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Risk Assessment in Patients with a Left Ventricular Assist Device Across INTERMACS Profiles Using Bayesian Analysis.

ABSTRACT: Current risk stratification models to predict outcomes after a left ventricular assist device (LVAD) are limited in scope. We assessed the performance of Bayesian models to stratify post-LVAD mortality across various International Registry for Mechanically Assisted Circulatory Support (INTERMACS or IM) Profiles, device types, and implant strategies. We performed a retrospective analysis of 10,206 LVAD patients recorded in the IM registry from 2012 to 2016. Using derived Bayesian algorithms from 8,222 patients (derivation cohort), we applied the risk-prediction algorithms to the remaining 2,055 patients (validation cohort). Risk of mortality was assessed at 1, 3, and 12 months post implant according to disease severity (IM profiles), device type (axial versus centrifugal) and strategy (bridge to transplantation or destination therapy). Fifteen percentage (n = 308) were categorized as IM profile 1, 36% (n = 752) as profile 2, 33% (n = 672) as profile 3, and 15% (n = 311) as profile 4-7 in the validation cohort. The Bayesian algorithms showed good discrimination for both short-term (1 and 3 months) and long-term (1 year) mortality for patients with severe HF (Profiles 1-3), with the receiver operating characteristic area under the curve (AUC) between 0.63 and 0.74. The algorithms performed reasonably well in both axial and centrifugal devices (AUC, 0.68-0.74), as well as bridge to transplantation or destination therapy indication (AUC, 0.66-0.73). The performance of the Bayesian models at 1 year was superior to the existing risk models. Bayesian algorithms allow for risk stratification after LVAD implantation across different IM profiles, device types, and implant strategies.

SUBMITTER: Kanwar MK

PROVIDER: S-EPMC6610699 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Risk Assessment in Patients with a Left Ventricular Assist Device Across INTERMACS Profiles Using Bayesian Analysis.

Kanwar Manreet K MK Lohmueller Lisa C LC Teuteberg Jeffrey J Kormos Robert L RL Rogers Joseph G JG Benza Raymond L RL Lindenfeld Joann J McIlvennan Colleen C Bailey Stephen H SH Murali Srinivas S Antaki James F JF

ASAIO journal (American Society for Artificial Internal Organs : 1992) 20190701 5

Current risk stratification models to predict outcomes after a left ventricular assist device (LVAD) are limited in scope. We assessed the performance of Bayesian models to stratify post-LVAD mortality across various International Registry for Mechanically Assisted Circulatory Support (INTERMACS or IM) Profiles, device types, and implant strategies. We performed a retrospective analysis of 10,206 LVAD patients recorded in the IM registry from 2012 to 2016. Using derived Bayesian algorithms from ...[more]

PMID: 30688695

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Project description:ObjectivesThis study examined patient outcomes after left ventricular assist device (LVAD) implantation across a range of center surgical volumes.BackgroundIn order for a center to qualify for reimbursement, Centers for Medicare and Medicaid Services (CMS) requires it to implant ≥10 LVADs or total artificial hearts over a 3-year period. The impact of center LVAD surgical volumes on patient outcomes has not been thoroughly scrutinized.MethodsCenter volumes were provided for 7,416 patients undergoing LVAD implantation who were enrolled in INTERMACS (Interagency Registry for Mechanically Assisted Circulatory Support). Center LVAD volume was categorized as either very low (≤10 implants/year, n = 617), low (11 to 30 implants/year, n = 2,561), medium (31 to 50 implants/year, n = 2,458), or high (>50 implants/year, n = 1,750). The main outcome of interest was patient survival based on center volume derived from Kaplan-Meier and multivariate Cox regression.ResultsOverall survival was associated with center volume (p = 0.003), as follows: 71 ± 1.8% (very low volume), 81 ± 0.8% (low volume), 83 ± 0.8% (medium volume), and 79 ± 1.0% (high volume) at 1 year. Compared with medium volume centers, the 90-day mortality was higher in very low volume (odds ratio [OR]: 1.35; p = 0.04) and high volume (OR: 1.28; p = 0.018) VAD centers. The adjusted hazard ratios (HRs) for mortality were 1.32 (95% confidence interval [CI]: 1.11 to 1.56), 1.07 (95% CI: 0.95 to 1.21), and 1.17 (95% CI: 1.03 to 1.30) for very low, low, and high volume centers, respectively. Center volume did not predict mortality (p = 0.25; n = 3,688) in INTERMACS profile 1 patients (patients who had sustained cardiogenic shock) and profile 2 patients (patients with progressive hemodynamic decline despite inotropes).ConclusionsCenter volume correlates with post-VAD survival, with worse survival noted at very-low volume centers. These findings suggest that current U.S. VAD center standards warrant reconsideration.

Project description:This study investigates the use of a Bayesian statistical model to address the limited predictive capacity of existing risk scores derived from multivariate analyses. This is based on the hypothesis that it is necessary to consider the interrelationships and conditional probabilities among independent variables to achieve sufficient statistical accuracy.Right ventricular failure (RVF) continues to be a major adverse event following left ventricular assist device (LVAD) implantation.Data used for this study were derived from 10,909 adult patients from the Inter-Agency Registry for Mechanically Assisted Circulatory Support (INTERMACS) who had a primary LVAD implanted between December 2006 and March 2014. An initial set of 176 pre-implantation variables were considered. RVF post-implant was categorized as acute (<48 h), early (48 h to 14 daysays), and late (>14 days) in onset. For each of these endpoints, a separate tree-augmented naïve Bayes model was constructed using the most predictive variables employing an open source Bayesian inference engine.The acute RVF model consisted of 33 variables including systolic pulmonary artery pressure (PAP), white blood cell count, left ventricular ejection fraction, cardiac index, sodium levels, and lymphocyte percentage. The early RVF model consisted of 34 variables, including systolic PAP, pre-albumin, lactate dehydrogenase level, INTERMACS profile, right ventricular ejection fraction, pro-B-type natriuretic peptide, age, heart rate, tricuspid regurgitation, and body mass index. The late RVF model included 33 variables and was predicted mostly by peripheral vascular resistance, model for end-stage liver disease score, albumin level, lymphocyte percentage, and mean and diastolic PAP. The accuracy of all Bayesian models was between 91% and 97%, with an area under the receiver operator characteristics curve between 0.83 and 0.90, sensitivity of 90%, and specificity between 98% and 99%, significantly outperforming previously published risk scores.A Bayesian prognostic model of RVF based on the large, multicenter INTERMACS registry provided highly accurate predictions of acute, early, and late RVF on the basis of pre-operative variables. These models may facilitate clinical decision making while screening candidates for LVAD therapy.

Project description:BackgroundLeft ventricular assist device (LVAD)-associated infections are major complications that can lead to critical outcomes. The aims of this study were to assess the incidence of and to determine the risk factors for LVAD-associated infections.MethodsWe included all consecutive patients undergoing LVAD implantation between January 1, 2010, and January 1, 2019, in a single institution. Infection-related data were retrospectively collected by review of patient’s medical files. LVAD-associated infections were classified into three categories: percutaneous driveline infections, pocket infections and pump and/or cannula infections.ResultsWe enrolled 72 patients. Twenty-one (29.2%) patients presented a total of 32 LVAD-associated infections. Eight (38.1%) patients had more than one infection. Five (62.5%) pocket infections and one (50.0%) pump and/or cannula infection were preceded by a driveline infection. The median delay between the operation and LVAD-associated infection was 6.5 (1.4–12.4) months. The probability of having a LVAD-associated infection at one year after receiving an implant was 26.6% (95% CI: 17.5–40.5%). Percutaneous driveline infections represented 68.7% of all LVAD-associated infections. Staphylococcus aureus and coagulase-negative staphylococci were the predominant bacteria in LVAD-associated infections (53.1% and 15.6%, respectively). Hospital length of stay (sdHR =1.22 per 10 days; P=0.001) and postoperative hemodialysis (sdHR =0.17; P=0.004) were statistically associated with infection. Colonization with multidrug-resistant bacteria was more frequent in patients with LVAD-associated infections than in others patients (42.9% vs. 15.7%; P=0.013).ConclusionsLVAD-associated infections remain an important complication and are mostly represented by percutaneous driveline infections. Gram-positive cocci are the main pathogens isolated in microbiological samples. Patients with LVAD-associated infections are more frequently colonized with multidrug-resistant bacteria.

Project description:Background Factors related to health-related quality of life (HRQOL) 2 years after left ventricular assist device (LVAD) implantation are unknown. We sought to determine whether preimplant intended goal of LVAD therapy (heart transplant candidate [short-term group], uncertain heart transplant candidate [uncertain group], and heart transplant ineligible [long-term group]) and other variables were related to HRQOL 2 years after LVAD implantation. Methods and Results Our LVAD sample (n=1620) was from INTERMACS (Interagency Registry for Mechanically Assisted Circulatory Support). Using the EuroQol-5 Dimension Questionnaire (EQ-5D-3L), a generic HRQOL measure, and the Kansas City Cardiomyopathy Questionnaire (KCCQ-12), a heart failure-specific HRQOL measure, multivariable linear regression modeling was conducted with the EQ-5D-3L Visual Analog Scale (VAS) score and KCCQ-12 overall summary score (OSS) as separate dependent variables. Two years after LVAD implant, the short-term group had a significantly higher mean VAS score versus the uncertain and long-term groups (short-term: 75.18 [SD, 20.62]; uncertain: 72.27 [SD, 20.33]; long-term: 70.87 [SD, 22.09], P=0.01); differences were not clinically meaningful. Two-year mean scores did not differ by group for the KCCQ-12 OSS (short-term, 67.85 [SD, 20.61]; uncertain, 67.79 [SD, 19.31]; long-term, 67.08 [SD, 21.49], P=0.80). Factors associated with a worse VAS score 2 years postoperatively (n=1205) included not working; not having a short-term LVAD; and postoperative neurological dysfunction, greater health-related stress, coping poorly, less VAD self-care confidence, and less satisfaction with VAD surgery, explaining 28% of variance (P<0.001). Factors associated with a worse KCCQ-12 OSS 2 years postoperatively (n=1250) included not working; history of high body mass index and diabetes mellitus; and postoperative renal dysfunction, greater health-related stress, coping poorly, less VAD self-care confidence, less satisfaction with VAD surgery, and regret regarding VAD implantation, accounting for 36% of variance (P<0.001). Conclusions Factors related to HRQOL 2 years after LVAD implantation include demographic, clinical, and psychological variables.

Dataset Information

Risk Assessment in Patients with a Left Ventricular Assist Device Across INTERMACS Profiles Using Bayesian Analysis.

Publications

Risk Assessment in Patients with a Left Ventricular Assist Device Across INTERMACS Profiles Using Bayesian Analysis.

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