacokinetic model switch: a large-scale quasi-experimental study of precision dosing"],"prefix":"10.1093","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7396-7958","authenticated-orcid":false,"given":"Dominic M H","family":"Tong","sequence":"first","affiliation":[{"name":"Data Science and Engineering, InsightRX , San Francisco, CA ,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jordan T","family":"Brooks","sequence":"additional","affiliation":[{"name":"Data Science and Engineering, InsightRX , San Francisco, CA ,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ron J","family":"Keizer","sequence":"additional","affiliation":[{"name":"Data Science and Engineering, InsightRX , San Francisco, CA ,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3053-1251","authenticated-orcid":false,"given":"Jasmine H","family":"Hughes","sequence":"additional","affiliation":[{"name":"Data Science and Engineering, InsightRX , San 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