{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T20:29:52Z","timestamp":1786480192634,"version":"build-2736575974"},"reference-count":42,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"7","license":[{"start":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T00:00:00Z","timestamp":1777939200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"crossref","award":["K01 DK120784"],"award-info":[{"award-number":["K01 DK120784"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100018488","name":"Clinical and Translational Science Institute, University of Florida","doi-asserted-by":"crossref","award":["97071"],"award-info":[{"award-number":["97071"]}],"id":[{"id":"10.13039\/100018488","id-type":"DOI","asserted-by":"crossref"}]},{"name":"University of Florida Research","award":["DRPD-ROSF2023"],"award-info":[{"award-number":["DRPD-ROSF2023"]}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"crossref","award":["UL1 TR000064"],"award-info":[{"award-number":["UL1 TR000064"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"crossref","award":["UL1TR001427"],"award-info":[{"award-number":["UL1TR001427"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"crossref","award":["K01 DK120784"],"award-info":[{"award-number":["K01 DK120784"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100018488","name":"Clinical and Translational Science Institute, University of Florida","doi-asserted-by":"crossref","award":["97071"],"award-info":[{"award-number":["97071"]}],"id":[{"id":"10.13039\/100018488","id-type":"DOI","asserted-by":"crossref"}]},{"name":"University of Florida Research","award":["DRPD-ROSF2023"],"award-info":[{"award-number":["DRPD-ROSF2023"]}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"crossref","award":["UL1 TR000064"],"award-info":[{"award-number":["UL1 TR000064"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"crossref","award":["UL1TR001427"],"award-info":[{"award-number":["UL1TR001427"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":["Kidney360"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Intraoperative hypotension is associated with postoperative AKI, which is a common and morbid postoperative complication.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>We developed a reinforcement learning model to guide intraoperative fluids and vasopressors, avoiding hypotension and postoperative AKI.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>The model's policy showcases the potential to lower postoperative AKI and improve outcomes driven by intraoperative hypotension.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Traditional methods of surgical decision making heavily rely on human experience and prompt actions, which are variable. A data-driven system that generates treatment recommendations based on patient states can be a substantial asset in perioperative decision making for cases of intraoperative hypotension in which suboptimal management is associated with AKI, a common and morbid postoperative complication.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this retrospective cohort study, we analyzed 50,021 surgeries from 42,547 adult patients who underwent major surgery at a quaternary care hospital between 2014 and 2020. We developed a deep reinforcement learning model to recommend the optimum doses of intravenous fluids and vasopressors during surgery to avoid intraoperative hypotension and AKI defined by Kidney Disease Improving Global Outcomes serum creatinine criteria within 3 days after surgery.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The developed model replicated 69% of physicians' decisions for the dosage of vasopressors and proposed higher or lower dosage of vasopressors than received in 10% and 21% of the treatments, respectively. In terms of intravenous fluids, the model's recommendations were within 0.05 ml\/kg per 15 minutes of the actual dose in 41% of the cases, with higher or lower doses recommended for 27% and 32% of the treatments, respectively. The reinforcement learning policy resulted in a higher estimated policy value compared with the physicians' actual treatments, as well as random policies and zero-drug policies. AKI incidence was the lowest in patients who received medication dosages that aligned with our agent model's decisions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our findings suggest that implementation of the model's policy has the potential to lower postoperative AKI and improve other outcomes driven by intraoperative hypotension.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.34067\/kid.0000001212","type":"journal-article","created":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T16:00:58Z","timestamp":1777996858000},"page":"1535-1544","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":1,"title":["Reinforcement Learning for Intraoperative Hypotension Management with Consideration to Postoperative Acute Kidney Injury"],"prefix":"10.34067","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4922-8888","authenticated-orcid":false,"given":"Esra","family":"Adiyeke","sequence":"first","affiliation":[{"name":"Intelligent Clinical Care Center, University of Florida, Gainesville, Florida"},{"name":"Division of Nephrology, Hypertension, and Renal Transplantation, Department of Medicine, University of Florida, Gainesville, Florida"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8617-5236","authenticated-orcid":false,"given":"Tianqi","family":"Liu","sequence":"additional","affiliation":[{"name":"Intelligent Clinical Care Center, University of Florida, Gainesville, Florida"},{"name":"Department of Electrical and Computer Engineering, University of Florida, Gainesville, Florida"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8115-8185","authenticated-orcid":false,"given":"Venkata Sai Dheeraj","family":"Naganaboina","sequence":"additional","affiliation":[{"name":"Intelligent Clinical Care Center, University of Florida, Gainesville, Florida"},{"name":"Department of Computer Science, University of Florida, Gainesville, Florida"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9800-9948","authenticated-orcid":false,"given":"Han","family":"Li","sequence":"additional","affiliation":[{"name":"Intelligent Clinical Care Center, University of Florida, Gainesville, Florida"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5354-443X","authenticated-orcid":false,"given":"Tyler J.","family":"Loftus","sequence":"additional","affiliation":[{"name":"Intelligent Clinical Care Center, University of Florida, Gainesville, Florida"},{"name":"Department of Surgery, University of Florida, Gainesville, Florida"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4716-2408","authenticated-orcid":false,"given":"Yuanfang","family":"Ren","sequence":"additional","affiliation":[{"name":"Intelligent Clinical Care Center, University of Florida, Gainesville, Florida"},{"name":"Division of Nephrology, Hypertension, and Renal Transplantation, Department of Medicine, University of Florida, Gainesville, Florida"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5304-7027","authenticated-orcid":false,"given":"Benjamin","family":"Shickel","sequence":"additional","affiliation":[{"name":"Intelligent Clinical Care Center, University of Florida, Gainesville, Florida"},{"name":"Division of Nephrology, Hypertension, and Renal Transplantation, Department of Medicine, University of Florida, Gainesville, Florida"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9757-4454","authenticated-orcid":false,"given":"Matthew M.","family":"Ruppert","sequence":"additional","affiliation":[{"name":"Intelligent Clinical Care Center, University of Florida, Gainesville, Florida"},{"name":"Division of Nephrology, Hypertension, and Renal Transplantation, Department of Medicine, University of Florida, Gainesville, Florida"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8980-2330","authenticated-orcid":false,"given":"Karandeep","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of California San Diego, San Diego, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3980-3532","authenticated-orcid":false,"given":"Ruogu","family":"Fang","sequence":"additional","affiliation":[{"name":"Intelligent Clinical Care 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