Key result
Multifactorial clinical risk model predicts 12-month stent thrombosis with an AUC of ~0.88.
Why the study?
The study aimed to identify predictors of stent thrombosis over 12 months in patients with ACS after PCI by creating a logistic regression model to optimize secondary prevention and personalized treatment.
What clinical and angiographic predictors identify the risk of stent thrombosis in patients with acute coronary syndrome after percutaneous coronary intervention?
Case-Control (n=183)
No
What clinical and angiographic predictors identify the risk of stent thrombosis in patients with acute coronary syndrome after percutaneous coronary intervention?
Effect estimate: AUC 0.876 (95% CI 0.819-0.920)
p-value: p=<0.0001
A simple multivariable logistic regression model using five common clinical and angiographic parameters can accurately predict 12-month stent thrombosis risk in patients with ACS.
AIM: to identify predictors of stent thrombosis in patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI) for 12 months by creating a miathematical logistic regression model to optimize rehabilitation, secondary prevention of ischemic events in the first year after ACS, as well as a personalized approach to treatment. MATERIALS AND METHODS: The analysis used data from the hospital register, which contained information on all PCIs, performed in the Semashko hospital between September 2016 and August 2018 (2378 patients). For this study we selected a sample of 183 ACS patients (146 men and 37 women) after PCI: 25 with definite stent thrombosis confirmed by repeated coronary angiography (CAG) (the main study group), and 158 without developing definite stent thrombosis (the comparison group) according to the observation for 12 months. All patients during hospitalization and 1 year after discharge received standard medical therapy ACS, according to international recommendations. Laboratory tests, electrocardiography (ECG), echocardiography, 24-hour ECG monitoring were performed for in patients. For determining predictors of the development of stent thrombosis we performed a logistic regression analysis. RESULTS: A mathematical model of multifactorial prognostication of stent thrombosis in patients with ACS after PCI was created. The model included the following predictors: Killip class >II; life-threatening paroxysmal tachyarrhythmias (atrial fibrillation and/or ventricular fibrillation) as ACS complication of; left ventricular ejection fraction ≤45%; CA dissection; CAG confirmed CA thrombosis before PCI. CONCLUSION: The proposed model in patients with ACS allows us to estimate the risk of stent thrombosis after PCI, as well as to improve the accuracy of the event prediction. The model is easy to use, can be applied by practicing cardiologists during hospitalization. This model allows us to personalize secondary prevention in the first year after ACS, and thus help to reduce cardiovascular mortality, incidence of recurrent myocardial infarctions, unstable angina, and emergency revascularization.
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Korotaeva et al. (2019) conducted a case-control in Acute Coronary Syndrome (ACS) post-PCI (n=183). Risk factors for stent thrombosis (Killip >II, LVEF ≤45%, coronary dissection, mural thrombus, tachyarrhythmias) vs. Absence of these risk factors was evaluated on Definite stent thrombosis confirmed by repeated coronary angiography within 12 months (AUC 0.876, 95% CI 0.819-0.920, p=<0.0001). A multifactorial logistic regression model incorporating Killip class >II, LVEF ≤45%, mural thrombus, coronary dissection, and tachyarrhythmias accurately predicted 12-month stent thrombosis with an AUC of 0.876.
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