Pre-operative mortality risk assessment in patients with continuous-flow left ventricular assist devices: Application of the HeartMate II risk score

A multicenter evaluation of the HeartMate 3 risk score

BACKGROUND

The Heartmate 3 (HM3) risk score (HM3RS) was derived and validated internally from within the Multicenter Study of MagLev Technology in Patients Undergoing Mechanical Circulatory Support Therapy with HeartMate 3 (MOMENTUM 3) trial population and provides 1- and 2-year mortality risk prediction for patients in those before HM3 left ventricular assist device (LVAD) implantation. We aimed to evaluate the HM3RS in nontrial unselected patients, including those not meeting inclusion criteria for MOMENTUM 3 trial enrollment.

METHODS

Patients who underwent HM3 LVAD implant at 1 of 7 US centers between 2017 and 2021, with at least 1-year follow-up, were included in this analysis. Patients were retrospectively assessed for their eligibility for the MOMENTUM 3 trial based on study inclusion and exclusion criteria. HM3RS risk discrimination was evaluated using time-dependent receiver operating characteristic curve analysis for 1-year mortality for all patients and further stratified by MOMENTUM 3 trial eligibility. Kaplan-Meier curves were constructed using the HM3RS-based risk categories.

RESULTS

Of 521 patients included in the analysis, 266 (51.1%) would have met enrollment criteria for MOMENTUM 3. The 1- and 2-year survival for the total cohort was 85% and 81%, respectively. There was no statistically significant difference in survival between those who met and did not meet enrollment criteria at 1 (87% vs 83%; p = 0.21) and 2 years postimplant (80% vs 78%; p = 0.39). For the total cohort, HM3RS predicted 1-year survival with an area under the curve (AUC) of 0.63 (95% confidence interval [CI]: 0.57-0.69, p < 0.001). HM3RS performed better in the subset of patients meeting enrollment criteria: AUC 0.69 (95% CI:0.61-0.77, p < 0.001) compared to the subset that did not: AUC 0.58 (95% CI: 0.49-0.66, p = 0.078).

CONCLUSIONS

In this real-world evidence, multicenter cohort, 1- and 2-year survival after commercial HM3 LVAD implant was excellent, regardless of trial eligibility. The HM3RS provided adequate risk discrimination in "trial-like" patients, but predictive value was reduced in patients who did not meet trial criteria.

Selection and management considerations to enhance outcomes in patients supported by left ventricular assist devices

PURPOSE OF REVIEW

Left ventricular assist devices (LVADs) are life-saving therapies for patients in end-stage heart failure (HF) with reduced ejection fraction regardless of candidacy for heart transplantation. Multiple clinical trials have demonstrated improved morbidity and mortality with LVADs when compared to medical therapy alone. However, the uptake of LVADs as a therapeutic option in a larger section of end-stage HF patients remains limited, partly due to associated adverse events and re-hospitalization.

RECENT FINDINGS

Accurate assessment and staging of HF patients is crucial to guide appropriate use of LVADs. Innovative methods to risk stratify patients and manage cardiac and noncardiac comorbidities can translate to improved outcomes in LVAD recipients. Inclusion of quality of life metrics and measurements of adverse events can better inform heart failure cardiologists to help identify ideal LVAD candidates. Addition of machine learning algorithms to this process may guide patient selection to improve outcomes.

SUMMARY

Patient selection and assessment of reversible medical comorbidities are critical to the postoperative success of LVAD implantation. Identifying patients most likely to benefit and least likely to experience adverse events should be a priority.

Improving Outcome Predictions for Patients Receiving Mechanical Circulatory Support by Optimizing Imputation of Missing Values

BACKGROUND

Risk prediction models play an important role in clinical decision making. When developing risk prediction models, practitioners often impute missing values to the mean. We evaluated the impact of applying other strategies to impute missing values on the prognostic accuracy of downstream risk prediction models, that is, models fitted to the imputed data. A secondary objective was to compare the accuracy of imputation methods based on artificially induced missing values. To complete these objectives, we used data from the Interagency Registry for Mechanically Assisted Circulatory Support.

METHODS

We applied 12 imputation strategies in combination with 2 different modeling strategies for mortality and transplant risk prediction following surgery to receive mechanical circulatory support. Model performance was evaluated using Monte-Carlo cross-validation and measured based on outcomes 6 months following surgery using the scaled Brier score, concordance index, and calibration error. We used Bayesian hierarchical models to compare model performance.

RESULTS

Multiple imputation with random forests emerged as a robust strategy to impute missing values, increasing model concordance by 0.0030 (25th-75th percentile: 0.0008-0.0052) compared with imputation to the mean for mortality risk prediction using a downstream proportional hazards model. The posterior probability that single and multiple imputation using random forests would improve concordance versus mean imputation was 0.464 and >0.999, respectively.

CONCLUSIONS

Selecting an optimal strategy to impute missing values such as random forests and applying multiple imputation can improve the prognostic accuracy of downstream risk prediction models.

Ventricular Assist Devices and Chronic Kidney Replacement Therapy: Technology and Outcomes

Heart failure and kidney failure are very common conditions, precipitating and exacerbating each other. Left ventricular assist devices (LVADs) represent a relatively new technology for treatment of advanced heart failure. Kidney dysfunction, if present, makes candidate selection for LVADs challenging and contributes to multiple complications while the patients are on an LVAD support. Although kidney function generally improves after LVAD implantation, some patients develop acute and then chronic kidney disease sometimes requiring kidney replacement therapies (KRTs). Overall, chronic KRT in LVAD recipients is feasible and well tolerated, but routine technique of blood pressure monitoring should be adjusted to the continuous blood flow. Both hemodialysis and peritoneal dialysis can be used. Unique challenges for chronic KRT posed by the presence of LVAD are discussed in this review.

Accuracy of Postoperative Risk Scores for Survival Prediction in Interagency Registry for Mechanically Assisted Circulatory Support Profile 1 Continuous-Flow Left Ventricular Assist Device Recipients

In this study, we sought to determine the accuracy of several critical care risk scores for predicting survival of Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) Profile 1 patients after continuous-flow left ventricular assist device (CF-LVAD) placement. We retrospectively analyzed the records of 605 patients who underwent CF-LVAD implantation between 2003 and 2016. We calculated the preoperative HeartMate II Risk Score (HMRS) and preoperative Right Ventricular Failure Risk Score (RVFRS) and the following risk scores for postoperative days 1-5: HMRS, RVFRS, Model for End-stage Liver Disease (MELD), MELD-eXcluding International Normalized Ratio, Post Cardiac Surgery (POCAS) risk score, Sequential Organ Failure Assessment (SOFA) risk score, and Acute Physiology and Chronic Health Evaluation III. The preoperative scores and the postoperative day 1, 5-day mean, and 5-day maximum scores were entered into a receiver operating characteristic curve analysis to examine accuracy for predicting 30-day, 90-day, and 1-year survival. The mean POCAS score was the best predictor of 30-day and 90-day survival (area under the curve [AUC] = 0.869 and 0.816). The postoperative mean RVFRS was the best predictor of 1-year survival (AUC = 0.7908). The postoperative maximum and mean RVFRS and HMRS were more accurate than the preoperative scores. Both of these risk score measurements of acuity in the postoperative intensive care unit setting help predict early mortality after LVAD implantation.

Gastrointestinal Bleeding as a Complication in Continuous Flow Ventricular Assist Devices: A Systematic Review With Meta-Analysis

Background

The use of ventricular assist devices (VADs) has become predominant in this era of medicine. It is commonly used as a bridge to transplant, recovery and as a destination therapy for patients with severe heart failure, who are not responsive to maximum optimal management or ineligible for transplant. However, several complications are known to occur with the use of these devices. In this research, we will compare gastrointestinal bleeding in patients who used centrifugal flow versus axial flow VADs. We hope that the result of this meta-analysis and the review presented provide adequate information to future researchers, physicians and other healthcare professionals who are interested in this topic.

Methods

Published articles evaluated for inclusion were obtained from MEDLINE (PubMed), Cochrane, EBSCO, clinicaltrials.gov, and international clinical trials registry. This research was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Procured articles were reviewed by two independent reviewers. Only randomized control trials and observational studies were used. Quality assessment was done with Cochrane Collaboration’s tool (RoB.2 with visualization through robviz) and Newcastle-Ottawa Scale (NOS). Data analysis was carried out with the use of R data analysis tool (version 4.0.0; release date: April 24th, 2020).

Results

At the end of this meta-analysis, the occurrence of gastrointestinal bleeding was not significantly different between both groups; with odds ratio (OR): 0.81; 95% confidence interval (CI): 0.65 - 1.00; P value = 0.05. Between-study variance (Tau-squared) was zero (0), standard error (SE) = 0.06. The degree of heterogeneity measured with I-squared statistic was 0% (minimal). Egger’s regression test was not statistically significant, P = 0.93. Symmetry of distribution was observed on the funnel plot. Trim and fill analysis showed no missing studies on the left; SE = 1.68.

Conclusions

The result obtained from this research indicates that the occurrence of gastrointestinal bleeding is not significantly different in both groups of patients, irrespective of the type of continuous flow VAD used. Although, the study sample used in this meta-analysis was limited.

Use of Ventricular Assist Devices and Heart Transplantation for Advanced Heart Failure

There are only 2 treatments for the thousands of patients who progress to the most advanced form of heart failure despite the application of guideline-based medical therapy, use of ventricular assist devices and heart transplantation. There has been a great deal of progress in both of these therapies that have led to improved outcomes including significant improvement in survival and functional capacity. Heart transplantation offers the best short- and long-term survival for patients with end-stage heart failure, and the majority of these recipients achieve relatively limitless functional capacity for their age. However, the chronic shortage of available donors limits the number of recipients in the United States to an only 2500 patients/y or only a fraction of potential candidates. The significant improvement in outcomes now possible with durable ventricular assist devices has led to a significant increase in their use, which now exceeds the volume of heart transplants in the United States, with the greatest growth in use for those not considered to be candidates for heart transplantation, previously referred to as destination therapy. This article will review the substantial progress that has taken place for both of these life-saving treatment options, as well as the future directions.

Mechanical circulatory support: 60 years of evolving knowledge

Since the 1950s when the first devices for mechanical circulatory support were developed, there has been an impressive evolution of their technology. The first pioneering pumps were used to rescue acute complications after cardiac surgery. Advances in technology, increased knowledge of flow dynamics, and a more appropriate selection of the patients who actually need this support have contributed to significantly improve the benefits of this therapy. Today, mechanical circulatory support is an essential tool for the treatment of advanced heart failure. This strategy is used either as a bridge to heart transplantation or as a destination therapy for patients who do not meet the transplant criteria. A third indication is the bridge to recovery option for those patients in whom the improvement in cardiac function may be so important that the pump can be removed and the transplantation circumvented. In addition, mechanical circulatory support has fostered marked improvements in several clinical aspects affecting both patient health and quality of life. Despite the improvements in the technology of the devices of the last generation, severe adverse effects are still the Achilles heel of mechanical circulatory support therapy. This review summarizes the history, the technology, the clinical outcomes, and the possible future directions of this therapy.

A Bayesian Model to Predict Survival After Left Ventricular Assist Device Implantation

OBJECTIVES

This study investigates the use of a Bayesian statistical models to predict survival at various time points in patients undergoing left ventricular assist device (LVAD) implantation.

BACKGROUND

LVADs are being increasingly used in patients with end-stage heart failure. Appropriate patient selection continues to be key in optimizing post-LVAD outcomes.

METHODS

Data used for this study were derived from 10,277 adult patients from the INTERMACS (Inter-Agency Registry for Mechanically Assisted Circulatory Support) who had a primary LVAD implanted between January 2012 and December 2015. Risk for mortality was calculated retrospectively for various time points (1, 3, and 12 months) after LVAD implantation, using multiple pre-implantation variables. For each of these endpoints, a separate tree-augmented naïve Bayes model was constructed using the most predictive variables.

RESULTS

A set of 29, 26, and 31 pre-LVAD variables were found to be predictive at 1, 3, and 12 months, respectively. Predictors of 1-month mortality included low Inter-Agency Registry for Mechanically Assisted Circulatory Support profile, number of acute events in the 48 h before surgery, temporary mechanical circulatory support, and renal and hepatic dysfunction. Variables predicting 12-month mortality included advanced age, frailty, device strategy, and chronic renal disease. The accuracy of all Bayesian models was between 76% and 87%, with an area under the receiver operative characteristics curve of between 0.70 and 0.71.

CONCLUSIONS

A Bayesian prognostic model for predicting survival based on the comprehensive INTERMACS registry provided highly accurate predictions of mortality based on pre-operative variables. These models may facilitate clinical decision-making while screening candidates for LVAD therapy.

Red Cell Distribution Width Predicts 90 Day Mortality in Continuous-Flow Left Ventricular Assist Device Patients

Red cell distribution width (RDW) measures the variance in size of circulating red blood cells and is a strong independent predictor of morbidity and mortality in cardiovascular disease and heart failure. Predictive power of RDW on mortality after continuous-flow left ventricular assist device (CF-LVAD) implantation remains largely unknown. Four hundred nine patients who underwent CF-LVAD implantation between April 2004 and December 2015 were retrospectively analyzed. The primary outcome of interest was 90 day mortality after CF-LVAD implantation. Median RDW before CF-LVAD implantation was 15.8%. Patients with elevated RDW (>15.8%) at baseline had significantly lower hemoglobin (10.6 ± 1.8 vs. 11.9 ± 2.1 mg/dl; p < 0.001), lower mean corpuscular volume (84.9 ± 7.7. vs. 88.7 ± 5.9; p < 0.001), higher blood urea nitrogen (BUN; 36.3 ± 21.8 vs. 30.1 ± 17.1; p < 0.001), lower albumin (3.4 ± 0.6 vs. 3.7 ± 0.5; p < 0.001), and higher total bilirubin levels (1.67 ± 2.21 vs. 1.29 ± 0.96). Red cell distribution width was independently predictive of 90 day mortality (odds ratio [OR], 1.16 for 1% increase; CI, 1.04-1.31; p = 0.010). Discriminatory power of RDW alone was comparable to model of end-stage liver disease excluding international normalized ratio (MELD-Xi) and HeartMate II risk scores. Mechanical unloading with CF-LVAD was associated with a reduction in RDW levels. These findings suggest that RDW, a simple and inexpensive test available through routine complete blood count, can be successfully used for mortality risk assessment in CF-LVAD candidates.

Predicting Long Term Outcome in Patients Treated With Continuous Flow Left Ventricular Assist Device: The Penn-Columbia Risk Score

Background

Predicting which patients are unlikely to benefit from continuous flow left ventricular assist device (LVAD) treatment is crucial for the identification of appropriate patients. Previously developed scoring systems are limited to past eras of device or restricted to specific devices. Our objective was to create a risk model for patients treated with continuous flow LVAD based on the preimplant variables.

Methods and Results

We performed a retrospective analysis of all patients implanted with a continuous flow LVAD between 2006 and 2014 at the University of Pennsylvania and included a total of 210 patients (male 78%; mean age, 56±15; mean follow‐up, 465±486 days). From all plausible preoperative covariates, we performed univariate Cox regression analysis for covariates affecting the odds of 1‐year survival following implantation (P<0.2). These variables were included in a multivariable model and dropped if significance rose above P=0.2. From this base model, we performed step‐wise forward and backward selection for other covariates that improved power by minimizing Akaike Information Criteria while maximizing the Harrell Concordance Index. We then used Kaplan–Meier curves, the log‐rank test, and Cox proportional hazard models to assess internal validity of the scoring system and its ability to stratify survival. A final optimized model was identified based on clinical and echocardiographic parameters preceding LVAD implantation. One‐year mortality was significantly higher in patients with higher risk scores (hazard ratio, 1.38; P=0.004). This hazard ratio represents the multiplied risk of death for every increase of 1 point in the risk score. The risk score was validated in a separate patient cohort of 260 patients at Columbia University, which confirmed the prognostic utility of this risk score (P=0.0237).

Conclusion

We present a novel risk score and its validation for prediction of long‐term survival in patients with current types of continuous flow LVAD support.

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.

Association of global and disease-specific health status with outcomes following continuous-flow left ventricular assist device implantation

BACKGROUND

The prognostic value of heart failure specific and global health status before and after left ventricular assist device (LVAD) implantation in the usual care setting is not well studied.

METHODS

We included 3,836 continuous-flow LVAD patients in the INTERMACS registry. Health status was measured pre-operatively and 3 months post-LVAD using the Kansas City Cardiomyopathy Questionnaire (KCCQ) and EuroQol visual analog scale (VAS). Primary outcomes were mortality/rehospitalization. Inverse propensity weighting was used to minimize bias from missing data.

RESULTS

Pre-operative global and heart failure-specific health status were very poor: KCCQ median 34.6 (IQR 21.4-50.5); VAS median 43 (interquartile range (IQR) 25-65). Health status measures improved 3 months after LVAD placement: KCCQ median 69.3 (IQR 54.2-82.3); VAS median 75 (IQR 60-85). Pre-operative health status was not associated with death (unadjusted HR for lowest vs. highest score quartiles: 1.09 (0.85-1.41) KCCQ; 1.12 (0.85-1.49) VAS) or rehospitalization (unadjusted HR 0.83 (0.72-0.96) KCCQ; 0.99 (0.85-1.16) VAS). Three-month KCCQ was associated with mortality (unadjusted HR 2.17 (1.47-3.21); VAS was not (1.43 (0.94-2.17). Three-month KCCQ added incremental discriminatory value to the HeartMate II Risk Score for death (c-stat 0.60 to 0.66); VAS did not (c-stat 0.59 to 0.60). Three-month health status was associated with rehospitalization (unadjusted HR 1.31 (1.15-1.57) KCCQ; 1.24 (1.05-1.46) VAS), but did not add incremental discriminatory value (c-stat 0.52 to 0.55 and 0.54, respectively).

CONCLUSIONS

These real-world data suggest that pre-operative health status has limited association with outcomes after LVAD. However, persistently low health status after surgery may independently signal higher risk for subsequent death. Further study is needed to determine the clinical utility of routinely collected health status data after LVAD implantation.

Mechanical Circulatory Support: Heart Failure Therapy “in Motion”

Because the first generation of pulsatile-flow devices was primarily used to bridge the sickest patients to transplantation (bridge-to-transplant therapy), the current generation of continuous-flow ventricular assist devices qualifies for destination therapy for patients with advanced heart failure who are ineligible for transplantation. The first-generation devices were associated with frequent adverse events, limited mechanical durability, and patient discomfort due device size. In contrast, second-generation continuous-flow devices are smaller, more quiet, and durable, thus resulting in less complications and significantly improved survival rates. Heart transplantation remains an option for a limited number of patients only, and this fact has also triggered the discussion about the optimal timing for device implantation. The increasing use of continuous-flow devices has resulted in new challenges, such as adverse events during long-term support, and high hospital readmission rates. In addition, there are a number of device-related complications including mechanical problems such as device thrombosis, percutaneous driveline damage, as well as conditions such as hemolysis, infection, and cerebrovascular accidents. This review provides an overview of the evolution of mechanical circulatory support systems from bridge to transplantation to destination therapy including technological advances and clinical improvements in long-term patient survival and quality of life. In addition, recent changes in device implant strategies and current trials are reviewed and discussed. A brief glimpse into the future of mechanical circulatory support therapy will summarize the innovations that may soon enter clinical practice.

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.

Role of Survival Scores Before Left Ventricular Assist Device Implantation: The New CHRiSS Compared to the HeartMate II Score

Risk stratification of patients are claimed to be useful before left ventricular assist device (LVAD) implantation and different scoring systems are available. The aim of the study was to validate the Cardiac Health Risk Stratification System (CHRiSS), based on Bayesian network analysis, and the HeartMate II score in our patient population. We retrospectively calculated the CHRiSS using a web-based application and the HeartMate II score of 105 adult patients who underwent consecutive HVAD (HeartWare International, Inc.) implantation as primary LVAD at our institution in a 12-month period (May 2014-April 2015). Survival was 83.8 % (3.6%) at 30 days, 77.8% (4.0%) at 90 days, and 72.8% (4.8%) at 6 months and 1 year. The area under the curve (AUC) of the receiver operating characteristics (ROC) curve for CHRiSS was 0.75 at 30 days, 0.66 at 90 days, and 0.65 at 6 months. The HeartMate II score had an AUC of 0.73 at 90 days. Comparison between the ROC curves of the two models calculated at 90 days showed no statistically significant difference (p = 0.48): CHRiSS presents a high positive predictive value (85 [80-91]), the opposite to the HeartMate II score, which has a high negative predictive value (91 [83.4-96.6]). In our population, application of the CHRiSS was valuable at 30 days, but the overall predictive value of both scores is not satisfactory. The CHRiSS model proved to be a promising tool, suggesting that, with greater sample size and a longer data collection period, it might potentially outperform the HeartMate II scoring system.

A new Bayesian network-based risk stratification model for prediction of short-term and long-term LVAD mortality

Existing risk assessment tools for patient selection for left ventricular assist devices (LVADs) such as the Destination Therapy Risk Score and HeartMate II Risk Score (HMRS) have limited predictive ability. This study aims to overcome the limitations of traditional statistical methods by performing the first application of Bayesian analysis to the comprehensive Interagency Registry for Mechanically Assisted Circulatory Support dataset and comparing it to HMRS. We retrospectively analyzed 8,050 continuous flow LVAD patients and 226 preimplant variables. We then derived Bayesian models for mortality at each of five time end-points postimplant (30 days, 90 days, 6 month, 1 year, and 2 years), achieving accuracies of 95%, 90%, 90%, 83%, and 78%, Kappa values of 0.43, 0.37, 0.37, 0.45, and 0.43, and area under the receiver operator characteristic (ROC) of 91%, 82%, 82%, 80%, and 81%, respectively. This was in comparison to the HMRS with an ROC of 57% and 60% at 90 days and 1 year, respectively. Preimplant interventions, such as dialysis, ECMO, and ventilators were major contributing risk markers. Bayesian models have the ability to reliably represent the complex causal relations of multiple variables on clinical outcomes. Their potential to develop a reliable risk stratification tool for use in clinical decision making on LVAD patients encourages further investigation.

Left ventricular assist device patient selection: do risk scores help?

Mechanical circulatory support (MCS) and left ventricular assist device (LVAD) implantation is becoming increasingly utilized in the advanced heart failure (HF) population. Until further developments are made in this continually evolving field, the need for appropriate patient selection is fueled by our knowledge that the less sick do better. Due to the evolution of MCS technology, and the importance of patient selection to outcomes, risk scores and classification schemes have been developed to provide a structure for medical decision making. As clinical experience grows, technology improves, and further favorable clinical characteristics are identified, it is incumbent upon the HF community to continually hone these instruments. The magnitude of such tools cannot be understated when it comes to aiding in the informed consent and shared-decision making process for patients, families, and the healthcare team. Many risk models that have attempted to address which groups of patients will be successful focus on short term mortality and not long term survival or quality of life. The benefits and pitfalls of these models and their potential implications for patient selection and MCS therapy will be reviewed here.

Left Ventricular Assist Devices: A Rapidly Evolving Alternative to Transplant

Left ventricular assist devices are becoming an increasingly prevalent therapy for patients with Stage D heart failure with reduced ejection fraction. Technological advances have improved the durability of these devices and have significantly lengthened survival in these patients. Quality of life is also improved, although adverse events related to device therapy remain common. Nevertheless, with the continuing organ donor shortage for cardiac transplantation, left ventricular assist devices are frequently serving as a substitute for transplant, particularly in the elderly patient.

Nutritional Risk Index predicts mortality in hospitalized advanced heart failure patients

BACKGROUND

Hospitalized advanced heart failure (HF) patients are at high risk for malnutrition and death. The Nutritional Risk Index (NRI) is a simple, well-validated tool for identifying patients at risk for nutrition-related complications. We hypothesized that, in advanced HF patients from the ESCAPE (Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness) trial, the NRI would improve risk discrimination for 6-month all-cause mortality.

METHODS

We analyzed the 160 ESCAPE index admission survivors with complete follow-up and NRI data, calculated as follows: NRI = (1.519 × discharge serum albumin [in g/dl]) + (41.7 × discharge weight [in kg] / ideal body weight [in kg]); as in previous studies, if discharge weight is greater than ideal body weight (IBW), this ratio was set to 1. The previously developed ESCAPE mortality model includes: age; 6-minute walk distance; cardiopulmonary resuscitation/mechanical ventilation; discharge β-blocker prescription and diuretic dose; and discharge serum sodium, blood urea nitrogen and brain natriuretic peptide levels. We used Cox proportional hazards modeling for the outcome of 6-month all-cause mortality.

RESULTS

Thirty of 160 patients died within 6 months of hospital discharge. The median NRI was 96 (IQR 91 to 102), reflecting mild-to-moderate nutritional risk. The NRI independently predicted 6-month mortality, with adjusted HR 0.60 (95% CI 0.39 to 0.93, p = 0.02) per 10 units, and increased Harrell's c-index from 0.74 to 0.76 when added to the ESCAPE model. Body mass index and NRI at hospital admission did not predict 6-month mortality. The discharge NRI was most helpful in patients with high (≥ 20%) predicted mortality by the ESCAPE model, where observed 6-month mortality was 38% in patients with NRI < 100 and 14% in those with NRI > 100 (p = 0.04).

CONCLUSIONS

The NRI is a simple tool that can improve mortality risk stratification at hospital discharge in hospitalized patients with advanced HF.

Advanced (stage D) heart failure: a statement from the Heart Failure Society of America Guidelines Committee

We propose that stage D advanced heart failure be defined as the presence of progressive and/or persistent severe signs and symptoms of heart failure despite optimized medical, surgical, and device therapy. Importantly, the progressive decline should be primarily driven by the heart failure syndrome. Formally defining advanced heart failure and specifying when medical and device therapies have failed is challenging, but signs and symptoms, hemodynamics, exercise testing, biomarkers, and risk prediction models are useful in this process. Identification of patients in stage D is a clinically important task because treatments are inherently limited, morbidity is typically progressive, and survival is often short. Age, frailty, and psychosocial issues affect both outcomes and selection of therapy for stage D patients. Heart transplant and mechanical circulatory support devices are potential treatment options in select patients. In addition to considering indications, contraindications, clinical status, and comorbidities, treatment selection for stage D patients involves incorporating the patient's wishes for survival versus quality of life, and palliative and hospice care should be integrated into care plans. More research is needed to determine optimal strategies for patient selection and medical decision making, with the ultimate goal of improving clinical and patient centered outcomes in patients with stage D heart failure.

The Heartmate Risk Score predicts morbidity and mortality in unselected left ventricular assist device recipients and risk stratifies INTERMACS class 1 patients

OBJECTIVES

This study evaluated the Heartmate Risk Score (HMRS) and its potential benefits in clinical practice.

BACKGROUND

The HMRS has been shown to correlate with mortality in the cohort of patients enrolled in the Heartmate II trials, but its validity in unselected, "real world" populations remains unclear.

METHODS

This study identified a cohort of 269 consecutive patients who received a Heartmate II left ventricular assist device at our institution, the Barnes-Jewish Hospital in St. Louis, Missouri, between June 2005 and June 2013. Ninety-day and 2-year mortality rates, as well as frequency of several morbid events, were compared by retrospectively assigned HMRS category groups. The analysis was repeated within the subgroup of INTERMACS (Interagency Registry for Mechanically Assisted Circulatory Support) class 1 patients.

RESULTS

Receiver operating curve analysis showed that the HMRS correlated with 90-day mortality with an area under the curve of 0.70. Stratification in low, mid, and high HMRS groups identified patients with increasing hazard of 90-day mortality, increasing long-term mortality, increasing rate of gastrointestinal bleeding events, and increasing median number of days spent in the hospital in the first year post implant. Within INTERMACS class 1 patients, those in the highest HMRS group were found to have a relative risk of 90-day mortality 5.7 times higher than those in the lowest HMRS group (39.1% vs. 6.9%, p = 0.029).

CONCLUSIONS

HMRS is a valid clinical tool to stratify risk of morbidity and mortality after implant of Heartmate II devices in unselected patients and can be used to predict short-term mortality risk in INTERMACS class 1 patients.