Previous Models to Identify Predictors
Other investigators have attempted to identify predictors of recurrent MR. Some studies have been limited by performing only univariate analysis to identify specific echocardiographic measurements and clinical features associated with recurrent MR (Table). Others, using traditional statistical modelling, have been able to predict recurrent MR with AUC values of 0.82, sensitivity of 0.86 and specificity of 0.70. [3] but were limited to the inclusion of only 10 clinical and echocardiographic variables (Table). Though the above modelling of recurrent MR have been successful in provided us with mechanistic and clinical insights, they have not been reproducible and sometimes require extremely complicated measurements that are not routinely performed in echocardiography or collected in clinical practice. As such, a tool built on data that is easily and ubiquitously collected and available from all patients becomes important to inform all surgeons on the best surgical plan.