Development and validation of a nomogram to predict the five-year risk of revascularization for non-culprit lesion progression in STEMI patients after primary PCI.
Front Cardiovasc Med
; 10: 1275710, 2023.
Article
em En
| MEDLINE
| ID: mdl-38094123
ABSTRACT
Background:
Acute ST-segment elevation myocardial infarction (STEMI) patients after primary PCI were readmitted for revascularization due to non-culprit lesion (NCL) progression.Objective:
To develop and validate a nomogram that can accurately predict the likelihood of NCL progression revascularization in STEMI patients following primary PCI.Methods:
The study enrolled 1,612 STEMI patients after primary PCI in our hospital from June 2009 to June 2018. Patients were randomly divided into training and validation sets in a 73 ratio. The independent risk factors were determined by LASSO regression and multivariable logistic regression analysis. Multivariate logistic regression analysis was utilized to develop a nomogram, which was then evaluated for its performance using the concordance statistics, calibration plots, and decision curve analysis (DCA).Results:
The nomogram was composed of five predictors, including age (OR 1.007 95% CI 1.005-1.009, P < 0.001), body mass index (OR 1.476, 95% CI 1.363-1.600, P < 0.001), triglyceride and glucose index (OR 1.050, 95% CI 1.022-1.079, P < 0.001), Killip classification (OR 1.594, 95% CI 1.140-2.229, P = 0.006), and serum creatinine (OR 1.007, 95% CI 1.005-1.009, P < 0.001). Both the training and validation groups accurately predicted the occurrence of NCL progression revascularization (The area under the receiver operating characteristic curve values, 0.901 and 0.857). The calibration plots indicated an excellent agreement between prediction and observation in both sets. Furthermore, the DCA demonstrated that the model exhibited clinical efficacy.Conclusion:
A convenient and accurate nomogram was developed and validated for predicting the occurrence of NCL progression revascularization in STEMI patients after primary PCI.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article