Key result
A prognostic nomogram based on nine clinical variables accurately predicted the 3-year risk of major adverse cardiovascular events in patients with acute coronary syndrome after percutaneous coronary intervention, achieving an AUC of 0.75 in the validation cohort.
Why the study?
The study aimed to establish and authenticate a clinical prognostic nomogram for predicting long-term MACEs among high-risk patients undergoing PCI in county-level health services.
Does a 9-variable clinical prognostic nomogram accurately predict 3-year MACEs in ACS patients undergoing PCI at county-level hospitals?
Case-Control (n=1,581)
Yes
Does a 9-variable clinical prognostic nomogram accurately predict 3-year MACEs in ACS patients undergoing PCI at county-level hospitals?
Effect estimate: AUC 0.75 (95% CI 0.71-0.78)
A 9-variable prognostic nomogram demonstrated good discrimination and clinical utility for predicting 3-year MACEs in ACS patients undergoing PCI at county-level hospitals.
May support MACE risk stratification after county-level PCI; leaves open prospective validation before clinical adoption.
Objective We aimed to establish and authenticate a clinical prognostic nomogram for predicting long-term Major Adverse Cardiovascular Events (MACEs) among high-risk patients who have undergone Percutaneous Coronary Intervention (PCI) in county-level health service. Methods This prospective study included Acute Coronary Syndrome (ACS) patients treated with PCI at six county-level hospitals between September 2018 and August 2019, selected from both the original and external validation cohorts. Least Absolute Shrinkage and Selection Operator (LASSO) regression techniques and logistic regression were used to assess potential risk factors and construct a risk predictive nomogram. Additionally, the potential non-linear relationships between continuous variables were tested using Restricted Cubic Splines (RCS). The performance of the nomogram was evaluated based on the Receiver Operating Characteristic (ROC) curve analysis, Calibration Curve, Decision Curve Analysis (DCA), and Clinical Impact Curve (CIC). Results The original and external validation cohorts comprised 520 and 1061 patients, respectively. The final nomogram was developed using nine clinical variables: Age, Killip functional classification III-IV, Hypertension, Hyperhomocysteinemia, Heart failure, Number of stents, Multivessel disease, Low-density Lipoprotein Cholesterol, and Left Ventricular Ejection Fraction. The AUC of the nomogram was 0.79 and 0.75 in the original and validation cohorts, respectively. The DCA and CIC validated the clinical value of the constructed prognostic nomogram. Conclusion Herein, we developed and validated a prognostic nomogram for predicting the probability of 3-year MACEs in ACS patients who underwent PCI at county-level hospitals. The nomogram could provide a precise risk assessment for secondary prevention in ACS patients receiving PCI.
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Lü et al. (2023) conducted a case-control in Acute Coronary Syndrome (ACS) post-PCI (n=1,581). Prognostic nomogram (9 clinical variables) was evaluated on Major Adverse Cardiovascular Events (MACEs) at 3 years (AUC 0.75, 95% CI 0.71-0.78). A prognostic nomogram based on nine clinical variables accurately predicted the 3-year risk of major adverse cardiovascular events in patients with acute coronary syndrome after percutaneous coronary intervention, achieving an AUC of 0.75 in the validation cohort.
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