Abstract:

Objective: To explore the related risk factors for the development of viral pneumonia combined with invasive pulmonary mycosis (IPM). Methods: Using a retrospective study method, 105 patients diagnosed with viral pneumonia combined with IPM who were hospitalized at the Affiliated Central Hospital of Shandong First Medical University from January 2021 to October 2023 were selected as the observation group; meanwhile, 105 patients with viral pneumonia who did not have IPM during the same period were selected as the control group in a 1∶1 ratio. The sociodemographic characteristics, clinical manifestations, imaging findings, and laboratory test results of the two groups were collected and analyzed. Logistic regression was used to analyze the influencing factors of IPM in patients with viral pneumonia. Results: In the observation group, 51.4% (54/105), 25.7% (27/105), 43.8% (46/105), 36.2% (38/105) and 23.8% (25/105) of the patients had diabetes, a history of malignant tumor, pleural effusion, bacterial infection, and a positive serum G test, respectively; In the control group, the corresponding figures were 35.2% (37/105), 6.7% (7/105), 19.0% (20/105), 13.3% (14/105), and 2.9% (3/105) respectively, and the differences were statistically significant (χ²=5.604, P=0.018; χ²=14.037, P<0.001; χ²=14.937, P<0.001; χ²=14.722, P<0.001; χ²=19.945, P<0.001). Multivariate logistic regression analysis showed that diabetes (OR(95%CI): 2.452 (1.164-5.163)), history of malignancy (OR(95%CI): 11.688 (3.707-36.847)), pleural effusion (OR(95%CI): 2.484 (1.123-5.494)), bacterial infection (OR(95%CI): 3.341 (1.410-7.920)), and positive serum G test (OR(95%CI): 13.649 (3.267-57.029)) were independent risk factors for the occurrence of IPM in patients with viral pneumonia. Conclusion: For patients diagnosed with viral pneumonia, attention should be paid to the risk of IPM in those with diabetes, a history of malignant tumor, pleural effusion, bacterial infection and a positive serum G test.

Key words: Pneumonia, viral, Lung Diseases, fungal, Comorbidity, Factor analysis, statistical