{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T14:58:26Z","timestamp":1789052306716,"version":"build-2803163510"},"reference-count":44,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000774","name":"Defense Threat Reduction Agency","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000774","id-type":"DOI","asserted-by":"crossref"}]},{"id":[{"id":"https:\/\/ror.org\/04tz64554","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000030","name":"Centers for Disease Control and Prevention","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000030","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Science Foundation"},{"id":[{"id":"https:\/\/ror.org\/021nxhr62","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012399","name":"Biomedical Advanced Research and Development Authority","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100012399","id-type":"DOI","asserted-by":"crossref"}]},{"id":[{"id":"https:\/\/ror.org\/029y69023","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Prenosis"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background: Early and accurate risk stratification of patients suspected of serious infection is essential for improving outcomes, but existing diagnostic and predictive tools have limited accuracy. The objective was to compare the performance of an FDA-authorized AI diagnostic test, the Sepsis ImmunoScore, against widely available biomarkers and clinical tools for diagnosis of sepsis and prediction of in-hospital mortality and intensive care unit (ICU) admission. Methods: This multicenter observational study included 6027 adult patients suspected of infection across 7 U.S. hospital sites. The Sepsis ImmunoScore\u2019s predictive performance was compared to the sequential organ failure assessment (SOFA) score, procalcitonin (PCT), C-reactive protein (CRP), Systemic Inflammatory Response Syndrome (SIRS) score, National Early Warning Score (NEWS), and quick SOFA (qSOFA). Primary outcomes included sepsis as defined by Sepsis-3 criteria, in-hospital mortality, and ICU admission. Predictive accuracy was assessed using area under the receiver operating characteristic curve (AUC), and 95% confidence intervals were generated and hypothesis testing conducted using the bootstrap method. Results: The Sepsis ImmunoScore demonstrated statistically significant superior performance across all outcomes. For sepsis prediction, the Sepsis ImmunoScore achieved an AUC of 0.82, compared to SOFA (0.72), procalcitonin (PCT) (0.70), C-reactive protein (CRP) (0.61), SIRS (0.59), NEWS (0.69), and qSOFA (0.67). For in-hospital mortality prediction, the Sepsis ImmunoScore achieved an AUC of 0.80, outperforming SOFA (0.72), PCT (0.67), CRP (0.58), SIRS (0.60), NEWS (0.72), and qSOFA (0.69). For ICU admission, the Sepsis ImmunoScore reached an AUC of 0.74, superior to SOFA (0.63), PCT (0.64), CRP (0.54), SIRS (0.60), NEWS (0.70), and qSOFA (0.65). All differences between the Sepsis ImmunoScore and comparators were statistically significant. Conclusions: The Sepsis ImmunoScore significantly improved predictive accuracy for sepsis, in-hospital mortality, and ICU admission compared to six conventional clinical scores and biomarkers. This AI-based tool may enhance risk stratification and clinical decision-making, potentially leading to more timely sepsis interventions and improved outcomes.<\/jats:p>","DOI":"10.3390\/diagnostics16131962","type":"journal-article","created":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T01:03:56Z","timestamp":1782349436000},"page":"1962","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["The Sepsis ImmunoScore Predicts Sepsis, Mortality, and Deterioration Better than Clinical Scores and Widely Available Biomarkers"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7597-7359","authenticated-orcid":false,"given":"Gregory L.","family":"Watson","sequence":"first","affiliation":[{"name":"Prenosis, Inc., Chicago, IL 60616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8239-2096","authenticated-orcid":false,"given":"Lincoln C.","family":"Updike","sequence":"additional","affiliation":[{"name":"Prenosis, Inc., Chicago, IL 60616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7160-9835","authenticated-orcid":false,"given":"Carlos G.","family":"L\u00f3pez-Espina","sequence":"additional","affiliation":[{"name":"Prenosis, Inc., Chicago, IL 60616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9314-0863","authenticated-orcid":false,"given":"Akhil","family":"Bhargava","sequence":"additional","affiliation":[{"name":"Prenosis, Inc., Chicago, IL 60616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3231-4930","authenticated-orcid":false,"given":"Lee A.","family":"Schmalz","sequence":"additional","affiliation":[{"name":"Prenosis, Inc., Chicago, IL 60616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3359-1601","authenticated-orcid":false,"given":"Shah","family":"Khan","sequence":"additional","affiliation":[{"name":"Prenosis, Inc., Chicago, IL 60616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8994-2820","authenticated-orcid":false,"given":"Dennys S.","family":"Urdiales","sequence":"additional","affiliation":[{"name":"Prenosis, Inc., Chicago, IL 60616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4427-6653","authenticated-orcid":false,"given":"Matthew D.","family":"Sims","sequence":"additional","affiliation":[{"name":"Department of Medicine, Section of Infectious Diseases and International Medicine, Corewell Health William Beaumont University Hospital, Royal Oak, MI 48073, USA"},{"name":"Departments of Internal Medicine and Foundational Medical Studies, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8998-1469","authenticated-orcid":false,"given":"Ashok V.","family":"Palagiri","sequence":"additional","affiliation":[{"name":"Mercy Hospital, St. Louis, MO 63141, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4106-7055","authenticated-orcid":false,"given":"Adrian D.","family":"Haimovich","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3404-9983","authenticated-orcid":false,"given":"Alon","family":"Dagan","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, 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