Patients with interstitial lung disease (ILD) are prone to acute exacerbation (AE-ILD), with infection being a significant trigger. AE-ILD patients exhibit high mortality rates and poor prognoses, yet domestic research on this population remains limited.

To investigate the clinical predictive value of dynamic changes in peripheral blood lymphocyte count (LYM) for 28-day prognosis in AE-ILD patients with pulmonary infection and to establish a corresponding prognostic prediction model.

A retrospective cohort study included AE-ILD patients with pulmonary infection hospitalized in the Department of Respiratory and Critical Care Medicine at the Affiliated Hospital of Xuzhou Medical University from January 2022 to June 2024. Patients were stratified into survival (n=37) and non-survival (n=65) groups based on 28-day outcomes. Data collected included demographics (sex, age, diagnosis, ILD subtype, comorbidities), disease severity scores (APACHEⅡ, SOFA), and laboratory parameters: white blood cell count (WBC), neutrophil count (NEU), lymphocyte count on days 1, 3, and 5 (d1 LYM, d3 LYM, d5 LYM), hemoglobin (Hb), platelet count (PLT), procalcitonin (PCT), C-reactive protein (CRP), albumin (ALB), total bilirubin (Tbil), lactate dehydrogenase (LDH), Serum creatinine (Scr), activated partial thromboplastin time (APTT), partial pressure of oxygen (PaO₂), partial pressure of carbon dioxide (PaCO₂), fraction of inspired oxygen (FiO₂), PaO₂/FiO₂ ratio (P/F), and lactate (Lac). Intergroup differences were analyzed, and statistically significant variables were identified. Receiver operating characteristic (ROC) curves evaluated prognostic predictive capacity. Univariate and multivariate Cox proportional hazards regression analyses were conducted using R software. Scores were assigned to each indicator based on the hazard ratio (HR). A nomogram prediction model was constructed. After calculating the total score of each indicator, risk stratification was established. The ROC curve of the prediction model was drawn to evaluate its predictive value. The survival curves of 28-day prognosis of patients with different risk stratifications were plotted using R software, and the 28-day survival rates of patients in different groups were compared.

The non-survival group exhibited higher APACHEⅡ scores, SOFA scores, PCT, CRP, and LDH than survival group, but lower d3 LYM, d5 LYM, ALB, and P/F than survival group (P<0.05). The results of the ROC curve showed that the AUCs of d3 LYM, d5 LYM, APACHEⅡ score, and SOFA score in predicting the 28-day prognosis of AE-ILD patients with pulmonary infectionwere 0.723, 0.764, 0.733, and 0.704, respectively. Multivariate Cox regression identified P/F (HR=2.01, 95%CI=1.08-3.75), PCT (HR=2.14, 95%CI=1.02-4.49), Hb (HR=2.34, 95%CI=1.22-4.48), d5 LYM (HR=2.40, 95%CI=1.01-5.70) as independent predictors of 28-day mortality (P<0.05). The nomogram model was constructed based on d5 LYM, P/F, PCT and Hb. The AUC value of this model for predicting 28-day mortality in AE-ILD patients with pulmonary infection was 0.853 (95%CI=0.781-0.925), with the optimal cut-off value being 2. The sensitivity and specificity were 88.24% and 82.35%, respectively. According to the results of the optimal risk stratification, 0-2 was classified as the low-risk group (n=39), and 3-6 was classified as the high-risk group (n=63). There were significant differences on the 28-day survival rates between the two groups of patients (χ²=51.00, P<0.001).

Lymphopenia is associated with increased 28-day mortality in AE-ILD patients with pulmonary infection. The nomogram model incorporating d5 LYM, P/F, PCT, and Hb provides a clinically practical tool for risk stratification and prognostic assessment.