{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T20:42:42Z","timestamp":1793392962707,"version":"4.5.0"},"reference-count":43,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T00:00:00Z","timestamp":1747785600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"the Senior Medical Talents Program of Chongqing for Young and Middle-aged"},{"name":"The Chongqing Science-health joint medical research project","award":["2022QNXM27"],"award-info":[{"award-number":["2022QNXM27"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Technology and Health Care"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Continuous Renal Replacement Therapy (CRRT), is essential for managing acute kidney injury (AKI) Dynamic monitoring of transmembrane pressure (TMP) during CRRT is crucial for predicting filter clotting and optimizing filter lifespan, which indirectly supports anticoagulation management.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To prolong the lifespan of CRRT circuits and enhance the precision of anticoagulation therapy by developing a predictive early warning model for CRRT circuit life, based on dynamic TMP monitoring.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective analysis in the ICU of the First Affiliated Hospital of Army Medical University. Leveraging the TMP data recorded by CRRT machines, we established an adaptive real-time predictive modeling framework, termed DTP (Dynamic Transmembrane Pressure Prediction), utilizing Long Short-Term Memory (LSTM) networks. This framework predicts TMP trends as an early indicator of filter clotting. Our models were validated using over 20,000\u2005min of clinical data from 405 CRRT cases, predicting TMP trajectories within 50\u2005min.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Resuits<\/jats:title>\n                    <jats:p>In simulated treatment evaluations, our LSTM models accurately identified impending TMP increases, achieving recall rates exceeding 0.97 and F2 scores above 0.93. Notably, an average warning time of 23\u2005min was provided prior to the TMP reaching the critical 260\u2005mmHg threshold, indicating substantial filter clotting. An analysis of false alarms revealed patterns consistent with emerging instability and transient artifacts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The personalized early warning model developed within the DTP framework effectively predicts TMP changes, enhancing the accuracy and timeliness of medical interventions. This improvement reduces the incidence of adverse events, maximizes the lifespan of CRRT circuits, and ultimately decreases treatment and personnel costs.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/09287329251337277","type":"journal-article","created":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T11:09:07Z","timestamp":1747825747000},"page":"2305-2319","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["A predictive model for real-time LSTM methods: Monitoring dynamic transmembrane pressure improves loop life and anticoagulant therapy accuracy in continuous renal replacement therapy"],"prefix":"10.1177","volume":"33","author":[{"given":"Fangzheng","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Critical Care Medicine, The First Affiliated Hospital of the Army Medical University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, The First Affiliated Hospital of the Army Medical University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Tan","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, The First Affiliated Hospital of the Army Medical University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tieniu","family":"Mei","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, The First Affiliated Hospital of the Army Medical University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongya","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, The First Affiliated Hospital of the Army Medical University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yonghui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, The First Affiliated Hospital of the Army Medical University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, The First Affiliated Hospital of the Army Medical University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zuzhi","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, The First Affiliated Hospital of the Army Medical University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, The First Affiliated Hospital of the Army Medical University, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,5,21]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12882-019-1660-z"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2018-024411"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1111\/1744-9987.12656"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13613-020-0648-y"},{"key":"e_1_3_3_6_2","first-page":"485","article-title":"Renal replacement therapy in acute kidney injury: from the indications to cessation","volume":"68","author":"K\u00fcllmar M","year":"2019","unstructured":"K\u00fcllmar M, Zarbock A. 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