To analyze the independent influencing factors for short-term prognosis in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and to construct a nomogram prediction model based on the neutrophil-to-lymphocyte ratio/albumin ratio (NLR/ALB).

A total of 220 patients with AECOPD admitted to our hospital from July 2023 to January 2026 were enrolled as the research subjects, and they were divided into a critical illness group and a stable condition group according to their short-term prognosis outcomes. The clinical data of the patients were collected, univariate and multivariate Logistic regression analyses were adopted to screen out the independent influencing factors for short-term prognosis, and a nomogram prediction model was constructed by using R software. The predictive performance and clinical utility of the model were evaluated via the receiver operating characteristic (ROC) curve, calibration curve and decision curve.

The observation group had a mean age of (69.47±8.25) years, Charlson Comorbidity Index (CCI) score of (3.21±1.02), procalcitonin (PCT) of (0.82±0.31) μg/L, red blood cell distribution width (RDW) of (14.82±2.45)%, and NLR/ALB of (3.62±1.25), compared with (65.29±9.76) years, (2.54±1.00), (0.62±0.33) μg/L, (13.19±2.32)%, and (2.76±1.02) in the control group, with statistically significant differences (P<0.05). Multivariate logistic regression analysis showed that age (OR=1.083, 95%CI: 1.029~1.141, P=0.002), CCI score (OR=1.613, 95%CI: 1.131~2.300, P=0.008), PCT(OR=3.819, 95%CI: 1.237~11.792, P=0.020), RDW (OR=1.318, 95%CI: 1.136~1.531, P<0.001), and NLR/ALB (OR=1.940, 95%CI: 1.401~2.687, P<0.001) were independent influencing factors for short-term prognosis in AECOPD patients. The constructed nomogram model achieved an AUC of 0.838(95%CI: 0.780~0.896), with a sensitivity of 72.31% and a specificity of 83.23%. The calibration curve showed good agreement with the ideal diagonal line (Hosmer-Lemeshow test: χ²=3.280, P=0.772). Within the threshold probability range of 5% to 89%, the model demonstrated a high clinical net benefit.

Age, CCI score, PCT, RDW, and NLR/ALB are independent influencing factors for short-term prognosis in AECOPD patients. The nomogram prediction model constructed in this study has good predictive performance and clinical utility, providing a reference for early identification of high-risk patients with poor short-term prognosis in AECOPD and for optimizing clinical intervention strategies.