Cardiogenic shock (CS) is the most severe form of acute heart failure.1 It can be described as a state of ineffective cardiac output, which results in clinical and biochemical manifestations of inadequate tissue perfusion.1, 2 CS is a leading cause of mortality after myocardial infarction (MI) and complicates up to 10% of cases of acute myocardial infarction (AMI).3 It is more common in patients with ST-elevation myocardial infarctions (STEMI) than in those with non-ST-elevation myocardial infarctions (NSTEMI).3, 4 Despite advances in treatment options, CS mortality remains high at approximately 35 to 50 percent.1, 3, 5
Several risk scores that help predict short-term mortality have been established. The ‘SHould we emergently revascularize Occluded coronaries for Cardiogenic shocK?” (SHOCK) trial score had a large registry (n = 1217) and emphasized the importance of early coronary revascularization in MI patients with shock.6 The SHOCK measure employs a two-stage process to identify variables that can predict short-term mortality, including age, shock on admission, evidence of end-organ hypoperfusion, anoxic brain damage, systolic blood pressure, prior coronary artery bypass grafting (CABG), noninferior MI, creatinine level, stroke work, and left ventricular ejection fraction (LVEF) of less than 28%.6 The model had an area under the curve (AUC) of 0.74 but has not been validated using an independent data set.6
The Intra-aortic Balloon Pump in Cardiogenic Shock II (IABP-SHOCK II) trial is the largest randomized trial to date (n = 480); however, only patients with MI were included.7 Similar to the SHOCK trial, age and creatinine were included in the risk score, among other factors, such as prior stroke, glucose level, blood lactate level, and thrombolysis in myocardial infarction (TIMI) flow grading.7 The model had a fair predictive performance (AUC = 0.79).7 Furthermore, internal validation using data from the IABP-SHOCK II registry patients (AUC = 0.79) and external validation based on the CardShock population (AUC = 0.73) were performed.7
The CardShock study is by far the largest prospective, observational study (n = 219) to include patients with all etiologies of CS.8 Age, previous MI or CABG, reduced LVEF, high lactate level, and confusion at presentation (presence of systemic hypoperfusion) were also used as predictors of mortality, as were acute coronary syndrome (ACS) etiology and estimated glomerular filtration rate (eGFR).8 This model had a good predictive power (AUC = 0.85) and the IABP-SHOCK II trial patients were used for external validation (AUC = 0.71).8
A comparative study of these risk scores revealed modest prognostic accuracy, which indicated the need for novel methods of risk prediction.9 Furthermore, these scores were largely based on Western populations, and their applicability to different populations had not been tested.9 Zhang et al. developed a predictive model of the risk of developing CS in Chinese patients; however, the primary outcome was not mortality and the population was limited to patients with AMI, instead of those with the entire spectrum of related etiologies.10 The predictive factors included age, sex, body mass index (BMI), Killip class, mean arterial pressure (MAP), heart rate, previous coronary disease, the outcome of thrombolytic therapy, and MI location.10
The patient characteristics included in the aforementioned models were mostly from the medical history and biochemistry results. The variance in these risk factors illustrates the heterogeneity of CS presentations. Furthermore, a patient’s clinical course is often nonlinear, and thus factors throughout their hospitalization should be explored.11 Therefore, this study aimed to develop a risk-predictive model of in-hospital mortality for patients with CS based on their medical history, examination results, and interventions throughout hospitalization to aid physicians in their clinical management and to improve patients’ prognoses.