Objective To investigate the risk factors for secondary pulmonary infarction (PI) in elderly patients with acute pulmonary embolism (PE) and to construct a risk prediction model based on these factors.

Methods This study enrolled 147 elderly PE patients hospitalized at our institution from July 2018 to September 2022. Patients were divided into a secondary PI group (n = 44) and a non-secondary PI group (n = 103) based on the occurrence of secondary PI. Stepwise regression analysis was used to identify risk factors for secondary PI, and a risk prediction model was constructed using R software. The model was validated with 63 elderly PE patients admitted between September 2022 and December 2023. Results Stepwise regression analysis identified alcohol consumption (odds ratio OR = 8.586, 95% CI: 2.430-30.361), chronic bronchitis (OR = 9.831, 95% CI: 2.701-35.782), emphysema (OR = 6.990, 95% CI: 1.987-24.582), coronary heart disease (OR = 15.603, 95% CI: 3.470-41.144), diabetes (OR = 11.955, 95% CI: 1.097-130.860), and D-dimer (OR = 1.021, 95% CI: 1.002-1.037) as independent risk factors for secondary PI in elderly PE patients (P < 0.05). Receiver operating characteristic (ROC) curve analysis showed an area under the curve (AUC) of 0.936 (95% CI: 0.901–0.976) for the modeling group and 0.917 (95% CI: 0.852–0.990) for the validation group. Calibration curve results indicated that the model demonstrated high accuracy in both the modeling and validation cohorts. Clinical decision curve analysis showed the model has high clinical utility.

Conclusion  Elderly PE patients with alcohol consumption, chronic bronchitis, coronary heart disease, emphysema, diabetes, or elevated D-dimer levels have a higher risk of secondary PI. The predictive model demonstrates high discriminatory power and accuracy, aiding clinical assessment of secondary PI in PE patients.