<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Rademaker E</submitter><funding>Center for Translational Molecular Medicine</funding><pagination>22-30</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12852201</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>52(1)</volume><pubmed_abstract>&lt;h4>Purpose&lt;/h4>Heterogeneity of the host response in sepsis hampers development of effective treatments. Several immunobiologically distinct subphenotypes (or endotypes) have been identified using data-driven analyses of single-timepoint biomarker data, but their temporal stability remains uncertain due to dynamic biology and statistical limitations.&lt;h4>Methods&lt;/h4>We analyzed data from 345 sepsis patients across two ICU cohorts. 30 immune biomarkers were measured every 8 h for up to 7 days. Latent profile analysis was used to identify classes upon admission and re-classify patients at later timepoints. Temporal robustness was assessed by (1) inter-class transition rates, and (2) intra-class cohesion (regardless of label) using the Rand Index (RI).&lt;h4>Results&lt;/h4>At ICU admission, three immune profiles were identified: profile A (149 patients, 43%) reflected adaptive immune activation (elevated IL-4, IL-5, RANTES, and GM-CSF); profile B (60 patients, 17%) a hyperinflammatory state (high IL-6, IL-8, IL-1Ra, and low protein C); and profile C (136 patients, 39%) broadly attenuated inflammation. By 48 h, the prevalences of A and B declined to 31% and 13%, while C increased to 56%. Inter-class transitions occurred most in patients assigned to A (41% of all 8-hourly transitions), compared to 39% and 22% for B and C. Intra-class cohesion across intervals was poor (median RI 65%, IQR 62-64%), indicating that patients classified together at admission did not remain consistently together.&lt;h4>Conclusion&lt;/h4>Sepsis patients were frequently reclassified across immune profiles over short intervals, with approximately one-third of subgroup peers changing at each timepoint. This instability challenges the clinical utility of biomarker-derived endotypes.</pubmed_abstract><journal>Intensive care medicine</journal><pubmed_title>Temporal robustness of biomarker-based classification algorithms for sepsis.</pubmed_title><pmcid>PMC12852201</pmcid><funding_grant_id>04I-201</funding_grant_id><pubmed_authors>Bos LDJ</pubmed_authors><pubmed_authors>Cremer OL</pubmed_authors><pubmed_authors>van der Poll T</pubmed_authors><pubmed_authors>van Vught L</pubmed_authors><pubmed_authors>Bonten MJM</pubmed_authors><pubmed_authors>de Grooth HJ</pubmed_authors><pubmed_authors>Derde LPG</pubmed_authors><pubmed_authors>Rademaker E</pubmed_authors><pubmed_authors>El Bouhaddani S</pubmed_authors><pubmed_authors>van Amstel RBE</pubmed_authors></additional><is_claimable>false</is_claimable><name>Temporal robustness of biomarker-based classification algorithms for sepsis.</name><description>&lt;h4>Purpose&lt;/h4>Heterogeneity of the host response in sepsis hampers development of effective treatments. Several immunobiologically distinct subphenotypes (or endotypes) have been identified using data-driven analyses of single-timepoint biomarker data, but their temporal stability remains uncertain due to dynamic biology and statistical limitations.&lt;h4>Methods&lt;/h4>We analyzed data from 345 sepsis patients across two ICU cohorts. 30 immune biomarkers were measured every 8 h for up to 7 days. Latent profile analysis was used to identify classes upon admission and re-classify patients at later timepoints. Temporal robustness was assessed by (1) inter-class transition rates, and (2) intra-class cohesion (regardless of label) using the Rand Index (RI).&lt;h4>Results&lt;/h4>At ICU admission, three immune profiles were identified: profile A (149 patients, 43%) reflected adaptive immune activation (elevated IL-4, IL-5, RANTES, and GM-CSF); profile B (60 patients, 17%) a hyperinflammatory state (high IL-6, IL-8, IL-1Ra, and low protein C); and profile C (136 patients, 39%) broadly attenuated inflammation. By 48 h, the prevalences of A and B declined to 31% and 13%, while C increased to 56%. Inter-class transitions occurred most in patients assigned to A (41% of all 8-hourly transitions), compared to 39% and 22% for B and C. Intra-class cohesion across intervals was poor (median RI 65%, IQR 62-64%), indicating that patients classified together at admission did not remain consistently together.&lt;h4>Conclusion&lt;/h4>Sepsis patients were frequently reclassified across immune profiles over short intervals, with approximately one-third of subgroup peers changing at each timepoint. This instability challenges the clinical utility of biomarker-derived endotypes.</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Jan</publication><modification>2026-06-16T03:10:22.986Z</modification><creation>2026-06-16T03:07:01.126Z</creation></dates><accession>S-EPMC12852201</accession><cross_references><pubmed>41324692</pubmed><doi>10.1007/s00134-025-08218-z</doi></cross_references></HashMap>