Lisa C. Lohmueller

Low Accuracy of the HeartMate Risk Score for Predicting Mortality using the INTERMACS Registry Data.

Selection is a key determinant of clinical outcomes after left ventricular assist device (LVAD) placement in patients with end-stage heart failure. The HeartMate II risk score (HMRS) has been proposed to facilitate risk stratification and patient selection for continuous flow pumps. This study retrospectively assessed the performance of HMRS in predicting 90 day and 1 year mortality in patients within the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS). A total of 11,523 INTERMACS patients who received a continuous flow LVAD between 2010 and 2015 were retrospectively categorized per their calculated HMRS to predict their 90 day and 1 year risk of mortality. The performance of the score was evaluated by the area under curve (AUC) of the receiver operator characteristic. We also performed multiple regression analysis using variables from the HMRS calculation on the INTERMACS data. The HMRS model showed moderate discrimination for both 90 day and 1 year mortality prediction with AUCs of 61% and 59%, respectively. The predictions had similar accuracy irrespective of whether the pump was axial or centrifugal flow. Multivariable analysis using independent variables used in the original HMRS analysis revealed different set of variables to be predictive of 90 day mortality than those used to calculate HMRS. HMRS predicts both 90 day and 1 year mortality with poor discrimination when applied to a large cohort of LVAD patients. Newer risk prediction models are therefore needed to optimize the therapeutic application of LVAD therapy. Patient selection for appropriate use of LVADs is critical. Currently available risk stratification tools (HMRS) continue to be limited in their ability to accurately predict mortality after LVAD. This study highlights these limitations when applied to a large, comprehensive, multicenter database. HMRS predicts mortality with only modest discrimination when applied to a large cohort of LVAD patients. Better risk stratification tools are needed to optimize outcomes.

Risk Assessment in Pulmonary Arterial Hypertension Patients: The Long and Short of it

Pulmonary arterial hypertension (PAH) is a chronic and rapidly progressive disease that is characterized by extensive narrowing of the pulmonary vasculature, leading to increases in pulmonary vascular resistance, subsequent right ventricular dysfunction, and eventual death. There are currently multiple approved drugs—developed as single or combination therapies in the last few years—that have improved outcome and functionality in PAH. However, despite improvement in short-term survival with these new effective therapies, PAH remains an incurable disease with a median survival of 7 years (Figure 1).1 This chronic disease state may be characterized by morbid events such as hospitalizations that herald rapid disease progression and account for a significant disease burden (Figure 2).2,3 Physician ability to predict PAH disease progression is critical for determining optimal care of patients. Accurate risk assessment allows clinicians to determine the patients prognosis, identify treatment goals, and monitor...

Retrospective Evaluation of Bayesian Risk Models of LVAD Mortality at a Single Implant Center

Use of a left ventricular assist device (LVAD) can benefit patients with end stage heart failure, but only with careful patient selection. In this study, previously derived Bayesian network models for predicting LVAD patient mortality at 1, 3, and 12 months post-implant were evaluated on retrospective data from a single implant center. The models performed well at all three time points, with a receiver operating characteristic area under the curve (ROC AUC) of 78, 76, and 75%, respectively. This evaluation of model performance verifies the utility of these models in “real life” scenarios at an individual institution.