[Risk factors and construction of predictive model for severe viral pneumonia complicated with pulmonary invasive mold infection].

OBJECTIVE: To analyze the risk factors for pulmonary invasive mold infection (PIMI) in patients with severe viral pneumonia (SVP), construct a predictive model, and evaluate its efficacy.

METHODS: A retrospective observational study was conducted, and patients with SVP admitted to the respiratory intensive care unit (RICU) of the First Affiliated Hospital of Xinjiang Medical University from August 2022 to October 2024 were enrolled. Patients were divided into a training set and a validation set at a ratio of 7 : 3 using the random number table method. Then, SVP patients in the training set were divided into a non-PIMI group and a PIMI group based on whether PIMI occurred or not. The data of patients in each group were collected and compared, including gender, age, underlying diseases, and British Thoracic Society's modified pneumonia score (CURB-65), Acute Physiology And Chronic Health Evaluation II (APACHE II) score, chest CT findings, oxygenation index (PaO2/FiO2), and laboratory indicators at RICU admission. Variables with statistically significant differences in univariate analysis were included in multivariate Logistic regression analysis to identify the risk factors for PIMI and construct a risk prediction model. The effectiveness and application value of the prediction model were evaluated using the receiver operator characteristic curve (ROC curve), calibration curve, and decision curve analysis (DCA). The model was further validated in the validation set.

RESULTS: A total of 201 patients with SVP were enrolled. There were 140 patients in the training set (97 cases in the non-PIMI group and 43 cases in the PIMI group) and 61 patients in the validation set. Univariate analysis showed that in the training set, there were statistically significant differences between the PIMI group and the non-PIMI group in terms of diabetes mellitus, chronic lung disease, solid organ tumor, CURB-65 score, pulmonary consolidation, pleural and pericardial effusion, PaO2/FiO2 at RICU admission, C-reactive protein (CRP) >50 mg/L, concurrent pulmonary bacterial infection, septic shock, and duration of broad-spectrum antimicrobial use≥14 days (all P<0.05). Multivariate Logistic regression analysis revealed that diabetes mellitus, chronic lung disease, solid organ tumor, duration of broad-spectrum antimicrobial use≥14 days, and pleural and pericardial effusion were independent risk factors for PIMI in SVP patients [all odds ratio (OR) >1, all P<0.05]. A risk prediction model was constructed using the above five indicators. ROC curve showed that the area under the ROC curve (AUC) of the prediction model in the training set and validation set were 0.849 [95% confidence interval (95%CI) was 0.785-0.914] and 0.773 (95%CI was 0.658-0.889), respectively. The calibration curves of both the training set and the validation set indicated good fitting performance of the model, and the DCA curves suggested that the model had good clinical application value.

CONCLUSIONS: Diabetes mellitus, chronic lung disease, solid organ tumor, duration of broad-spectrum antimicrobial use≥14 days, and pleural and pericardial effusion are risk factors for PIMI in patients with SVP. The constructed predictive model based on the above factors has good predictive value and clinical utility for the occurrence of PIMI.