OBJECTIVE  To analyze the pathogenic bacteria and risk factors of pulmonary infections in patients with interstitial lung disease （ILD） and to construct a nomogram risk prediction model based on multifactorial indicators.

METHODS  A total of 145 ILD patients hospitalized in the department of respiratory and critical care medicine at Hebei General Hospital from Jan. 2022 to Aug. 2025 were enrolled, including 67 who developed pulmonary infections. The results of metagenomic next-generation sequencing （mNGS） of bronchoalveolar lavage fluid （BALF） and clinical data were collected. Logistic regression analysis was applied to identify the risk factors for pulmonary infections in ILD patients. Based on these factors, a nomogram prediction model was constructed. The discriminative ability was evaluated with the receiver operating characteristic （ROC） curve, the predictive consistency was tested with the calibration curve, and the clinical practicality and net benefit of the model were evaluated through decision curve analysis （DCA）.

RESULTS  A total of 97 pathogenic bacterial strains were isolated from the infection group, including gram-negative bacteria （n=40）, gram-positive bacteria （n=8） and fungi （n=31）. Multivariate analysis revealed that albumin （ALB） levels （OR=0.759）, recent use of glucocorticoids/immunosuppressants （GCs/IS） （OR=3.662）, honeycombing （HC） on CT （OR=4.485）, Decreased diffusing capacity of the lungs for carbon monoxide （DLCO%） （OR=0.932） and elevated pulmonary artery systolic pressure （PASP） （OR=1.112） were risk factors for pulmonary infections in ILD patients （all P＜0.05）. The nomogram model based on the aforementioned factors demonstrated robust predictive performance, with an area under the ROC curve of 0.911. The calibration curve indicated good consistency between between the predicted and observed probabilities. DCA suggested that the model had excellent clinical utility.

CONCLUSIONS  The predominant pathogens in ILD patients with pulmonary infections are gram-negative bacteria and fungi. Hypoalbuminemia, recent use of hormones and immunosuppressive therapy and alterations in pulmonary structure and hemodynamics are identified as the key risk factors.