Contemporary risk model for inhospital major bleeding for patients with acute myocardial infarction: The acute coronary treatment and intervention outcomes network (ACTION) registry®-Get With The Guidelines (GWTG)®.

BACKGROUND: Major bleeding is a frequent complication for patients with acute myocardial infarction (AMI) and is associated with significant morbidity and mortality. OBJECTIVE: To develop a contemporary model for inhospital major bleeding that can both support clinical decision-making and serve as a foundation for assessing hospital quality. METHODS: An inhospital major bleeding model was developed using the Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With the Guidelines (ACTION Registry-GWTG) database. Patients hospitalized with AMI between January 1, 2012 and December 31, 2013 across 657 hospitals were used to create a derivation cohort (n=144,800) and a validation cohort (n=96,684). Multivariable hierarchal logistic regression was used to identify significant predictors of major bleeding. A simplified risk score was created to enable prospective risk stratification for clinical care. RESULTS: The rate of major bleeding in the overall population was 7.53%. There were 8 significant, independent factors associated with major bleeding: presentation after cardiac arrest (OR 2.99 [2.77-3.22]); presentation in cardiogenic shock (OR 2.22 [2.05-2.40]); STEMI (OR 1.72 [1.65-1.80]); presentation in heart failure (OR 1.55 [1.47-1.63]); baseline hemoglobin less than 12 g/dL (1.55 [1.48-1.63]); heart rate (per 10 beat per minute increase) (OR 1.13 [1.12-1.14]); weight (per 10 kilogram decrease) (OR 1.12 [1.11-1.14]); creatinine clearance (per 5-mL decrease) (OR 1.07 [1.07-1.08]). The model discriminated well in the derivation (C-statistic = 0.74) and validation (C-statistic = 0.74) cohorts. In the validation cohort, a risk score for major bleeding corresponded well with observed bleeding: very low risk (2.2%), low risk (5.1%), moderate risk (10.1%), high risk (16.3%), and very high risk (25.2%). CONCLUSION: The new ACTION Registry-GWTG inhospital major bleeding risk model and risk score offer a robust, parsimonious, and contemporary risk-adjustment method to support clinical decision-making and enable hospital quality assessment. Strategies to mitigate risk should be developed and tested as a means to lower costs and improve outcomes in an era of alternative payment models.

Predicting In-Hospital Mortality in Patients With Acute Myocardial Infarction.

BACKGROUND: As a foundation for quality improvement, assessing clinical outcomes across hospitals requires appropriate risk adjustment to account for differences in patient case mix, including presentation after cardiac arrest. OBJECTIVES: The aim of this study was to develop and validate a parsimonious patient-level clinical risk model of in-hospital mortality for contemporary patients with acute myocardial infarction. METHODS: Patient characteristics at the time of presentation in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry-GWTG (Get With the Guidelines) database from January 2012 through December 2013 were used to develop a multivariate hierarchical logistic regression model predicting in-hospital mortality. The population (243,440 patients from 655 hospitals) was divided into a 60% sample for model derivation, with the remaining 40% used for model validation. A simplified risk score was created to enable prospective risk stratification in clinical care. RESULTS: The in-hospital mortality rate was 4.6%. Age, heart rate, systolic blood pressure, presentation after cardiac arrest, presentation in cardiogenic shock, presentation in heart failure, presentation with ST-segment elevation myocardial infarction, creatinine clearance, and troponin ratio were all independently associated with in-hospital mortality. The C statistic was 0.88, with good calibration. The model performed well in subgroups based on age; sex; race; transfer status; and the presence of diabetes mellitus, renal dysfunction, cardiac arrest, cardiogenic shock, and ST-segment elevation myocardial infarction. Observed mortality rates varied substantially across risk groups, ranging from 0.4% in the lowest risk group (score <30) to 49.5% in the highest risk group (score >59). CONCLUSIONS: This parsimonious risk model for in-hospital mortality is a valid instrument for risk adjustment and risk stratification in contemporary patients with acute myocardial infarction.