{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T06:19:46Z","timestamp":1773641986308,"version":"3.50.1"},"reference-count":33,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>The present study is an observational descriptive follow-up investigation designed to characterize the profile of serum immune mediators in COVID-19 patients further categorized according to disease outcome.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 92 COVID-19 patients were enrolled in a timeline kinetics, starting at hospital admission (Day\u00a00) throughout consecutive timepoint intervals (Day 3\u20137, Day 8\u201314 and Day 15\u201340). Immune mediators (chemokines, cytokines and growth factors) were quantified by a high-throughput multiplex assay and compared with a pre-pandemic healthy control group (HC).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Data demonstrated that COVID-19 exhibited a classical immune mediator storm, with prominent increase of chemokines and pro-inflammatory cytokines. Longitudinal follow-up revealed that the \u201cdeath\u201d outcome was associated with a persistent increase of immune mediators across all timepoints, with higher imbalance at Day 8\u201314. Conversely, the \u201cdischarge\u201d outcome evolved with a balanced temporal profile with progressive waning of pro-inflammatory cytokines. Integrative network architectures uncovered that the \u201cdeath\u201d outcome exhibited a selective high-density chemokine cluster, contrasting with the balanced pattern described for \u201cdischarge\u201d subgroups. A set of serum immune mediators (CXCL8, CCL2, CXCL10, IL-6, and IFN-\u03b3) emerged as relevant predictors of disease outcome (AUC \u2265 0.8). Decision tree stepwise algorithms pointed out the hierarchical power (accuracy = 83%) of IL-6, CCL2, and CXCL8 to sort out patients according to disease outcome.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Overall, these findings support clinical applicability of measuring serum immune mediators as complementary prognostic biomarkers for early classification and prediction of disease outcome in COVID-19 patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1765997","type":"journal-article","created":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T05:22:34Z","timestamp":1773638554000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploring the timeline and network interplay of immune mediators in COVID-19 patients according to disease 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