Predictive significance of nomogrammodel based on clinical risk factors and hemodynamics to major adverse cardiovascular events in patients with heart failure
Han Wei
Hao Fang
Lu Lili
Chen Shaobo
Yang Guohong
Abstract：Objective To develop a comprehensivenomogrammodelintegrated mainhemodynamic parameters for predicting the risks of major adverse cardiovascular events(MACE)in patients with heart failure(HF).Methods HF patients received right heart catheterization(RHC,n=661,aged 64.12±14.14 and 67.47％of male)were retrospectively studied,and followed up for the primary endpoint of MACE incidence within 2 y.The demographic information,laboratory tests,transthoracic echocardiography,and RHC hemodynamic parameters were analyzed for selecting key features by using regression analysis ofleast absolute shrinkage and selection operator(LASSO).The independent risk factors were determined and nomogram was established by using multivariate stepwise Cox analysis.The predictive value of the nomogram model was analyzed by using receiver operating characteristic(ROC)curve,Kaplan-Meier curve,calibration diagram and decision curve.Results Among 661 HF patients,the incidence of MACE was 21.48％(n=142,MACE group)within 2 y.The patients without MACE were included into non-MACE group.In MACE group,the patients were older,and percentages of patients with anemia and heart failure with reduced ejection fraction(HFrEF)and systolic blood pressure(SBP)at admission were higher,indexes of end-diastolic interventricular septal thickness(IVST)and left ventricular posterior wall thickness(LVPWT)were higher,levels of low-density lipoprotein-cholesterol(LDL-C)and brain natriuretic peptide(BNP)were higher,estimated glomerular filtration rate(eGFR)was lower,and right atrial pressure(RAP),systolic pulmonary arterial pressure(sPAP),diastolic pulmonary arterial pressure(dPAP),mean pulmonary arterial pressure(mPAP),pulmonary artery wedge pressure(PAWP)and pulmonary vascular resistance(PVR)were higher,and cardiac output(CO)and cardiac index(CI)were lower(P＜0.05).After LASSO screening[ln(λ)=-2.366(λ=0.094)]and multivariate Cox regression analysis,there were 6 variables determined in nomogram model including age,anemia,IVST,LVPWT,RAP and CI.The results of ROC curve analysis showed that nomogram model had higher predictive and discriminative ability(A UC=0.818,95％CI:0.787～0.847).The calibration diagram of nomogram model based on bootstrap method showed good performance.The results of decision curve analysis showed that the net benefit of nomogram model was superior to that of IVST,LVPWT,RAP and CI with higher threshold probability.The patients were divided into 2 groups according to the total nomogram scores:low risk group(n=255,prediction probability＜0.5),and high risk group(n=406,prediction probability ≥0.5).The results of K-M survival curve comparison showed that difference in non-MACE median survival time had statistically significance between 2 groups(log rank=71.221,P＜0.001).Conclusion This study has developed and validated a nomogram model for predicting 2-y incidence of MACE in HF patients.The integration of RHC hemodynamic parameters may has a higher predictability,which is conducive for clinical risk stratification and treatment decisions in HF patients.
Keywords：Heart failureNomogramMajor adverse cardiovascular eventsRight heart catheterization
Publication Date：2024-07-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 850-855 )