CHA2DS2-VASc Score as an Independent Predictor of Suboptimal Reperfusion and Short-Term Mortality after Primary PCI in Patients with Acute ST Segment Elevation Myocardial Infarction.
Ammar AshooriHamidreza PourhosseiniSaeed GhodsiMojtaba SalarifarEbrahim NematipourMohammad AlidoostiAli-Mohammad Haji-ZeinaliYones NozariAlireza AmirzadeganHassan AghajaniArash JalaliZahra HosseiniYaser JenabBabak GeraielyNegar OmidiPublished in: Medicina (Kaunas, Lithuania) (2019)
We aimed to demonstrate the clinical utility of CHA2DS2-VASc score in risk assessment of patients with STEMI regarding adverse clinical outcomes particularly no-reflow phenomenon. We designed a retrospective cohort study using the data of Tehran Heart Center registry for acute coronary syndrome. The study included 1331 consecutive patients with STEMI who underwent primary angioplasty. Patients were divided into two groups according to low and high CHA2DS2-VASc score. Angiographic results of reperfusion were inspected to evaluate the association of high CHA2DS2-VASc score and the likelihood of suboptimal TIMI flow. The secondary endpoint of the study was short-term in-hospital mortality of all cause. The present study confirmed that CHA2DS2-VASc model enables us to determine the risk of no-reflow and all-cause in-hospital mortality independently. Odds ratios were 1.59 (1.30⁻2.25) and 1.60 (1.17⁻2.19), respectively. Moreover, BMI, high thrombus grade, and cardiogenic shock were predictors of failed reperfusion (odds were 1.07 (1.01⁻1.35), 1.59 (1.28⁻1.76), and 8.65 (3.76⁻24.46), respectively). We showed that using a cut off value of ≥ two in CHA2DS2-VASc model provides a sensitivity of 69.7% and specificity of 64.4% for discrimination of increased mortality hazards. Area under the curve: 0.72 with 95% CI (0.62⁻0.81). Calculation of CHA2DS2-VASc score applied as a simple risk stratification tool before primary PCI affords great predictive power. Furthermore, incremental values are obtained by using both CHA2DS2-VASc and no-reflow regarding mortality risk assessment.
Keyphrases
- atrial fibrillation
- st segment elevation myocardial infarction
- percutaneous coronary intervention
- acute coronary syndrome
- risk assessment
- acute myocardial infarction
- st elevation myocardial infarction
- antiplatelet therapy
- coronary artery disease
- end stage renal disease
- cardiovascular events
- heart failure
- risk factors
- cerebral ischemia
- body mass index
- acute ischemic stroke
- type diabetes
- chronic kidney disease
- cardiovascular disease
- left ventricular
- deep learning
- heavy metals
- brain injury
- machine learning
- climate change
- human health
- artificial intelligence
- prognostic factors
- data analysis
- patient reported outcomes