Pos1284 a Nomogram for the Prediction of Co-Infection in Mda5 Dermatomyositis: A Rapid Clinical Assessment Model

Background: Patients with anti-melanoma differentiation-associated gene 5-positive dermatomyositis (MDA5 DM) are prone to infections, but there is a lack of rapid methods to assess infection risk, which greatly affects patient prognosis. Objectives: The aim of this study is to establish a rapid prediction model for the risk of co-infection based on the clinical characteristics of patients with MDA5 dermatomyositis. Methods: Retrospective analysis was performed on clinical data from 118 hospitalized patients with MDA5 DM. According to the results of pathogen detection and clinical manifestations, the patients were divided into infected group and non-infected group. LASSO analysis and multivariate logistic regression were used to establish the prediction model of infection in MAD5 DM patients. The resulting model was visualized using a Nomogram. We used methods such as ROC curve analysis, AUC calculation to evaluate the model. Results: Cough, rapidly progressive interstitial lung disease, and elevated hydroxybutyrate dehydrogenase were significantly associated with infection risk in MDA5 DM patients. A prediction model was developed using these three risk factors, achieving an AUC of 0.773 in determining co-infection status. Further analysis based on infection site and pathogen classification demonstrated improved performance of the model in identifying pulmonary infection (AUC: 0.817) and fungal infection (AUC: 0.901). Conclusion: This study aimed to develop a clinical prediction model and visualize it using Nomogram to assess the risk of infection in MDA5 DM. The model provides an effective tool for determining infection status in patients and serves as a reference for formulating clinical medication regimens. REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests: None declared.