INTERMACS profiles and modifiers: Heterogeneity of patient classification and the impact of modifiers on predicting patient outcome

Background Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) patient profiles and modifiers are descriptors of patient illness severity before durable ventricular assist device implantation. It is unknown how individual U.S. institutions and practitioners assign profiles and if modifiers improve on risk discrimination. Methods Respondents (n = 212) to a web-based survey answered questions about the INTERMACS profile assignment process in their institution. For 5 hypothetical clinical scenarios, respondents assigned the best profile. The INTERMACS registry (2009-2014) was queried, and hazard ratio (HR) (95% confidence interval [CI]) for mortality between profiles as well as based on the presence of temporary circulatory support (TCS), frequent flyer (FF), or arrhythmia modifiers was calculated. Results Respondents included 131 (62%) cardiologists, 30 (14%) surgeons, and 51 (24%) physician extenders/coordinators. Institutional INTERMACS profile assignment was variable (63% assigned by cardiologists/surgeons; 10% by research coordinators; 27% by physician extenders). Profile assignments in hypothetical patient scenarios were heterogeneous, especially for contiguous profiles. The 1-year survivals for Profiles 1, 2, and 3 were 77 ± 1.2%, 80 ± 0.7%, and 84 ± 0.7% (p < 0.001). Although Profile 1 patients had worse adjusted survival than Profile 3 patients (p = 0.001), survival for Profile 1 patients vs Profile 2 patients was similar (adjusted HR = 1.01 [95% CI = 0.88-1.12]). The TCS (adjusted HR = 1.1 [95% CI = 0.94-1.2]) and arrhythmia (adjusted HR = 1.1 [95% CI = 0.97-1.2]) modifiers were not predictive of mortality, but the FF modifier was (HR = 1.3 [95% CI = 1.02-1.63]). Conclusions Substantial heterogeneity exists in the process and assignment of INTERMACS profiles. This heterogeneity could affect mortality estimates used for risk stratification. Only the FF modifier appears to improve risk discrimination beyond that of known risk factors. Adding objective descriptors may reduce profile heterogeneity.