Key result
A five-factor nomogram predicts in-hospital malignant ventricular arrhythmia after STEMI PCI with ~0.80 accuracy.
Why the study?
Malignant ventricular arrhythmia seriously affects hemodynamic changes, prompting the development and validation of a nomogram to predict in-hospital risk in STEMI patients after emergency PCI.
Does a nomogram incorporating clinical and inflammatory markers predict in-hospital malignant ventricular arrhythmia in patients with STEMI after emergency PCI?
Observational
Does a nomogram incorporating clinical and inflammatory markers predict in-hospital malignant ventricular arrhythmia in patients with STEMI after emergency PCI?
Effect estimate: C-index 0.803 (95% CI 0.738-0.868)
A novel nomogram incorporating Killip class, CK-MB, serum potassium, NLR, and monocytes provides good discrimination for predicting in-hospital malignant ventricular arrhythmias in STEMI patients post-PCI.
Killip class enables early MVA risk stratification after STEMI PCI; extends nomogram validation for post-procedural decision support.
Background: Malignant ventricular arrhythmia (MVA) can seriously affect the hemodynamic changes of the body. In this study, we developed and validated a nomogram to predict the in-hospital MVA risk in patients with STEMI after emergency PCI. Methods: The multivariable logistic regression analysis included variables with a P< 0.05 in the univariate logistic regression analysis and investigated the independent predictors affecting in-hospital MVA after PCI in patients with STEMI in the training cohort. The construction of a nomogram model used independent predictors to predict the risk of in-hospital MVA, and C-index, Hosmer-Lemeshow (HL) test, calibration curves, decision curve analysis (DCA), and receiver operating characteristic (ROC) were used to validate the nomogram. Results: Killip class [OR=5.034 (95% CI: 1.596– 15.809), P=0.005], CK-MB [OR=1.002 (95% CI: 1.001– 1.004), P=0.022], serum potassium [OR=0.618 (95% CI: 0.406– 0.918), P=0.020], NLR [OR=1.073 (95% CI: 1.034– 1.115), P< 0.001], and monocyte [OR=1.974 (95% CI: 1.376– 2.925), P< 0.001] were the independent predictors of in-hospital MVA after PCI in patients with STEMI. A nomogram including the 5 independent predictors was developed to predict the risk of in-hospital MVA. The C-index, equivalent to the area under the ROC curve (AUC), was 0.803 (95% confidence interval [CI]: 0.738– 0.868) in the training cohort, and 0.801 (95% CI:0.692– 0.911) in the validation cohort, showing that the nomogram had a good discrimination. The HL test ( χ 2 =8.439, P=0.392 in the training cohort; χ 2 =9.730, P=0.285 in the validation cohort) revealed a good calibration. The DCA suggested an obvious clinical net benefit. Conclusion: Killip class, CK-MB, serum potassium, NLR, and monocyte were independent factors for in-hospital MVA after PCI in patients with STEMI. The nomogram model constructed based on the above factors to predict the risk of in-hospital MVA had satisfactory discrimination, calibration, and clinical effectiveness, and was an excellent tool for early prediction of the risk of in-hospital MVA after PCI in patients with STEMI.
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Wang et al. (2023) conducted an observational in Acute ST-Segment Elevation Myocardial Infarction. Nomogram model (Killip class, CK-MB, serum potassium, NLR, and monocytes) was evaluated on In-hospital malignant ventricular arrhythmia (MVA) (C-index 0.803, 95% CI 0.738-0.868). A nomogram incorporating Killip class, CK-MB, serum potassium, NLR, and monocytes accurately predicted in-hospital malignant ventricular arrhythmia in STEMI patients after PCI (C-index 0.803).
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