{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T05:26:56Z","timestamp":1764912416005,"version":"3.46.0"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"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. Med."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>While glucocorticoids remain cornerstone therapy for severe COVID-19, substantial heterogeneity persists in clinical outcomes. This single-center retrospective study sought to establish a predictive model integrating inflammatory biomarkers to guide risk stratification and personalized management.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analysed 151 adults with WHO-defined severe COVID-19 receiving glucocorticoid therapy (December 2022\u2013August 2023). Treatment non-response was defined as mortality during hospitalization, mechanical ventilation escalation, or persistent organ dysfunction. LASSO and logistic regression analyses identified predictors, with optimal biomarker thresholds determined using ROC curves. A nomogram was constructed and validated via split-sample testing (7:3 ratio) and 10-fold cross-validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Ferritin &amp;gt;970.7\u2009ng\/mL and IL-10\u2009&amp;gt;\u20094.79\u2009pg.\/mL predicted glucocorticoid resistance (AUC: training set 0.779, test set 0.780). The nomogram incorporated diabetes, ferritin, and IL-10, demonstrating robust calibration (Hosmer-Lemeshow\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.84; Brier score\u2009=\u20090.182) and discrimination (sensitivity\u2009=\u200971.4%, specificity\u2009=\u200970.0%). Diabetic patients exhibited heightened inflammatory responses and poorer outcomes, exacerbated by glucocorticoid-induced hyperglycaemia.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This nomogram shows promising predictive performance and provides a potentially implementable framework for risk stratification and personalized management, which warrants prospective validation in larger, multi-center cohorts.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2025.1635545","type":"journal-article","created":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T05:13:49Z","timestamp":1764911629000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Development of a laboratory-based nomogram for predicting clinical outcomes in patients with severe COVID-19 undergoing glucocorticoid therapy"],"prefix":"10.3389","volume":"12","author":[{"given":"Langqing","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunyang","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Jie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhifang","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,12,5]]},"reference":[{"key":"ref1","year":""},{"key":"ref2","volume-title":"COVID-19 Clinical Outcome 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