A nomogram to predict the risk of low cardiac output syndrome after heart valve replacement in cardiac valvular disease patients

Background and AimLow cardiac output syndrome (LCOS) is a serious postoperative complication, affecting the prognosis of patients underwent heart valve replacement (HVR). We aim to create a nomogram to predict LCOS after HVR in cardiac valvular disease patients.MethodsWe performed a retrospective review of 500 cardiac valvular disease patients underwent HVR from 2016 to 2020 in our department. Univariate analysis evaluated the associations between clinical/echocardiographic parameters and LCOS. Independent t-test or Mann–Whitney U‐test: for continuous variables. Fisher's exact test or χ2 test: for categorical variables. Variables with a P < 0.1 in the univariate analysis were entered into least absolute shrinkage and selection operator (LASSO) regression to select factors. Then, multivariable logistic regression was performed to develop the predictive model and a nomogram. The discrimination ability, calibration curve analysis and decision curve analysis (DCA) of the nomogram was evaluated in development and validation group.ResultsOf 500 patients, 92 developed postoperative LCOS (18.4%). The nomogram included the following variables: body mass index (BMI), left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS). The nomogram showed favorable calibration and favorite performance for LCOS detection with C-index 0.826 in the development group and 0.783 in validation group. The DCA showed that the novel model was clinically useful.ConclusionsWe created a nomogram of predicting postoperative LCOS in cardiac valvular disease patients received HVR. This nomogram could be an important tool of LCOS risk prediction after HVR to guide the therapeutic strategy in cardiac valvular disease patients.