The Colorado Heart Failure Acuity Risk Model (CHARM) Score: A Mortality Risk Model for Waitlisted Cardiac Transplant Patients

Importance Although the Organ Procurement and Transplantation network provides structured policies and guidance for waitlisted cardiac transplant patients, the heart transplantation community lacks a mathematical model that can accurately estimate the short-term risk of death associated with being waitlisted. Importantly, the CHARM score provides a risk management and ranking system for patients based on a well-defined and sensitive medical urgency metric. Objective We had three primary objectives in completing this study. First, to increase relevance and applicability, we selected patient attributes that were clinically justified and readily available. Second, we designed and implemented an intuitive, formal system that accurately defined the relative risk of death while being waitlisted at 30-day, 90-day, and 1-year censoring periods. Third, we developed and validated a medical urgency metric that is intuitive, practical, and can be implemented nationally. Design We present a multivariable, prognostic model and risk management strategy for adult waitlisted heart transplant patients (N=1,965) from the Scientific Registry of Transplant Recipients (SRTR) database that were waitlisted from January 1, 2008, to September 2, 2022. To independently validate each model, we randomly split this cohort into a discovery set (N=1,174) and validation set (N=784). Twelve independent patient attributes were selected, and three linear regression formulas were derived to estimate and rank the relative risk of dying while waitlisted. Four independent validation methods were used to measure each model’s performance as a classifier and ranking system. Setting The United States Participants This cohort (N=1,965) consisted of adult heart transplant candidates without missing laboratory data who were placed on the waitlist from January 1, 2008, to September 2, 2022. Patients listed for multi-organ transplantation were excluded. Patients with missing laboratory data were analyzed independently. Exposures The short-term risk of death remaining on the heart transplant waitlist. Main Outcomes and Measures The primary outcome of this study was the design, development, and validation of a formal risk management system for waitlisted heart transplant candidates experiencing end-stage heart failure. We derived three linear regression formulas and calibrated a seven-tiered risk index to accurately rank patients who were more likely to die on the waitlist at 30-day (30D), 90-day (90D), and 1-year (1Y) censoring periods. Four independent validation methods were used to measure each model’s classification and ranking performance. Results Using six interaction terms, we applied the 5-fold cross-validation procedure to the CHARM to discover an area under the ROC curve of 96.4%, 90.4.%, and 78% for the 30D, 90D, and 1Y models, respectively. The mean positive predictive values of the tiered risk system were 99.2% (30D), 94.1% (90D), and 88% (1Y). Risk indices for all three models were >99% correlated to the observed mortality rate across the seven tiers for the 30D, 90D, and 1Y models. Conclusions and Relevance We designed, implemented, and validated an intuitive and formal risk scoring and ranking system which is ideal for prioritizing waitlisted heart failure patients based on a well-defined medical urgency metric. The CHARM score provides extreme sensitivity in predicting short-term mortality outcomes. The CHARM score is extensible to larger patient populations experiencing end-stage heart failure. Question Can pre-operative patient characteristics be used to develop a formal system to accurately estimate, rank, and predict the relative short-term mortality of waitlisted heart transplant patients? Findings Using twelve patient attributes, we derived three linear regression equations to accurately predict the 30-day, 90-day, and 1-year mortality of waitlisted heart transplant patients. We developed and calibrated a seven-tiered risk index for each model that was 99% correlated to the observed mortality rate. Using several independent validation methods, we achieved extreme sensitivity (>98%) in ordinally ranking patient groups who were more likely to survive 30 days on the waitlist. Model performance was measured using the area under the receiver operating characteristic (ROC) curve. Using six interaction terms, the area under the ROC curve was 96.4% (30-day), 90.4% (90-day), and 78% (1-year). Meaning Our models accurately discriminate among patient subgroups who are more likely to die while waitlisted. Because our tiered ranking system is simple, extremely sensitive, and well calibrated, it is ideal for prioritizing waitlisted heart transplant patients based on a well-defined medical urgency score. These models are generalized and therefore extensible to defining medical urgency in larger patient populations experiencing end-stage heart failure. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Trial Not applicable ### Funding Statement No funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Approved by the Colorado Multiple Institutions Review Board I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data are obtained for publich registries.