Predictor Of Waitlist Mortality Research Articles

Elevated pulmonary vascular resistance is associated with increased lung transplant waitlist mortality among patients with chronic obstructive pulmonary disease and pulmonary hypertension: a retrospective cohort analysis

BackgroundThe latest European Society of Cardiology and European Respiratory Society guidelines have changed the definition of both pre-capillary pulmonary hypertension (PH) and severe PH in chronic lung disease. The clinical significance of these new criteria are unclear among patients with chronic obstructive pulmonary disease (COPD)-PH. We aim to examine the clinical significance of the new PH definitions with regards to lung transplant waitlist mortality amongst patients with COPD-PH.MethodsThis was a retrospective cohort study of adult patients with COPD-PH listed for lung transplantation. Kaplan–Meier survival analyses were performed comparing patients with newly defined pre-capillary PH to those without pre-capillary PH and comparing patients with severe PH, defined as pulmonary vascular resistance (PVR) > 5 WU, to those without severe PH. Both mean pulmonary artery pressure (mPAP) and PVR were analyzed for potential cut-off points associated with increased waitlist mortality. Predictors of waitlist mortality were identified via Cox regression.ResultsAmong 6495 patients with COPD-PH listed for lung transplantation, pre-capillary PH was not associated with increased waitlist mortality (logrank p = 0.43), while severe PH was (logrank p < 0.001). Both severe PH (HR 1.79, 95% CI 1.22–2.60, p = 0.003) and PVR > 3.9 WU (HR 1.49, 95% CI 1.14–1.95, p = 0.004) were independently and significantly associated with increased waitlist mortality.ConclusionsPVR may serve as a strong predictor of lung transplant waitlist mortality among patients with COPD-PH as compared to other pulmonary hemodynamic parameters when predicting transplant waitlist mortality.

Neighborhood-level Social Determinants of Health and Waitlist Mortality for Liver Transplantation: The Liver Outcomes and Equity Index.

To examine neighborhood-level disparities in waitlist mortality for adult liver transplantation (LT), we developed novel area-based social determinants of health (SDOH) index using a national transplant database. ZIP Codes of individuals listed for or received LT in the Scientific Registry of Transplant Recipients database between June 18, 2013, and May 18, 2019, were linked to 36 American Community Survey (ACS) variables across 5 SDOH domains for index development. A step-wise principal component analysis was used to construct the Liver Outcomes and Equity (LOEq) index. We then examined the association between LOEq quintiles (Q1 = worst and Q5 = best neighborhood SDOH) and waitlist mortality with competing risk regression among listed adults in the study period and acuity circle (AC) era. The final LOEq index consisted of 13 ACS variables. Of 59 298 adults waitlisted for LT, 30% resided in LOEq Q5 compared with only 14% in Q1. Q1 neighborhoods with worse SDOH were disproportionately concentrated in transplant regions with low median Model for End-Stage Liver Disease at transplant (MMAT) and shorter wait times. Five years cumulative incidence of waitlist mortality was 33% in Q1 in high MMAT regions versus 16% in Q5 in low MMAT regions. Despite this allocation advantage, LOEq Q1-Q4 were independently associated with elevated risk of waitlist mortality compared with Q5, with highest increased hazard of waitlist deaths of 19% (95% CI, 11%-26%) in Q1. This disparity persisted in the AC era, with 24% (95% CI, 10%-40%) increased hazard of waitlist deaths for Q1 versus Q5. Neighborhood SDOH independently predicts waitlist mortality in adult LT.

Brief PROMIS Assessment Screens for Frailty and Predicts Hospitalizations in Liver Transplant Candidates.

Frailty is prevalent in patients with end-stage liver disease and predicts waitlist mortality, posttransplant mortality, and frequency of hospitalizations. The Liver Frailty Index (LFI) is a validated measure of frailty in liver transplant (LT) candidates but requires an in-person assessment. We studied the association between patient-reported physical function and LFI in a single-center prospective study of adult patients with cirrhosis undergoing LT evaluation from October 2020 to December 2021. Frailty was assessed with the LFI and 4-m gait speed. Patient-reported physical function was evaluated using a brief Patient-Reported Outcomes Measurement Information System (PROMIS) survey. Eighty-one LT candidates were enrolled, with a mean model of end-stage liver disease-sodium of 17.6 (±6.3). The mean LFI was 3.7 (±0.77; 15% frail and 59% prefrail) and the mean PROMIS Physical Function score was 45 (±8.6). PROMIS Physical Function correlated with LFI ( r = -0.54, P < 0.001) and 4-m gait speed ( r = 0.48, P < 0.001). The mean hospitalization rate was 1.1 d admitted per month. After adjusting for age, sex, and model of end-stage liver disease-sodium, patient-reported physical function-predicted hospitalization rate ( P = 0.001). This study suggests that a brief patient-reported outcome measure can be used to screen for frailty and predict hospitalizations in patients with cirrhosis.

Development and Validation of an Abridged Physical Frailty Phenotype for Clinical Use: A Cohort Study Among Kidney Transplant Candidates.

Frailty is associated with poor outcomes in surgical patients including kidney transplant (KT) recipients. Transplant centers that measure frailty have better pre- and postoperative outcomes. However, clinical utility of existing tools is low due to time constraints. To address this major barrier to implementation in the preoperative evaluation of patients, we developed an abridged frailty phenotype. The abridged frailty phenotype was developed by simplifying the 5 physical frailty phenotype (PFP) components in a two-center prospective cohort of 3 220 KT candidates and tested for efficiency (time to completion) in 20 candidates evaluation (January 2009 to March 2020). We examined area under curve (AUC) and Cohen's kappa agreement to compare the abridged assessment with the PFP. We compared waitlist mortality risk (competing risks models) by frailty using the PFP and abridged assessment, respectively. Model discrimination was assessed using Harrell's C-statistic. Of 3 220 candidates, the PFP and abridged assessment identified 23.8% and 27.4% candidates as frail, respectively. The abridged frailty phenotype had substantial agreement (kappa = 0.69, 95% CI: 0.66-0.71) and excellent discrimination (AUC = 0.861). Among 20 patients at evaluation, abridged assessment took 5-7 minutes to complete. The PFP and abridged assessment had similar associations with waitlist mortality (subdistribution hazard ratio [SHR] = 1.62, 95% CI: 1.26-2.08 vs SHR = 1.70, 95% CI: 1.33-2.16) and comparable mortality discrimination (p = .51). The abridged assessment is an efficient and valid way to identify frailty. It predicts waitlist mortality without sacrificing discrimination. Surgical departments should consider utilizing the abridged assessment to evaluate frailty in patients when time is limited.

An Objective Risk Score Predicts Waitlist Mortality with Higher Accuracy Than 6-Status Ranking at Listing

<h3>Purpose</h3> The US has a new 6-status ranking system for heart transplant candidates that, in contrast to kidney, liver and lung allocation, relies primarily on subjective treatment decisions as a surrogate for medical urgency. Incorporating objective patient characteristics could create a more equitable system and save more lives. <h3>Methods</h3> We utilized Scientific Registry of Transplant Recipients data on 32,567 US adult heart-only transplant candidates divided into pre-policy training (2010 - 2017) and post-policy test (11/1/2018 - 3/1/2020) datasets. We generated risk scores from a Cox Proportional Hazards (CPH) model fit to the outcome of death without a transplant. In addition to treatment variables, we included age, year of listing, height, weight, GFR, cardiac index, pulmonary artery mean pressure, pulmonary capillary wedge pressure, peak oxygen capacity, diagnosis, blood type, diabetes, and history of tobacco use, malignancy, or stroke. We compared the performance of this model to the performance of a model that includes only a candidate's 6-status ranking at listing using 1) Uno's c-index and 2) Kaplan-Meier of risk score groups. <h3>Results</h3> In the post-policy test dataset, the risk score model had higher discrimination than the 6-status based model (c-index 0.71 vs. 0.63, p < 0.01). Status 5 candidates had significantly lower survival without transplant than Status 4 candidates (p<0.01 by log-rank test, <b>Fig</b>). The risk score identified a highest risk group with greater urgency than Status 1 candidates (median survival 96 days vs 129 days, p = 0.05). An entirely objective model without treatment variables also outperformed the 6-status rankings (c-index 0.69 vs. 0.63, p < 0.01). <h3>Conclusion</h3> A risk score incorporating objective patient characteristics can rank order heart transplant candidates more effectively than the 6-status ranking at listing. Heart allocation systems should use objective measurements of physiological function to identify medically urgent candidates.

Derivation and validation of a clinical risk score to predict death among patients awaiting cardiac surgery in Ontario, Canada: a population-based study.

Background:Surgical delay may result in unintended harm to patients needing cardiac surgery, who are at risk for death if their condition is left untreated. Our objective was to derive and internally validate a clinical risk score to predict death among patients awaiting major cardiac surgery.Methods:We used the CorHealth Ontario Registry and linked ICES health administrative databases with information on all Ontario residents to identify patients aged 18 years or more who were referred for isolated coronary artery bypass grafting (CABG), valvular procedures, combined CABG–valvular procedures or thoracic aorta procedures between Oct. 1, 2008, and Sept. 30, 2019. We used a hybrid modelling approach with the random forest method for initial variable selection, followed by backward stepwise logistic regression modelling for clinical interpretability and parsimony. We internally validated the logistic regression model, termed the CardiOttawa Waitlist Mortality Score, using 200 bootstraps.Results:Of the 112 266 patients referred for cardiac surgery, 269 (0.2%) died while awaiting surgery (118/72 366 [0.2%] isolated CABG, 81/24 461 [0.3%] valvular procedures, 63/12 046 [0.5%] combined CABG–valvular procedures and 7/3393 [0.2%] thoracic aorta procedures). Age, sex, surgery type, left main stenosis, Canadian Cardiovascular Society classification, left ventricular ejection fraction, heart failure, atrial fibrillation, dialysis, psychosis and operative priority were predictors of waitlist mortality. The model discriminated (C-statistic 0.76 [optimism-corrected 0.73]). It calibrated well in the overall cohort (Hosmer–Lemeshow p = 0.2) and across surgery types.Interpretation:The CardiOttawa Waitlist Mortality Score is a simple clinical risk model that predicts the likelihood of death while awaiting cardiac surgery. It has the potential to provide data-driven decision support for managing access to cardiac care and preserve system capacity during the COVID-19 pandemic, the recovery period and beyond.

MELD is MELD is MELD? Transplant center–level variation in waitlist mortality for candidates with the same biological MELD

Recently, model for end-stage liver disease (MELD)-based liver allocation in the United States has been questioned based on concerns that waitlist mortality for a given biologic MELD (bMELD), calculated using laboratory values alone, might be higher at certain centers in certain locations across the country. Therefore, we aimed to quantify the center-level variation in bMELD-predicted mortality risk. Using Scientific Registry of Transplant Recipients (SRTR) data from January 2015 to December 2019, we modeled mortality risk in 33260 adult, first-time waitlisted candidates from 120 centers using multilevel Poisson regression, adjusting for sex, and time-varying age and bMELD. We calculated a "MELD correction factor" using each center's random intercept and bMELD coefficient. A MELD correction factor of +1 means that center's candidates have a higher-than-average bMELD-predicted mortality risk equivalent to 1 bMELD point. We found that the "MELD correction factor" median (IQR) was 0.03 (-0.47, 0.52), indicating almost no center-level variation. The number of centers with "MELD correction factors" within ±0.5 points, and between ±0.5-± 1, ±1.0-±1.5, and ±1.5-±2.0 points was 62, 41, 13, and 4, respectively. No centers had waitlisted candidates with a higher-than-average bMELD-predicted mortality risk beyond ±2 bMELD points. Given that bMELD similarly predicts waitlist mortality at centers across the country, our results support continued MELD-based prioritization of waitlisted candidates irrespective of center.

Patient-reported dyspnea and health predict waitlist mortality in patients waiting for lung transplantation in Japan

BackgroundWaitlist mortality due to donor shortage for lung transplantation is a serious problem worldwide. Currently, the selection of recipients in Japan is mainly based on the registration order. Hence, scientific evidence for risk stratification regarding waitlist mortality is urgently needed. We hypothesized that patient-reported dyspnea and health would predict mortality in patients waitlisted for lung transplantation.MethodsWe analyzed factors related to waitlist mortality using data of 203 patients who were registered as candidates for lung transplantation from deceased donors. Dyspnea was evaluated using the modified Medical Research Council (mMRC) dyspnea scale, and the health status was determined with St. George’s Respiratory Questionnaire (SGRQ).ResultsAmong 197 patients who met the inclusion criteria, the main underlying disease was interstitial lung disease (99 patients). During the median follow-up period of 572 days, 72 patients died and 96 received lung transplantation (69 from deceased donors). Univariable competing risk analyses revealed that both mMRC dyspnea and SGRQ Total score were significantly associated with waitlist mortality (p = 0.003 and p < 0.001, respectively) as well as age, interstitial lung disease, arterial partial pressure of carbon dioxide, and forced vital capacity. Multivariable competing risk analyses revealed that the mMRC and SGRQ score were associated with waitlist mortality in addition to age and interstitial lung disease.ConclusionsBoth mMRC dyspnea and SGRQ score were significantly associated with waitlist mortality, in addition to other clinical variables such as patients’ background, underlying disease, and pulmonary function. Patient-reported dyspnea and health may be measured through multi-dimensional analysis (including subjective perceptions) and for risk stratification regarding waitlist mortality.

Impact of the New French Heart Allocation System on Post-Transplant Mortality

<h3>Purpose</h3> The goal of the new French heart allocation system launched on January 2018 was to minimize death on the waiting list without detrimental effect on post-transplant outcome. The new system is based on the candidate risk score (CRS) considering donor-recipient matching and post-transplant risk of death as well as the distance between procurement and transplant centers. Exceptions to the score have been implemented for adults for whom the CRS does not accurately predict waitlist mortality. This study aimed to compare recipients' profile and survival under the old and new allocation systems. <h3>Methods</h3> The study included all patients undergoing transplantation between January 2014 and June 2019 (n=2520) listed on the national registry CRISTAL. The main outcome was 6-month post-transplant mortality. Survival curves were estimated using the Kaplan-Meier method and compared between the old allocation system (2014-2017, N=1838) and the new system (2018-2019, N=682) using the log-rank test. To evaluate the independent effect of the period on post-transplant mortality, we used a multivariable Cox proportional hazard model adjusting on post-transplant mortality risk factors. <h3>Results</h3> Recipients from the new system (n=682) were more likely to be supported with VA-ECMO (29.6% vs 18.3%, p=0.01) and ventilator (10.6% VS 7.6%, p=0.02) and less likely to be on inotrope infusion (13.2% vs 26.2%, p<0.01). Six-month post-transplant survival rate did not differ between 2018-2019 and 2014-2017 (81.0% vs 81.8%, p=0.8) (Figure 1). In a multivariable Cox model including post-transplant mortality risk factors (recipient age, indication, mechanical ventilation, GFR, Inotropic infusion, history of cardiac surgery, diabetes mellitus and donor age), no association was found between period and 6-month post-transplant mortality (HR=1.0 95%CI : 0.8-1.2; p=0.9). <h3>Conclusion</h3> The new French heart allocation system has resulted in higher rate of recipients supported with VA-ECMO without change in 6-month post-transplant Survival.

Validating a novel score based on interaction between ACLF grade and MELD score to predict waitlist mortality

Among candidates listed for liver transplant (LT), the model for end-stage liver disease (MELD) score may not capture acute-on-chronic liver failure (ACLF) severity. Data on the interaction between ACLF and MELD score in predicting waitlist mortality are scarce. We analyzed the UNOS database (01/2002 to 06/2018) for LT listings in adults with cirrhosis and ACLF (without hepatocellular carcinoma). ACLF grades 1, 2, 3a, and 3b- were defined using the modified EASL-CLIF criteria. Of 18,416 candidates with ACLF at listing (mean age 54 years, 69% males, 63% Caucasians), 90-day waitlist mortality (patient death or being too sick for LT) was 21.6% (18%, 20%, 25%, and 39% for ACLF grades 1, 2, 3a, and 3b, respectively). Using a Fine and Gray regression model, we identified an interaction between MELD and ACLF grade, with ACLF having a higher impact at lower MELD scores. Other variables included candidate's age, sex, liver disease etiology, listing MELD, ACLF grade, obesity, and performance status. A score developed using parameter estimates from the interaction model on the derivation cohort (n = 9,181) stratified the validation cohort (n= 9,235) into quartiles: Q1 (score <10.42), Q2 (10.42-12.81), Q3 (12.82-15.50), and Q4 (>15.50). Waitlist mortality increased with each quartile from 13%, 18%, 23%, and 36%, respectively. Observed vs. expected waitlist mortality deciles in the validation cohort showed good calibration (goodness of fit p= 0.98) and correlation (R= 0.99). Among selected candidates who have ACLF at listing, MELD score and ACLF interact in predicting cumulative risk of 90-day waitlist mortality, with higher impact of ACLF grade at lower listing MELD score. Validating these findings in large prospective studies will support consideration of both MELD and ACLF when prioritizing transplant candidates and allocating liver grafts. In patients with cirrhosis listed for liver transplantation, the presence of multiorgan failure, a condition referred to as acute-on-chronic liver failure, is associated with high waiting list mortality rates. Current organ allocation policy disadvantages patients with this condition. This study describes and validates a new scoring method that performs better than the currently available scoring systems. Further validation of this approach may reduce the deaths of patients with cirrhosis and acute-on-chronic liver failure on the transplant waiting list.

Identifying an Optimal Liver Frailty Index Cutoff to Predict Waitlist Mortality in Liver Transplant Candidates.

Frailty, as measured by the Liver Frailty Index (LFI), is associated with liver transplant (LT) waitlist mortality. We sought to identify an optimal LFI cutoff that predicts waitlist mortality. Adults with cirrhosis awaiting LT without hepatocellular carcinoma at nine LT centers in the United States with LFI assessments were included. Multivariable competing risk analysis assessed the relationship between LFI and waitlist mortality. We identified a single LFI cutoff by evaluating the fit of the competing risk models, searching for the cutoff that gave the best model fit (as judged by the pseudo-log-likelihood). We ascertained the area under the curve (AUC) in an analysis of waitlist mortality to find optimal cutoffs at 3, 6, or 12 months. We used the AUC to compare the discriminative ability of LFI+Model for End Stage Liver Disease-sodium (MELDNa) versus MELDNa alone in 3-month waitlist mortality prediction. Of 1,405 patients, 37 (3%), 82 (6%), and 135 (10%) experienced waitlist mortality at 3, 6, and 12 months, respectively. LFI was predictive of waitlist mortality across a broad LFI range: 3.7-5.2. We identified an optimal LFI cutoff of 4.4 (95% confidence interval [CI], 4.0-4.8) for 3-month mortality, 4.2 (95% CI, 4.1-4.4) for 6-month mortality, and 4.2 (95% CI, 4.1-4.4) for 12-month mortality. The AUC for prediction of 3-month mortality for MELDNa was 0.73; the addition of LFI to MELDNa improved the AUC to 0.79. LFI is predictive of waitlist mortality across a wide spectrum of LFI values. The optimal LFI cutoff for waitlist mortality was 4.4 at 3 months and 4.2 at 6 and 12 months. The discriminative performance of LFI+MELDNa was greater than MELDNa alone. Our data suggest that incorporating LFI with MELDNa can more accurately represent waitlist mortality in LT candidates.

Use of Skeletal Muscle Index as a Predictor of Wait-List Mortality in Patients With End-Stage Liver Disease.

The aim of this study is to validate a proposed definition of sarcopenia in predicting wait-list mortality. We retrospectively evaluated 355 adults (age ≥18 years) with cirrhosis listed for first-time LT from January 1, 2010, to April 1, 2018 from our center. Demographic, laboratory, and outcome data were collected in conjunction with computed tomography scans performed within 3months of listing. Using imaging analysis software, the skeletal muscle index (SMI), which is a marker for sarcopenia-related mortality, was calculated. A survival analysis was performed to evaluate the association of the proposed sarcopenia definition of SMI<50cm2 /m2 for men or <39cm2 /m2 for women with wait-list mortality or delisting. Median SMI was 54.1cm2 /m2 (range, 47-60cm2 /m2 ). A total of 61 (17.2%) patients exhibited sarcopenia according to the proposed threshold, and 24.6% (57/232) of men were sarcopenic compared with 3.3% (4/123) of women (P<0.001). Mean (standard deviation [SD]) SMI was also higher for men (56.6±9.6 cm2 /m2 ) than for women (50.7±8.0 cm2 /m2 ; P<0.001). Median follow-up time among patients was 2.1 months (0-12 months), and 30 events were observed (hazard ratio, 0.98; 95% confidence interval, 0.95-1.02; P=0.41). There was no statistically significant difference in time on the waiting list between patients with and without sarcopenia (P=0.89) as defined at the threshold. Using the prespecified definitions of sarcopenia based on SMI, there was no statistically significant difference in mortality and delisting from the transplant waiting list between patients with and without sarcopenia in this population. Practice and region-specific patterns for pretransplant selection and median Model for End-Stage Liver Disease at transplant may affect SMI as a predictor of wait-list mortality.

Clinical judgment versus lung allocation score in predicting lung transplant waitlist mortality.

Canadian lung transplant centers currently use a subjective and dichotomous "Status" ranking to prioritize waitlisted patients for lung transplantation. The lung allocation score (LAS) is an objective composite score derived from clinical parameters associated with both waitlist and post-transplant survival. We performed a retrospective cohort study to determine whether clinical judgment (Status) or LAS better predicted waitlist mortality. All adult patients listed for lung transplantation between 2007 and 2012 at three Canadian lung transplant programs were included. Status and LAS were compared in their ability to predict waitlist mortality using Cox proportional hazards models and C-statistics. Status and LAS were available for 1122 patients. Status 2 patients had a higher LAS compared to Status 1 patients (mean 40.8 (4.4) vs 34.6 (12.5), P=.0001). Higher LAS was associated with higher risk of waitlist mortality (HR 1.06 per unit LAS, 95% CI 1.05, 1.07, P<.001). LAS predicted waitlist mortality better than Status (C-statistic 0.689 vs 0.674). Patients classified as Status 2 and LAS≥37 had the worst survival awaiting transplant, HR of 8.94 (95% CI 5.97, 13.37). LAS predicted waitlist mortality better than Status; however, the best predictor of waitlist mortality may be a combination of both LAS and clinical judgment.

Validation of the French Index for the Prediction of Waitlist Mortality in a New Cohort of Candidates

We derived and validated from the cohort of patients registered on the national registry CRISTAL, between January 2010 and December 2014, the Candidate Risk Score (CRS), predicting waitlist mortality. The CRS, converted into the Cardiac Risk Index (CRI), ranging from 0 to 40, includes 4 variables, venoarterial extracorporeal membrane oxygenator (VA-ECMO) use, plasma concentrations of natriuretic peptides (NP), glomerular filtration rate (GFR) and total serum bilirubin level. This study aimed to validate the CRI within the cohort of candidates listed on the CRISTAL registry between January 2018 and March 2019. All patients, aged 16 years or older, registered on the national registry CRISTAL, for heart transplantation, between January 2018 and March 2019, without score exception, (N=617) were included. The main outcome was 3-month waitlist mortality or delisting for worsening medical condition. Survival curves were estimated using Kaplan Meier method. Three-month survival curves stratified by CRI category were compared with the log rank test. The CRI calibration was assessed by calculating the correlation between the observed and predicted 3-month mortality by CRI decile. The slope of the calibration straight line was calculated. The CRI showed a good discriminative capacity with 3-month survival ranging from 34.8% [17.7%-52.6%] and 63.4% [43.0%-78.2%] in the highest (35-40) and second highest (30-34) CRI categories to 97.7% [93.1%-99.3%] and 93.4% [84.7%-97.2%] in the lowest (0-14) and second lowest (15-20) CRI categories(Figure). The correlation between predicted and observed 3-month waitlist mortality was excellent (r=0.90) and the slope of the calibration straight line was 0.93. This study validates the use of the CRI as a predictor of waitlist mortality in adult candidates. Currently the CRI is the cornerstone of the French heart allocation system.

Standardized measures of frailty predict hospital length of stay following orthotopic liver transplantation for hepatocellular carcinoma.

Frailty in liver transplant (LT) waitlisted patients has been shown to predict waitlist mortality. While not currently used to allocate organs, the relationship between preoperative frailty and postoperative outcomes following orthotopic LT needs further elucidation. We determined the frailty status of 50 OLT candidates listed for hepatocellular carcinoma (HCC) and examined relationships between frailty and outcomes on the waitlist and, if transplanted, 30-day mortality, hospital length of stay (LOS), ICU LOS, and several other secondary outcomes. The overall prevalence of frailty was 30%, and the median natural MELD score for patients was 13. The overall hospital LOS for the frail group was longer (14.5days [IQR 12-19]) as compared to the non-frail group (8days [IQR 7-13]); P=.015. Groups also differed in the time to their first PT session (6days [IQR 4-15] for the frail vs 4days [IQR 3-7] for the non-frail patients; P=.042). There was no statistically significant difference in other outcomes measures, including ICU LOS and 30-day mortality. Frailty in OLT patients with diagnosed HCC is a predictor of longer hospital stay and longer time to the first completed PT session independent of preoperative MELD scores.

Incidence and risk factors for mortality in patients with cirrhosis awaiting liver transplantation

Aim: This study aimed to determine the mortality in Indian patients awaiting liver transplantation and to assess the impact of cirrhosis-related complications (CRCs) on mortality. Materials and Methods: This was a prospective study on patients of Indian origin, aged >18 years, with cirrhosis liver (confirmed by imaging and/or liver biopsy), and registered for liver transplant (LTx) between November 2015 and May 2016. Patients were followed up for at least a year. Any admission or day-care procedure for complications after registration was recorded as an event, and outcome was noted as recovered, deterioration, or death. The primary end point of the study was LTx, survival, or death. Patients undergoing transplantation were grouped with survivors for analysis of factors predicting waitlist mortality. Statistics: t-test, Chi-square test, Mann–Whitney U-test, and univariate and logistic regression analyses were used for statistical analysis. P

Objective Versus Subjective Assessment of Functional Status in Candidates for Liver Transplantation

Introductionand aim. Poor functional status is associated with increased mortality in cirrhosis patients awaiting liver transplantation (LT); however, the optimal assessment of functional status remains unknown. This study sought to determine the relationship between 6-minute walk distance (6MWD) and Karnofsky Performance Status (KPS) and their association with waitlist mortality in LT candidates. Material and methodsTwo hundred seventy-eight consecutive patients listed for LT were included. KPS and 6MWD were assessed at the time of evaluation. KPS was recorded as a percentage from 0 to 100, with 0 representing death and 100 representing no presence of disease. Patients were followed from time of listing until transplantation, death, removal from the waitlist or end of the study period. ResultsThe mean KPS and 6MWD were 77.4 ± 13.5 and 323.6 ± 163.9 m, respectively. A mild correlation between 6MWD and KPS was demonstrated (Spearman ρ = 0.4317, P < .0001). KPS was significantly lower in patients with 6MWD < 250 meters (P < .0001). The 6MWD was significantly lower in patients who suffered waitlist mortality (266.1 vs 331.8 m, P = .05). ConclusionIn conclusion, 6MWD is a better predictor of waitlist mortality than KPS score in candidates for LT. The addition of 6MWD as a standard assessment may help to identify patients at risk of dying on the waitlist.

THU-247 - Number of organ failures is a better predictor of waitlist mortality in those who die within 30 days of listing for liver transplantation

THU-247 - Number of organ failures is a better predictor of waitlist mortality in those who die within 30 days of listing for liver transplantation

Mechanical Circulatory Support Device Utilization and Heart Transplant Waitlist Outcomes in Patients With Restrictive and Hypertrophic Cardiomyopathy.

Patients with restrictive cardiomyopathy (RCM) and hypertrophic cardiomyopathy (HCM) generally are considered poor candidates for mechanical circulatory support devices (MCSDs) and often not able to be bridged mechanically to heart transplantation. This study characterized MCSD utilization and transplant waitlist outcomes in patients with RCM/HCM under the current allocation system and discusses changes in the era of the new donor allocation system. Patients waitlisted from 2006 to 2016 in the United Network for Organ Sharing registry were stratified by RCM/HCM versus other diagnoses. MCSD utilization and waitlist duration were analyzed by propensity score models. Waitlist outcomes were assessed by cumulative incidence functions with competing events. Predictors of waitlist mortality or delisting for worsening status in patients with RCM/HCM were identified by proportional hazards model. Of 30 608 patients on the waitlist, 5.1% had RCM/HCM. Patients with RCM/HCM had 31 fewer waitlist days (P<0.01) and were ≈26% less likely to receive MCSD (P<0.01). Cumulative incidence of waitlist mortality was similar between cohorts; however, patients with RCM/HCM had higher incidence of heart transplantation. Predictors of waitlist mortality or delisting for worsening status in patients with RCM/HCM without MCSD support included estimated glomerular filtration rate <60 mL/min per 1.73 m2, pulmonary capillary wedge pressure >20 mm Hg, inotrope use, and subjective frailty. Patients with RCM/HCM are less likely to receive MCSD but have similar waitlist mortality and slightly higher incidence of transplantation compared with other patients. The United Network for Organ Sharing RCM/HCM risk model can help identify patients who are at high risk for clinical deterioration and in need of expedited heart transplantation.

The Liver Frailty Index Improves Mortality Prediction of the Subjective Clinician Assessment in Patients With Cirrhosis.

Frailty, a critical determinant of health outcomes, is most commonly assessed in patients with cirrhosis by general clinician assessment that is limited by its subjectivity. We aimed to compare the objective Liver Frailty Index (LFI), consisting of three performance-based tests (grip, chair stands, balance), with a subjective hepatologist assessment. Outpatients with cirrhosis awaiting liver transplantation (LT) underwent: (1) objective measurement using the LFI and (2) subjective clinician assessment. Spearman's correlation assessed associations between the LFI and clinician assessment; Cox regression with waitlist mortality (death/delisting for sickness); discriminative ability with Concordance(C) statistics. The net reclassification index evaluated the percentage of patients correctly reclassified by adding the LFI to the clinician assessment. Of the 529 patients with cirrhosis, median LFI was 3.8 (range 1.0-7.0) and clinician assessment was 3 (range 0-5). Correlation between LFI and the clinician assessment was modest (ρ=0.38) with high variability by hepatologist (ρ=0.26-0.70). At a median of 11 months, 102 (19%) died/were delisted. Both the LFI (hazard ratio (HR) 2.2, 95% confidence interval (CI) 1.7-2.9) and clinician assessment (HR 1.6, 95% CI 1.3-1.9) were associated with adjusted waitlist mortality risk (P<0.01). The addition of the LFI to the clinician assessment significantly improved mortality prediction over the clinician assessment alone (0.74 vs. 0.68; P=0.02). Compared with the clinician assessment alone, the addition of the LFI correctly reclassified 34% (95% CI 8-53%) of patients to their correct survival status. The subjective clinician assessment can predict waitlist mortality in patients with cirrhosis but is subjective and variable by hepatologist. The addition of the LFI to the subjective clinician assessment significantly improved mortality risk prediction, reclassifying 34% of patients. Our data strongly support the incorporation of the objective LFI to anchor our assessments of patients with cirrhosis to enhance our decision-making.