Key result
Liver-based clinical model identifies significant coronary stenosis in AMI with ~70% diagnostic accuracy.
Why the study?
Noninvasive detection of high-risk subjects in AMI to predict stenosis severity could reduce the need for intracardiac catheterization and its complications.
Does a prediction model using routine liver parameters predict stenosis diameter severity in patients with acute myocardial infarction?
Observational (n=437)
Does a prediction model using routine liver parameters predict stenosis diameter severity in patients with acute myocardial infarction?
Routine liver parameters are associated with stenosis diameter in AMI, and a noninvasive prediction model may help identify patients who could avoid unnecessary coronary angiography.
Answers are grounded in this paper and cite their sources.
Liver enzymes were associated with stenosis severity in AMI; leaves open their role in noninvasive risk stratification pending prospective validation.
Detection of high-risk subjects in acute myocardial infarction (AMI) by noninvasive means would reduce the need for intracardiac catheterization and associated complications. Liver enzymes are associated with cardiovascular disease risk. A potential predictive value for liver serum markers for the severity of stenosis in AMI was analyzed.Patients with AMI undergoing percutaneous coronary intervention (PCI; n = 437) were retrospectively evaluated. Minimal lumen diameter (MLD) and percent stenosis diameter (SD) were determined from quantitative coronary angiography. Patients were classified according to the severity of stenosis (SD ≥ 50%, n = 357; SD < 50%, n = 80). Routine heart and liver parameters were associated with SD using random forests (RF). A prediction model (M10) was developed based on parameter importance analysis in RF.Age, alkaline phosphatase (AP), aspartate aminotransferase (AST), and MLD differed significantly between SD ≥ 50 and SD < 50. Age, AST, alanine aminotransferase (ALT), and troponin correlated significantly with SD, whereas MLD correlated inversely with SD. M10 (age, BMI, AP, AST, ALT, gamma-glutamyltransferase, creatinine, troponin) reached an AUC of 69.7% (CI 63.8-75.5%, P < 0.0001).Routine liver parameters are associated with SD in AMI. A small set of noninvasively determined parameters can identify SD in AMI, and might avoid unnecessary coronary angiography in patients with low risk. The model can be accessed via http://stenosis.heiderlab.de.
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Baars et al. (2016) conducted an observational in Acute myocardial infarction (n=437). Routine liver parameters and clinical variables (M10 model) was evaluated on Prediction of percent stenosis diameter ≥ 50% (AUC 69.7%, 95% CI 63.8-75.5, p=< 0.0001). A prediction model (M10) based on routine liver and clinical parameters identified stenosis diameter ≥50% in acute myocardial infarction with an AUC of 69.7% (95% CI 63.8-75.5%; P<0.0001).
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