Predictive value of admission levels of IL-6 and PCT combined with the peri-treatment change in NLR (ΔNLR) for hospital length of stay in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD)

BACKGROUND: The accurate prediction of hospital length of stay (LOS) for patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD) remains a clinical challenge. While inflammatory biomarkers like Neutrophil-to-Lymphocyte Ratio (NLR), Interleukin-6 (IL-6), and Procalcitonin (PCT) are associated with severity, the predictive value of their peri-treatment dynamic changes, particularly ΔNLR, combined for LOS is not well established. OBJECTIVE: This study aimed to evaluate the predictive value of ΔNLR combined with admission levels of IL-6 and PCT levels for hospital LOS in patients with AECOPD. METHODS: A single-center retrospective cohort study was conducted involving 328 hospitalized AECOPD patients. Patients were divided into short-LOS (≤ 7 days, n = 186) and long-LOS (> 7 days, n = 142) groups based on the average LOS. Data on demographics, clinical characteristics, and laboratory parameters (including NLR, IL-6, and PCT before and after treatment) were collected. The predictive performance of ΔNLR, IL-6, and PCT, both individually and in combination, for long LOS was assessed using Receiver Operating Characteristic (ROC) curve analysis. Multivariate logistic regression was used to identify independent risk factors for long LOS. RESULTS: % pred < 45% (OR = 2.183) as independent risk factors for long LOS (all P < 0.05). CONCLUSIONS: The combination of peri-treatment ΔNLR, IL-6, and PCT is a potent predictor for prolonged hospitalization in AECOPD, being superior to individual biomarkers. This model, utilizing routine clinical data, can facilitate early identification of high-risk patients and optimize resource allocation.