2017
DOI: 10.1097/mat.0000000000000494
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Low Accuracy of the HeartMate Risk Score for Predicting Mortality Using the INTERMACS Registry Data

Abstract: Patient selection is a key determinant of clinical outcomes after LVAD placement in patients with end stage heart failure. The 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). 11,523 INTERMACS patients who received a continuous flow LVAD between 2010 an… Show more

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Cited by 20 publications
(10 citation statements)
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“…We have previously published algorithms based on Bayesian modeling to predict mortality at various time points post-LVAD implantation (6). In the current study, we validate these mortality models for their performance across IM profiles, as a function of disease severity.…”
Section: Introductionmentioning
confidence: 77%
See 1 more Smart Citation
“…We have previously published algorithms based on Bayesian modeling to predict mortality at various time points post-LVAD implantation (6). In the current study, we validate these mortality models for their performance across IM profiles, as a function of disease severity.…”
Section: Introductionmentioning
confidence: 77%
“…These include multiple pre-operative characteristics such as demographics, medical history, and test results (laboratory, exercise and imaging) etc. In fact, IM profile at the time of implant was one of the variables predictive of 1 and 3-month mortality (6). This becomes increasingly relevant when risk stratifying outcomes in patients with end-stage HF, given their inherent heterogeneity and associated medical co-morbidities.…”
Section: Discussionmentioning
confidence: 99%
“…(1315) Rather than trying to combine a multiplicity of factors by using a weighted summation, Bayesian models provide a dynamic incorporation of many variables, yielding a more robust ROC value than previously published scores. (6, 11) The 90-day and 1-year HMRS stratifications had AUC of 61% and 59%, respectively, whereas the Bayesian 90-day and 1-year predictions exhibited AUC of 71% and 70%, respectively. (15)…”
Section: Discussionmentioning
confidence: 99%
“…Although various risk stratification models have been proposed to predict survival / mortality post-LVAD, they all have limited applications in ‘real life’ decision making due to their derivation from a limited number of variables in small data sets, or analyzing a specific pump. (69) It is recognized that accurate predictions of outcomes after LVAD implantation depend on a complex and dynamic interplay of multiple pre-operative variables that may be inadequately captured by traditional multivariate statistical modeling. Bayesian network (BN) algorithms have been proposed to predict mortality, gastrointestinal bleeding, and right ventricular failure in LVAD populations.…”
Section: Introductionmentioning
confidence: 99%
“…Baseline characteristics were assessed from our LVAD database. From the data of this database, we calculated established risk scores, such as the HeartMate II Score, 6,7 the Cardiac Surgery Score, 8 the Vasoactive-Inotropic Score (VIS), 9 and the Model of End Stage Liver Disease excluding international normalized ratio score (MELD-XI). 10,11 The HeartMate II Score is the only established LVAD-specific risk score.…”
Section: Methodsmentioning
confidence: 99%