{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T01:49:57Z","timestamp":1777945797664,"version":"3.51.4"},"reference-count":46,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Beijing Hospitals Authority\u2019s Ascent Plan","award":["DFL20240302"],"award-info":[{"award-number":["DFL20240302"]}]},{"name":"Beijing Municipal Science & Technology Commission, Administrative Commission of Zhongguancun Science Park","award":["No. Z251100006025022"],"award-info":[{"award-number":["No. Z251100006025022"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["INQUIRY"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:p>Current risk stratification for Post-cardiac Arrest Syndrome (PCAS) relies mainly on static admission variables and may fail to capture the dynamic systemic evolution. This study aimed to identify trajectory-defined thrombo-inflammatory phenotypes in PCAS using longitudinal trajectories of platelets, white blood cells (WBC), hemoglobin, and body temperature, and to evaluate their association with 30-day ICU mortality. We conducted a multicenter retrospective cohort study using the MIMIC-IV, MIMIC-III, and eICU-CRD databases, including adult patients with ICU stays of 2-90 days after cardiac arrest. A Multivariate Process Joint Latent Class Mixed Model (mJLCMM) identified latent classes from 30-day biomarker trajectories. The primary outcome was 30-day ICU mortality. Associations were evaluated using Inverse Probability Weighting (IPW) and Doubly Robust Estimation (DRE). Prognostic accuracy was compared against SOFA and OASIS scores using time-dependent Receiver Operating Characteristic (ROC) analysis. A total of 5,099 patients were included. Two phenotypes were identified: Class 1 (\u201cRapid Decline and Recovery\u201d) and Class 2 (\u201cMild Decline and Recovery\u201d). Class 1 was associated with higher 30-day ICU mortality (eICU: 46.7%; MIMIC: 24.6%). In doubly robust analyses, the class 2 remained associated with lower ICU mortality in both cohorts, with odds ratios (ORs) of 0.82 (95% CI, 0.72-0.96) in eICU and 0.74 (95% CI, 0.55-0.95) in MIMIC. By Day 30, the trajectory model outperformed SOFA and OASIS, with an AUC of 0.74 versus 0.54 and 0.59, respectively. This trajectory-based classification showed superior prognostic performance for 30-day ICU mortality and highlights the potential value of dynamic monitoring in post-cardiac arrest management.<\/jats:p>","DOI":"10.1177\/00469580261448815","type":"journal-article","created":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T09:31:22Z","timestamp":1777541482000},"page":"1-1","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Trajectory-Defined Thrombo-Inflammatory Phenotypes Predict 30-Day ICU Mortality in Post-cardiac Arrest Syndrome: A Multicenter Retrospective Longitudinal Cohort Study"],"prefix":"10.1177","volume":"63","author":[{"given":"Guyu","family":"Zhang","sequence":"first","affiliation":[{"name":"Beijing Chaoyang Hospital, Capital Medical University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Le","family":"An","sequence":"additional","affiliation":[{"name":"Beijing Chaoyang Hospital, Capital Medical University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ChenChen","family":"Hang","sequence":"additional","affiliation":[{"name":"Beijing Chaoyang Hospital, Capital Medical University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"XingSheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing Chaoyang Hospital, Capital Medical University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Shao","sequence":"additional","affiliation":[{"name":"Beijing Chaoyang Hospital, Capital Medical University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ZhenYu","family":"Shan","sequence":"additional","affiliation":[{"name":"Beijing Chaoyang Hospital, Capital Medical 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