Key result
Novel 7-variable nomogram predicts significant coronary stenosis in low-to-intermediate risk NSTE-ACS patients with ~0.79 AUC.
Why the study?
Patients with NSTE-ACS have significant coronary heterogeneity, and better assessing significant coronary artery stenosis in low-to-intermediate risk patients could identify who benefits from invasive coronary angiography.
Does a 7-variable clinical nomogram accurately predict significant coronary artery stenosis in suspected NSTE-ACS patients with low-to-intermediate risk?
Cross-Sectional (n=469)
No
Does a 7-variable clinical nomogram accurately predict significant coronary artery stenosis in suspected NSTE-ACS patients with low-to-intermediate risk?
Effect estimate: AUC 0.79 (95% CI 0.72-0.86)
A 7-variable clinical nomogram provides good discrimination for predicting significant coronary artery stenosis in low-to-intermediate risk NSTE-ACS patients, potentially aiding in the decision to pursue invasive angiography.
May aid angiography decisions in low-to-intermediate risk NSTE-ACS; leaves open prospective validation before clinical adoption.
Background: Patients with non-ST-segment coronary artery syndrome (NSTE-ACS) have significant heterogeneity in their coronary arteries. A better assessment of significant coronary artery stenosis (SCAS) in low-to-intermediate risk NSTE-ACS patients would help identify who might benefit from invasive coronary angiography (ICA). Our study aimed to develop a multivariable-based model for pretesting SCAS in suspected NSTE-ACS with low-to-intermediate risk. Methods: = 138, patients admitted to hospital since 1 May 2021). The outcome was existing SCAS, including left main artery stenosis ≥50% or any subepicardial coronary artery stenosis ≥70%, all confirmed by invasive coronary angiography. Pretest predictors were selected using Least Absolute Shrinkage and Selection Operator (LASSO) and stepwise logistic regression. Results: = 331, admitted before 1 May 2021) generated the 7 strongest predictors out of 25 candidate variables comprising smoker, diabetes, heart rate, cardiac troponin T, N-terminal pro-B-type natriuretic peptide, high-density lipoprotein cholesterol, and left atrial diameter. This nomogram model showed excellent discrimination ability with an area under the receiver operating characteristic curve (AUC) of 0.83 in the development set and 0.79 in the validation dataset. Good calibration was generally displayed, although it slightly overestimated patients' SCAS risk in the validation group. Decision curve analysis demonstrated the clinical benefit of this model, indicating its value in clinical practice. Furthermore, an optimal cut-off of prediction probability was assigned as 0.61 according to the Youden index. Conclusion: A prediction nomogram consisting of seven readily available clinical parameters was established to pretest the probability of SCAS in suspected NSTE-ACS patients with low-to-intermediate risk, which may serve as a cost-effective risk stratification tool and thus assist in initial decision making.
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Chen et al. (2022) conducted a cross-sectional in Suspected non-ST-segment elevation acute coronary artery syndrome (NSTE-ACS) with low-to-intermediate risk stratification (n=469). SCAS prediction nomogram vs. Updated Diamond-Forrester Model and Duke risk score was evaluated on Area under the receiver operating characteristic curve (AUC) for predicting significant coronary artery stenosis in the validation cohort (AUC 0.79, 95% CI 0.72-0.86). A novel 7-variable nomogram accurately predicted significant coronary artery stenosis in suspected low-to-intermediate risk NSTE-ACS patients, demonstrating an AUC of 0.79 in the validation cohort.
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