Abstract
BACKGROUND: Understanding the dynamic changes in immune indicators during sepsis and their predictive value for Acute respiratory distress syndrome (ARDS) is crucial for improving patient outcomes. METHODS: This single-center, observational retrospective study was conducted at Lishui Central Hospital, Zhejiang Province. Patients diagnosed with Sepsis-3 were categorized into non-ARDS and ARDS groups based on ARDS development. Data collection included demographics, clinical data, and immune parameters. Immune parameters were collected on days 1, 3, and 7 post-admission. Multivariate logistic regression analysis identified independent risk factors for ARDS, and a nomogram model was constructed. The predictive ability of the model was evaluated using ROC curves. RESULTS: Multivariate analysis identified key factors for the nomogram, including CD4, CD8, Treg, lymphocyte, IgG, and IgA levels on Days 3 and 7. On Day 3, CD8 (P < 0.001), Tregs (P = 0.021), IgG (P < 0.001), and IgA (P < 0.001) showed significant negative correlations with ARDS development. On Day 7, CD4 (P < 0.001), CD8 (P < 0.001), lymphocyte count (P < 0.001), and IgA (P < 0.001) similarly demonstrated significant negative correlations with ARDS risk. The nomogram model had an AUC of 0.998 (95% CI: 0.997-0.999), indicating high predictive ability. CONCLUSION: Early dynamic changes in immune indicators, including CD8, CD4, Treg, IgA, IgG, and Lymphocyte, predict ARDS development in ICU sepsis patients.