Combined Risk Stratification With Patient Characteristics and Biomarkers in Patients Treated With the Impella for Cardiogenic Shock - Yuichi Saito; Yuki Shiko; Kazuya Tateishi; Koichi Toda; Goro Matsumiya; Yoshio Kobayashi (Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease)
Background In patients with cardiogenic shock (CS), a percutaneous microaxial ventricular assist device (Impella, Abiomed, Danvers, MA) is a choice for temporary mechanical circulatory support. Given the high morbidity and mortality in this patient population, early risk stratification is relevant when making treatment decisions. Methods Using nationwide registry data between February 2020 and December 2022 in Japan, we included a total of 4122 patients with cardiogenic shock treated with the Impella devices. Using logistic regression analysis, we incorporated patient characteristics and biomarkers to develop a risk‐stratifying model for in‐hospital mortality. The model was also tested if applicable to composite outcomes of in‐hospital death and major complications. Results Of the 4122 patients with cardiogenic shock, the Impella was indicated for acute myocardial infarction in 2575 (62.5%). Multivariable analysis identified 4 patient characteristics (age, body mass index, out‐of‐hospital cardiac arrest, and blood pressure) and 6 biomarkers (lactate, lactate dehydrogenase, creatinine, total bilirubin, albumin, and creatinine kinase) with cutoff values as factors significantly associated with in‐hospital mortality. We developed a risk‐stratifying model using the 10 variables, which was predictive of in‐hospital death (area under the curve, 0.711; P<0.001). Adding biomarkers to patient characteristics significantly improved the diagnostic accuracy (area under the curve, from 0.649 to 0.711; P<0.001). This risk score was also predictive of death and major complications (area under the curve, 0.680; P<0.001). Conclusions In patients with cardiogenic shock treated with the Impella devices, our risk‐stratifying system, consisting of 4 patient characteristics and 6 biomarkers, strongly correlated with in‐hospital mortality, potentially facilitating clinical decision‐making.