LAUSR

BACKGROUND Heart transplant allocation in the United States is made on the basis of coarse tiers, defined by mechanical circulatory devices and therapy for advanced heart failure, updated infrequently as a patient's condition deteriorates. Thus, many patients die awaiting heart transplantation. What is needed is a tool that continuously updates risk of mortality as a patient's condition changes to inform clinical decision making. OBJECTIVES This study sought to develop a decision aid that aggregates adverse events and measures of end-organ function into a continuously updated waitlist mortality estimate. METHODS From 2008 to 2013, 414 patients were listed for heart transplantation at Cleveland Clinic, Cleveland, Ohio. The endpoint was waitlist death. Pre-listing patient characteristics and events and laboratory results during listing were analyzed. At each event or measurement change, mortality was recomputed from the resulting model. RESULTS There were 77 waitlist deaths, with 1- and 4-year survival of 85% and 57%, respectively. When time-varying events and measurements were incorporated into a mortality model, pre-listing patient characteristics became nonsignificant. Neurological events (hazard ratio [HR]: 13.5; 95% confidence interval [CI]: 7.63 to 23.8), new requirement for dialysis (HR: 3.67; 95% CI: 1.88 to 7.14), more respiratory complications (HR: 1.79 per episode; 95% CI: 1.23 to 2.59), and higher serum bilirubin (p < 0.0001) and creatinine (p < 0.0001) yielded continuously updated estimates of patient-specific mortality across the waitlist period. CONCLUSIONS Mortality risk for patients with advanced heart failure who are listed for transplantation is related to adverse events and end-organ dysfunction that change over time. A continuously updated mortality estimate, combined with clinical evaluation, may inform status changes that could reduce mortality on the heart transplant waiting list.