[Risk Factors and Prognosis of Pneumoconiosis Combined With Bacterial Pneumonia: Application of a Random Forest Model].

Objective: To apply a random forest model combined with logistic regression in the understudied area of pneumoconiosis complications, and to investigate the incidence and risk factors of pneumoconiosis complicated by bacterial pneumonia, and the effect of concomitant bacterial pneumonia on the survival and prognosis of patients with pneumoconiosis. Methods: Pneumoconiosis patients admitted to the West China Fourth Hospital, Sichuan University, between January 2018 and April 2022 were enrolled and divided into a group of those with only pneumoconiosis and another group of those with pneumoconiosis complicated by bacterial pneumonia. Univariate analyses, including chi-squared test, t-test, or rank sum test, were conducted to examine the differences between the groups. A random forest model was used to screen the variables, and the risk factors of pneumoconiosis complicated by bacterial pneumonia were identified by stepwise forward logistic regression method. Cox regression was applied to the survival data to assess the effect of concomitant bacterial pneumonia on the survival and prognosis of pneumoconiosis patients. Results: Among the 742 pneumoconiosis patients, 536 cases (72.24%) had concomitant bacterial pneumonia. Among the 55 deaths, 36 cases (65.45%) had concomitant bacterial pneumonia. Univariate analysis showed statistically significant differences in age, duration of disease, lung function, duration of exposure, lung lavage, pulmonary tuberculosis, and emphysema between the two groups ( Conclusion: Pneumoconiosis patients are susceptible to bacterial pneumonia and are influenced by multiple risk factors. Concomitant bacterial pneumonia markedly affects the patient prognosis.