Objective To identify patients at high risk of death during hospitalization after emergency percutaneous coronary intervention(PCI) and to intervene early to reduce mortality.Methods Clinical data of patientswho underwent emergency PCI and were hospitalized at Dongyang People's Hospital from June 1,2013,to December 31,2021,were collected.This included systolic blood pressure,heart rate,and related blood indicators.LASSO regression and stepwise regression analysis were used to determine the factors associated with the risk of death,and a nomogram model was constructed.The accuracy of the model was assessed using the area under the receiver operating characteristic curve(AUC),the calibration was evaluated using the calibration plot(GiViTI plot),and the clinical value of the predictive model was assessed through Decline Curve Analysis(DCA).Additionally,internal validation was performed using the bootstrap method.Results The first detection of B-type natriuretic peptide(BNP),white blood cell count,systolic blood pressure,D-dimer levels,and the presence of respiratory failure at admission were all closely related to the risk of death in patients after emergency PCI(P<0.05).After the model was established,the AUC value was 0.944,the P-value for the calibration plot was 0.700,Brier scaled was 0.029,the calibration slope was 1.000,R2 was 0.500,and the DCA curve was above the two extreme curves.The internal validation results showed a high degree of overlap between the corrected curve and the ideal curve.Conclusion The detection results of B-type natriuretic peptide(BNP),white blood cell count,systolic blood pressure,D-dimer,and the presence of respiratory failure upon admission are significant risk factors for death in patients after emergency PCI during hospitalization.The predictive model constructed based on these indicators has high clinical significance in assessing the risk of death for such patients during hospitalization.
万方数据
维普
