{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T11:33:24Z","timestamp":1789990404576,"version":"4.0.1"},"reference-count":36,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T00:00:00Z","timestamp":1753056000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec014\">\n<jats:title>Background and objective<\/jats:title>\n<jats:p>Despite advances in intensive care, sepsis remains a leading cause of mortality in intensive care unit (ICU) patients, especially middle-aged and elderly individuals. Given the limitations of conventional scoring systems and the interpretability challenges of machine learning models, this study aims to develop and temporally validate a nomogram for predicting 28-day ICU mortality in middle-aged and elderly sepsis patients via the eICU database (2014--2015), providing a clinically practical prediction tool.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec015\">\n<jats:title>Methods<\/jats:title>\n<jats:p>This retrospective study included 13,717 sepsis patients aged \u226545 years. The cohort was temporally divided into training (n\u2009=\u20096,397, 2014) and validation (n\u2009=\u20097,320, 2015) sets. Variable selection was performed via random forest importance ranking and LASSO regression. A nomogram was developed on the basis of multivariable logistic regression analysis.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec016\">\n<jats:title>Results<\/jats:title>\n<jats:p>The 28-day ICU mortality rates were 9.08% and 9.49% in the training and validation cohorts, respectively. The final nomogram incorporated 11 independent predictors: red cell distribution width (RDW), SOFA score, lactate, pH, 24-hour urine output, platelet count, total protein, temperature, heart rate, GCS score, and white blood cell (WBC) count. The model showed good discrimination in both the training (AUC: 0.805) and validation (AUC: 0.756) cohorts. The calibration curves demonstrated good agreement between the predicted and observed probabilities.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec017\">\n<jats:title>Conclusions<\/jats:title>\n<jats:p>We developed and temporally validated a nomogram with good predictive performance for 28-day ICU mortality in middle-aged and elderly sepsis patients, providing a practical tool for risk stratification and clinical decision-making.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0328701","type":"journal-article","created":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T17:22:16Z","timestamp":1753118536000},"page":"e0328701","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["Development and temporal validation of a nomogram for predicting ICU 28-day mortality in middle-aged and elderly sepsis patients: An eICU database 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