Abstract:  Objective To analyze the effect of LncRNA FOXD2-AS1 on the sternal incision problem after heart valve replacement and the other factors,and to build a visual prediction model,evaluate its clinical effectiveness. Methods Retrospective analysis of the data about heart valve replacement in Sanya people’s Hospital and Xinjiang Military Region General Hospital from January 2016 to January 2022,analysis of the factors affecting the incision problem using R software to build a visualized prediction model of nomogram,and using rms and pROC package to evaluate the model. Results Among the 546 cases,39 had incision problem,BMI,LncRNA FOXD2-AS1,age and pulmonary hypertension were independent predictors.The prediction model based on all independent prediction factors have better prediction ability.From the evaluation results of calibration curve,Hosmer-lemeshow test and clinical decision curve,the prediction model also shown more significant advantages. Conclusion The prediction model based on BMI,LncRNA FOXD2-AS1,age and pulmonary hypertension has better discrimination ability,accuracy and clinical applicability,which can provide reference for clinicians in the diagnosis and treatment of incision problem after valve replacement.

Key words: valve replacement, surgical incision, incision problem, predictive model, visualization