{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:38:44Z","timestamp":1760143124344,"version":"build-2065373602"},"reference-count":16,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T00:00:00Z","timestamp":1705968000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["1837985"],"award-info":[{"award-number":["1837985"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>The aim of this research is to apply the learning using privileged information paradigm to sepsis prognosis. We used signal processing of electrocardiogram and electronic health record data to construct support vector machines with and without privileged information to predict an increase in a given patient\u2019s quick-Sequential Organ Failure Assessment score, using a retrospective dataset. We applied this to both a small, critically ill cohort and a broader cohort of patients in the intensive care unit. Within the smaller cohort, privileged information proved helpful in a signal-informed model, and across both cohorts, electrocardiogram data proved to be informative to creating the prediction. Although learning using privileged information did not significantly improve results in this study, it is a paradigm worth studying further in the context of using signal processing for sepsis prognosis.<\/jats:p>","DOI":"10.3390\/diagnostics14030234","type":"journal-article","created":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T04:17:40Z","timestamp":1705983460000},"page":"234","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sepsis Trajectory Prediction Using Privileged Information and Continuous Physiological Signals"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1029-6664","authenticated-orcid":false,"given":"Olivia P.","family":"Alge","sequence":"first","affiliation":[{"name":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Gryak","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Queens College, The City University of New York, Flushing, NY 11367, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0805-0913","authenticated-orcid":false,"given":"J. Scott","family":"VanEpps","sequence":"additional","affiliation":[{"name":"Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, MI 48109, USA"},{"name":"Department of Emergency Medicine, University of Michigan, Ann Arbor, MI 48109, USA"},{"name":"Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA"},{"name":"Macromolecular Science and Engineering, University of Michigan, Ann Arbor, MI 48109, USA"},{"name":"The Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, MI 48109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kayvan","family":"Najarian","sequence":"additional","affiliation":[{"name":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA"},{"name":"Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, MI 48109, USA"},{"name":"Department of Emergency Medicine, University of Michigan, Ann Arbor, MI 48109, USA"},{"name":"The Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, MI 48109, USA"},{"name":"Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA"},{"name":"Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI 48109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1001\/jama.2016.0287","article-title":"The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)","volume":"315","author":"Singer","year":"2016","journal-title":"JAMA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1889","DOI":"10.1097\/CCM.0000000000003342","article-title":"Epidemiology and Costs of Sepsis in the United States-An Analysis Based on Timing of Diagnosis and Severity Level","volume":"46","author":"Paoli","year":"2018","journal-title":"Crit. Care Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"762","DOI":"10.1001\/jama.2016.0288","article-title":"Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)","volume":"315","author":"Seymour","year":"2016","journal-title":"JAMA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"e1063","DOI":"10.1097\/CCM.0000000000005337","article-title":"Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2021","volume":"49","author":"Evans","year":"2021","journal-title":"Crit. Care Med."},{"key":"ref_5","unstructured":"Alge, O.P., Pickard, J., Zhang, W., Cheng, S., Derksen, H., Omenn, G.S., Gryak, J., VanEpps, J.S., and Najarian, K. (Sci. Rep., 2021). Continuous Sepsis Trajectory Prediction using Tensor-Reduced Physiological Signals, Sci. Rep., in review."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sabeti, E., Drews, J., Reamaroon, N., Gryak, J., Sjoding, M., and Najarian, K. (2019, January 23\u201327). Detection of Acute Respiratory Distress Syndrome by Incorporation of Label Uncertainty and Partially Available Privileged Information. Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany.","DOI":"10.1109\/EMBC.2019.8857434"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1109\/JBHI.2020.3008601","article-title":"Learning Using Partially Available Privileged Information and Label Uncertainty: Application in Detection of Acute Respiratory Distress Syndrome","volume":"25","author":"Sabeti","year":"2021","journal-title":"IEEE J. Biomed. 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