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Cardiovascular disease is the leading cause of mortality following kidney transplantation. Heart failure affects 17–21% of patients with chronic kidney disease and increases along with time receiving dialysis. The Seattle Heart Failure Model (SHFM) is a validated mortality risk model for heart failure patients that incorporates clinical, therapeutic, and laboratory parameters but does not include measures of kidney function. We applied the SHFM to patients with end-stage renal disease (ESRD) who were being evaluated for kidney transplantation to determine if the model was associated with post-transplant mortality. This retrospective single-center study analyzed survival among 360 adult deceased-donor kidney transplant recipients. Cox regression was used to model post-transplant patient survival. Our findings indicated that a 1.0-point increase in the adapted SHFM score was significantly associated with post-transplant mortality (HR 1.76, 95% CI = 1.10–2.83, p = 0.02), independently of the Kidney Donor Profile Index and Estimated Post-Transplant Survival. Individual covariates of the SHFM were evaluated in univariate analyses, and age, sodium, cholesterol, and lymphocyte count were significantly related to mortality. This study provides preliminary evidence that an adapted SHFM score could be a useful tool in evaluating mortality risk post-transplant in patients with ESRD. [ABSTRACT FROM AUTHOR]

Background: Deficiency in vitamin D3 and its metabolites has been linked to dismal outcomes in patients with chronic diseases, including cardiovascular disease and heart failure (HF). It remains unclear if a vitamin D3 status is a prognostic feature in patients with acute decompensated HF. Methods: We assessed serum levels of 25-OH-vitamin D3 and 1,25-(OH)2-vitamin D3 in 139 patients with acute HF who had been admitted to the intermediate care unit of a maximum care hospital. The follow-up period was one year. After exclusion of patients with sampling errors and those who were lost to follow-up, 118 patients remained in the final study cohort. Outcome estimates by 25-OH-vitamin D3 and 1,25-(OH)2-vitamin D3 levels were compared to the Seattle Heart Failure (SHF) Model. Results: More than two-thirds (79.7%) of the patients showed inadequate 25-OH-vitamin D3 levels (i.e., <30 ng/mL) upon admission. Low levels of 1,25-(OH)2-vitamin D3 (i.e., <19.9 pg/mL) were observed in 16.1% of patients. Of the 118 HF patients, 22 (19%) died during the following 12 months. There were no differences in vitamin D3 levels between patients who died and those who survived, neither in 25-OH-vitamin D3 (23.37 ± 19.14 ng/mL vs. 19.11 ± 12.25 ng/mL; p = 0.19) nor in 1,25-(OH)2-vitamin D3 levels (31.10 ± 19.75 ng/mL vs. 38.25 ± 15.73 ng/mL; p = 0.02); therefore, vitamin D3 levels alone did not predict one-year survival (AUC [25-OH-vitamin D3] 0.50; 95% CI 0.34–0.65; AUC [1,25-(OH)2-vitamin D3] 0.62; 95% CI 0.48–0.76). Moreover, whilst the SHF model exhibited acceptable discriminatory ability for predicting one-year mortality (AUC 0.79; 95% CI 0.66–0.91), adding vitamin D levels on admission to the SHF score did not improve its discriminatory value. Conclusion: Our data do not support the use of vitamin D3 screening in patients admitted with acute decompensated HF to aid prognostication. [ABSTRACT FROM AUTHOR]

BackgroundScore-based survival prediction in patients with advanced heart failure (HF) is complicated. Easy-to-use prognostication tools could inform clinical decision-making and palliative care delivery.ObjectiveTo compare the prognostic utility of the Seattle HF model (SHFM), the surprise question (SQ), and the number of HF hospitalizations (NoH) within the last 12 months for predicting 1-year survival in patients with advanced HF.MethodsWe retrospectively analyzed data from a cluster-randomized controlled trial of advanced HF patients, predominantly with reduced ejection fraction. Primary outcome was the prognostic discrimination of SHFM, SQ (“Would you be surprised if this patient were to die within 1 year?”) answered by HF cardiologists, and NoH, assessed by receiver operating characteristic (ROC) curve analysis. Optimal cut-offs were calculated using Youden’s index (SHFM:

Background: Heart failure (HF) is a highly prevalent, heterogeneous, and life-threatening condition. Precise prognostic understanding is essential for effective decision making, but little is known about patients' attitudes toward prognostic communication with their physicians.Methods and Results: We conducted a questionnaire survey, consisting of patients' prognostic understanding, preferences for information disclosure, and depressive symptoms, among hospitalized patients with HF (92 items in total). Individual 2-year survival rates were calculated using the Seattle Heart Failure Model, and its agreement level with patient self-expectations of 2-year survival were assessed. A total of 113 patients completed the survey (male 65.5%, median age 75.0 years, interquartile range 66.0-81.0 years). Compared with the Seattle Heart Failure Model prediction, patient expectation of 2-year survival was matched only in 27.8% of patients; their agreement level was low (weighted kappa = 0.11). Notably, 50.9% wished to know "more," although 27.7% felt that they did not have an adequate prognostic discussion. Compared with the known prognostic variables (eg, age and HF severity), logistic regression analysis demonstrated that female and less depressive patients were associated with patients' preference for "more" prognostic discussion.Conclusions: Patients' overall prognostic understanding was suboptimal. The communication process requires further improvement for patients to accurately understand their HF prognosis and be involved in making a better informed decision. [ABSTRACT FROM AUTHOR]

Background: MitraClip ® (MC) is an established procedure for severe mitral regurgitation (MR) in patients deemed unsuitable for surgery.Right ventricular dysfunction (RVD) is associated with a higher mortality risk. The prognostic accuracy of heart failure risk scores like the Seattle heart failure model (SHFM) and Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score in pts undergoing MC with or without RVD has not been investigated so far. Methods: SHFM and MAGGIC score were calculated retrospectively. RVD was determined as tricuspid annular plane systolic excursion (TAPSE) ≤15 mm. Area under receiver operating curves (AUROC) of SHFM and MAGGIC were performed for one-year all-cause mortality after MC. Results: N = 103 pts with MR III° (73 ± 11 years, LVEF 37 ± 17%) underwent MC with a reduction of at least I° MR. One-year mortality was 28.2%.In Kaplan-Meier analysis, one- year mortality was significantly higher in RVD-pts (34.8% vs 2.8%, p = 0.009).Area under the Receiver Operating Characteristic (AUROC) for SHFM and MAGGIC were comparable for both scores (SHFM: 0.704, MAGGIC: 0.692). In pts without RVD, SHFM displayed a higher AUROC and therefore better diagnostic accuracy (SHFM: 0.776; MAGGIC: 0.551, p

This quality improvement project utilized a risk stratification process and an advance care planning (ACP) tool to identify patients at high risk of death and prompt ACP discussions and documentation of health care preferences in the electronic health record. Inherent uncertainty in heart failure (HF) prognostication and provider time constraints impede initiation of timely ACP discussions. In an effort to mitigate these obstacles, the Seattle Heart Failure Model was utilized to calculate mortality risk for 195 patients in an ambulatory HF clinic. Next, a HF-specific ACP tool, developed for this project, was used to prompt and guide ACP discussions with patients determined to have a prognosis of life expectancy of 3 years or less. The project yielded a 35% completion of ACP tools over 3 months, with 100% of these entered into the electronic health record. Postimplementation surveys suggest clinic staff believe a comprehensive and systematic approach to ACP services facilitates timely ACP discussions and decision making in the outpatient setting. [ABSTRACT FROM AUTHOR]

Patient-reported quality of life (PRQL) is a primary therapeutic target for patients with chronic heart failure (HF) and is associated with long-term prognosis. However, its utility in hospitalized HF (HHF) patients in the acute setting remains unclear. We aimed to assess the utility of PRQL (the Kansas City Cardiomyopathy Questionnaire [KCCQ]) in HHF patients and its association with long-term prognosis as well as with the clinical risk score (Get With The Guidelines-Heart Failure [GWTG-HF] risk score). PRQL was evaluated using the KCCQ in consecutive 114 HHF patients. Its association with the composite outcome of all-cause mortality or HF readmission within the first year after discharge was analyzed. Furthermore, its distribution by the clinical risk score (GWTG-HF) was evaluated using Pearson's correlation coefficient. The median KCCQ was 34.9, but was widely distributed (interquartile range 23.7–56.8). After adjustment for known prognostic indicators, the KCCQ was not an independent predictor of the composite outcome within the first year (group with high vs. low KCCQ scores: hazard ratio, 0.67; 95% confidence interval 0.26–1.71). There was no significant correlation between the KCCQ and the GWTG-HF risk score. In conclusion, PRQL during the acute phase of HF was significantly impaired and also varied widely, irrespective of patient characteristics or severity. PRQL assessment and risk prediction for HHF patients in the acute setting seemed to provide two distinct types of information for health care providers. [ABSTRACT FROM AUTHOR]

Background: Precise risk stratification in heart failure (HF) patients enables clinicians to tailor the intensity of their management. The Seattle Heart Failure Model (SHFM), which uses conventional clinical variables for its prediction, is widely used. We aimed to externally validate SHFM in Japanese HF patients with a recent episode of acute decompensation requiring hospital admission.Methods and Results: SHFM was applied to 2470 HF patients registered in the West Tokyo Heart Failure and National Cerebral And Cardiovascular Center Acute Decompensated Heart Failure databases from 2006 to 2016. Discrimination and calibration were assessed with the use of the c-statistic and calibration plots, respectively, in HF patients with reduced ejection fraction (HFrEF; <40%) and preserved ejection fraction (HFpEF; ≥40%). In a perfectly calibrated model, the slope and intercept would be 1.0 and 0.0, respectively. The method of intercept recalibration was used to update the model. The registered patients (mean age 74 ± 13 y) were predominantly men (62%). Overall, 572 patients (23.2%) died during a mean follow-up of 2.1 years. Among HFrEF patients, SHFM showed good discrimination (c-statistic = 0.75) but miscalibration, tending to overestimate 1-year survival (slope = 0.78; intercept = -0.22). Among HFpEF patients, SHFM showed modest discrimination (c-statistic = 0.69) and calibration, tending to underestimate 1-year survival (slope = 1.18; intercept = 0.16). Intercept recalibration (replacing the baseline survival function) successfully updated the model for HFrEF (slope = 1.03; intercept = -0.04) but not for HFpEF patients.Conclusions: In Japanese acute HF patients, SHFM showed adequate performance after recalibration among HFrEF patients. Using prediction models to tailor the care for HF patients may improve the allocation of medical resources. [ABSTRACT FROM AUTHOR]

Aims: Heart failure hospitalization is a sentinel event associated with increased mortality risk. Whether long‐term heart failure risk models such as the Seattle Heart Failure Model (SHFM) accurately assess risk in the post‐hospital setting is unknown. Methods and results: The SHFM was applied to a cohort of 2242 consecutive patients (50% women; mean age 73) on discharge after acute heart failure hospitalization and analysed for the primary endpoint of all‐cause mortality. Model discrimination and calibration were assessed. Direct patient‐level comparison between our study cohort and the original SHFM cohorts was also performed to confirm and quantify the degree and extent of increased mortality risk attributable to post‐hospital status. The SHFM demonstrated good overall risk discrimination (area under the receiver operating characteristic curve 0.704) and was well calibrated in patients <65 years old. The SHFM significantly underestimated mortality risk in patients ≥65 years old post‐hospitalization. Direct patient‐level comparison revealed a stepwise increase in adjusted mortality risk attributable to post‐hospital status for each advancing age group ≥65 years old. This heightened mortality risk showed a diminishing trend over 18 months after discharge. Conclusions: The SHFM accurately predicts mortality risk in younger patients after acute heart failure hospitalization. However, patients ≥65 years old had increased adjusted mortality risk for up to 18 months after discharge compared with ambulatory heart failure patients, a pattern consistent with the well‐described post‐hospital syndrome. [ABSTRACT FROM AUTHOR]

Background: Despite the availability of validated risk scores for survival in heart failure (HF), individualized estimates are not typically provided directly to patients.Methods and Results: We explored patient perspectives regarding conveyance of individualized Seattle Heart Failure Model (SHFM) survival estimates. In 2014 and 2015, 24 HF patients completed a semistructured interview at the initial offering of SHFM survival estimates (baseline) and a follow-up interview. Themes emerging from questions of interest were identified: 1) preferences for receiving estimates: patients generally wished to see their SHFM estimates (acceptors; n = 17, and ideally would have received such information early after HF "diagnosis"; 2) reactions: viewing their personalized estimates restored some control and hope for most patients and rarely increased anxiety; 3) application: some acceptors found the information to be helpful in considering future plans, but its usefulness in specific decisions was restricted owing to perceived model limitations; 4) understanding uncertainty: participants contextualized estimates through observations that uncertainty is pervasive in life; acceptors qualitatively understood the population-based nature of the estimates.Conclusions: The majority of patients valued receiving individualized prognostic survival estimates. Acceptors generally understood the nature of the information and found it to provide clarity, control, and hope rather than invoking confusion or anxiety. [ABSTRACT FROM AUTHOR]

Aim. To assess the life prognosis in patients with chronic heart failure (CHF) – male residents of St. Petersburg – according to the Seattle Heart Failure Model (SHFM) and compare it to the observed survival. Material and methods. A retrospective survival analysis was performed in 135 patients with Functional Class (FC) II–IV CHF of ischemic aetiology. At baseline, anamnestic, clinical, functional, and instrumental data were collected. Observed five-year all-cause mortality was compared to that predicted by SHFM. Statistical analyses were performed in SPSS 15.0. Results. Over the five years of the follow-up (60 months), 67% of the participants (n=88) survived. Observed one-, two-, and five-year survival in FC II CHF patients was 95%, 92%, and 74%, respectively. In FC III CHF patients, the respective figures were 92%, 85%, and 61%. Predicted one-, two-, and five-year survival, according to the mean risk estimates by SHFM, was 98%, 95%, and 89% for FC II CHF individuals, and 96%, 92%, and 80%, respectively, for the FC III CHF participants. Therefore, for the first five years of the follow-up, the SHFM predictions exceeded the observed survival by 3–15% and 4–19% in CHF patients with FC II and FC III, respectively (p1,2< 0,05). There was a statistically significant association between the observed survival and smoking, concomitant chronic obstructive pulmonary disease, and hypertension duration before the CHF manifestation. Conclusion. The SHFM markedly overestimated the observed survival in male patients with systolic CHF – St. Petersburg residents. Therefore, in this population, this instrument cannot be recommended for the CHF prognosis assessment. There is a need to develop a survival model for Russian patients with CHF, which would incorporate additional determinants of adverse prognosis.

Background Heart failure (HF) guidelines recommend brain natriuretic peptide (BNP) and multivariable risk scores, such as the Seattle Heart Failure Model (SHFM), to predict risk in HF with reduced ejection fraction (HFrEF). A practical way to integrate information from these 2 prognostic tools is lacking. We sought to establish a SHFM+BNP risk-stratification algorithm. Methods The retrospective derivation cohort included consecutive patients with HFrEF at the Mayo Clinic. One-year outcome (death, transplantation or ventricular assist device) was assessed. The SHFM+BNP algorithm was derived by stratifying patients within SHFM-predicted risk categories (≤2.5%, 2.6% to ≤10%, >10%) according to BNP above or below 700 pg/ml and comparing SHFM-predicted and observed event rates within each SHFM+BNP category. The algorithm was validated in a prospective, multicenter HFrEF registry (Penn HF Study). Results Derivation ( n = 441; 1-year event rate 17%) and validation ( n = 1,513; 1-year event rate 12%) cohorts differed with the former being older and more likely ischemic with worse symptoms, lower EF, worse renal function and higher BNP and SHFM scores. In both cohorts, across the 3 SHFM-predicted risk strata, a BNP >700 pg/ml consistently identified patients with approximately 3-fold the risk that the SHFM would have otherwise estimated, regardless of stage of HF, intensity and duration of HF therapy and comorbidities. Conversely, the SHFM was appropriately calibrated in patients with a BNP <700 pg/ml. Conclusion The simple SHFM+BNP algorithm displays stable performance across diverse HFrEF cohorts and may enhance risk stratification to enable appropriate decision-making regarding HF therapeutic or palliative strategies. [ABSTRACT FROM AUTHOR]

Background The aim of the study was to investigate mortality following transcatheter mitral valve repair with the MitraClip System (MC) (Abbott Vascular, Santa Clara, CA, USA) in patients with mitral regurgitation and moderate-to-severe symptomatic heart failure in comparison to mortality predicted by the Seattle Heart Failure Model (SHFM) and the heart failure calculator of the meta-analysis global group in chronic heart failure (MAGGIC). Methods and results This retrospective study included 194 consecutive patients, who received a MC implantation between 2009 and 2013 at our institution. The observed mortality was compared with that predicted by the SHFM and the MAGGIC after 1 year: 24% observed, 18% by SHFM ( p = 0.185) and 20.9% by MAGGIC ( p = 0.542). At 2 years: 32% observed vs. 33% by SHFM ( p = 0.919). The subgroup of patients with end-stage heart failure and N-terminal pro-B-type natriuretic peptide (NTproBNP) >10,000 pg/ml ( n = 41) had significantly worse mortality after 1 year (49%) than predicted by SHFM (24%, p = 0.034) and MAGGIC (24.8%, p = 0.041). Conclusion In the overall patient cohort defined by 3+ to 4+ mitral valve regurgitation with New York Heart Association III and IV symptomatic heart failure, mortality following MC is consistent with that predicted by SHFM and MAGGIC for patients that are not at high risk. However, the subset of patients with severe heart failure defined by NTproBNP >10,000 pg/ml had worse than predicted mortality and may not benefit from MC therapy, mainly due to a high 30-day mortality. [ABSTRACT FROM AUTHOR]

Background Multivariable risk scores and exercise measures are well-validated risk prediction methods. Combining information from a functional evaluation and a risk model may improve accuracy of risk predictions. We analyzed whether adding exercise measures to the Seattle Heart Failure Model (SHFM) improves risk prediction accuracy in systolic heart failure. Methods We used a sample of patients from the Heart Failure and A Controlled Trial Investigating Outcomes of Exercise TraiNing (HF-ACTION) study ( http://www.clinicaltrials.gov ; unique identifier: NCT00047437) to examine the addition of peak oxygen consumption, expired volume per unit time/volume of carbon dioxide slope, 6-minute walk distance, or cardiopulmonary exercise duration to the SHFM. Multivariable Cox proportional hazards models were used to test the association between the combined end point (death, left ventricular assist device, or cardiac transplantation) and the addition of exercise variables to the SHFM. Results The sample included 2,152 patients. The SHFM and all exercise measures were associated with events (all p < 0.0001) in proportional hazards models. There was statistically significant improvement in risk estimation when exercise measures were added to the SHFM. However, the improvement in the C index for the addition of peak volume of oxygen consumption (+0.01), expired volume per unit time/volume of carbon dioxide slope (+0.02), 6-minute walk distance (–0.001), and cardiopulmonary exercise duration (+0.001) to the SHFM was small or slightly worse than the SHFM alone. Changes in risk assignment with the addition of exercise variables were minimal for patients above or below a 15% 1-year mortality. Co nclusions Exercise performance measures and the SHFM are independently useful for predicting risk in systolic heart failure. Adding cardiopulmonary exercise testing measures and 6MWD to the SHFM offers only minimal improvement in risk reassignment at clinically meaningful cut points. [ABSTRACT FROM AUTHOR]

Background: Renal dysfunction (RD) is a strong predictor of mortality in patients with heart failure (HF). However, its impact on the discrimination of the Seattle Heart Failure Model (SHFM) is poorly understood. Methods: Serum creatinine (SCr) and creatinine clearance (CrCl) were reviewed for patients from four of the six cohorts originally used to derive and validate the SHFM. Patients were followed for death. The independent prediction of adding SCr or CrCl to the SHFM was assessed using multivariable Cox proportional hazards and the incremental value for prediction by changes in the ROC curves for 1- and 2-year event prediction. Results: Among 7,146 patients (mean age 63 ± 11 years), 1,511 deaths occurred during a mean follow-up of 2.04 years. SCr and CrCl had a modest positive correlation with SHFM (r = 0.30, p = 0.002). In combination with SHFM, SCr (hazard ratio [HR] per mg/dl 1.25, 95% CI 1.13 to 1.38, p < 0.0001) and CrCl (HR per 10 ml/min 0.95, 95% CI 0.93 to 0.97, p < 0.0001) were both multivariable predictors of events. When stratified by absolute risk based on the SHFM, SCr or CrCl provided more additional information in lower risk patients and less or no additional information in higher risk patients. The addition of SCr and the SHFM*SCr, or CrCl and the SHFM*CrCl interaction to the SHFM was associated with almost no change in the 1- and 2-year area under ROC curves for the SHFM score. Conclusions: Compared with the SHFM alone, RD is independently predictive of mortality only in lower risk patients. Overall discrimination is only minimally improved with addition of SCr or CrCl to the SHFM. [Copyright &y& Elsevier]

Background: The Seattle Heart Failure Model (SHFM) is a multivariable model that uses demographic and clinical markers to predict survival in patients with heart failure. Inappropriate activation of the sympathetic nervous system, which contributes to the progression of heart failure and increased mortality, can be assessed using iodine-123 meta-iodobenzylguanidine (MIBG) cardiac imaging. This study investigated the incremental value of MIBG cardiac imaging when added to the SHFM for prediction of all-cause mortality. Methods: Survival data from 961 NYHA II-III subjects in the ADMIRE-HFX trial were included in this analysis. The predictive value of the SHFM alone and in combination with MIBG heart-to-mediastinum ratio (H/M) was compared for all-cause mortality (101 deaths during a median follow-up of 2 years). Results: The addition of H/M to the SHFM in a Cox model significantly improved risk prediction ( P < .0001), with a greater utility in higher risk SHFM patients. The observed 2-year mortality in the highest-risk SHFM subjects (rounded SHFM score of 1) was 24%, but varied from 46% with H/M <1.2 to 0% with H/M >1.8. Net reclassification improvement was 22.7% ( P < .001), with 14.9% of subjects who died reclassified into a higher risk category than suggested by SHFM score alone ( P = .01) and 7.9% of subjects who survived reclassified into a lower risk category ( P < .0001). The 2-year integrated discrimination improvement (+4.14%, P < .0001) and the 1-year area under the receiver-operator characteristic curve (+0.04, P = .026) both showed significant improvement for the combined model with H/M compared to the SHFM alone. Conclusion: The addition of MIBG imaging to the SHFM improves risk stratification, especially in higher risk patients. MIBG may have clinical utility in higher risk patients who are being considered for devices such as ICD, CRT-D, LVAD, and cardiac transplantation. [ABSTRACT FROM AUTHOR]

Abstract: Background: Fatigue is a prominent and poorly understood symptom of heart failure with reduced ejection fraction (HFrEF). The purpose of this study was to determine whether fatigue correlated with immune biomarkers and prognosis. Methods/Results: In patients with HFrEF (N = 59) and healthy controls (N = 25), we prospectively measured fatigue (Profile of Mood States), depressive symptoms (Patient Health Questionnaire-8), sleep quality (Pittsburgh Sleep Quality Index), and immune biomarkers (plasma C-reactive protein [CRP], tumor necrosis factor-α [TNFα], and interleukins [IL-6 and IL-10]). Seattle Heart Failure Model (SHFM) mortality risk scores were determined. Patients with HFrEF had significantly greater fatigue and depressive symptoms and poorer sleep quality compared to control subjects. When controlling for depressive symptoms, however, fatigue did not differ significantly between patients with HFrEF and controls. Patients with HFrEF had significantly lower levels of IL-10 compared to controls. Cytokines did not correlate significantly with fatigue, but fatigue was significantly associated with higher SHFM scores. Conclusions: Depressive symptoms were an important covariate of fatigue in patients with HFrEF. Our study findings were the first to show a positive association between fatigue and the SHFM score, indicating that fatigue was associated with poorer prognosis. [Copyright &y& Elsevier]

Abstract: Background: The Seattle Heart Failure Model (SHFM) predicts mortality in patients with heart failure, but no study has investigated model performance in subjects with cardiac resynchronization therapy (CRT). Methods and Results: Prospectively collected registry data of 427 patients with CRT were used for the evaluation of the discrimination and calibration performance of the SHFM. The primary end point was all-cause mortality. Calibration profile was assessed with the use of Hosmer-Lemeshow tests, and discrimination was assessed by calculating areas under receiver operating characteristic curves (AUCs) derived from the model. Mean (SD) age of the study population was 61.2 (11.1) years (72.6% male). During a median follow-up of 24.7 months, 16.9% (72/427) of the patients reached the primary end point, with observed outcomes of 34/303, 54/234, and 72/97 at years 1, 2, and 5, respectively. No evidence of insufficient fit was found in any calibration tests. AUC estimates in all subjects were 0.7377 (95% CI 0.6575–0.8179) at year 1, 0.7936 (95% CI 0.7317–0.8556) at year 2, and 0.7572 (95% CI 0.6455–0.8689) at year 5. Conclusions: SHFM offers an accurate prediction of survival in patients with CRT, with good observed calibration and AUC estimates indicating discrimination performance similar to those found by earlier validation studies. [Copyright &y& Elsevier]

Background: In this study we investigated whether the addition of peak oxygen consumption (VO2) improves the predictive accuracy of the Seattle Heart Failure Model (SHFM). The SHFM is a validated multivariate risk model that uses NYHA classification to assess functional capacity rather than peak oxygen consumption (VO2). Methods: Outpatients (n = 1,240) evaluated for transplant at three centers had their SHFM score calculated and peak VO2 measured. The outcomes assessed were death/LVAD/urgent transplant with censoring at the time of elective transplant. Results: Over the course of 4.0 (mean) years of observation, there were 571 events. Both the SHFM score (χ2 = 227) and peak VO2 (χ2 = 88, both p < 0.0001) were highly predictive of outcomes. The SHFM and peak VO2 were modestly correlated (r = 0.39, p < 0.0001). In a multivariate Cox model, peak VO2 added to the SHFM with a hazard ratio of 0.949 (p < 0.0001) for each 1-ml/kg/min increase. Peak VO2 improved both the net reclassification improvement and integrated discrimination index (both p ≤ 0.0002). Peak VO2 provided additive prognostic information within each SHFM score (p < 0.05). The 1-year areas under the receiver-operating characteristic curve were obtained for peak VO2 (0.645, 95% CI 0.606 to 0.684), SHFM (0.758, 95% CI 0.721 to 0.795) and SHFM with peak VO2 (0.766, 95% CI 0.731 to 0.802). The SHFM-predicted vs actual survival free of LVAD/UNOS Status 1 transplant at 1 year (86% vs 83%) and 4 years (63% vs 63%) were similar. Conclusions: The multivariate SHFM is a powerful predictor of death/LVAD/urgent transplant. Peak VO2 adds prognostic information across the spectrum of the SHFM, but changes in decision regarding transplant listing occur mainly in moderate-risk patients. [ABSTRACT FROM AUTHOR]

Background: The Heart Failure Survival Score (HFSS) risk-stratifies patients with chronic heart failure (CHF) referred for heart transplantation using 7 parameters, including peak VO2. The Seattle Heart Failure Model (SHFM) is a 20-variable model that combines clinical, laboratory and therapeutic data. Although both models have excellent accuracy, only the HFSS was derived and validated in patients referred for transplantation, and the HFSS and SHFM have not been directly compared. Methods: We tested the accuracy of the SHFM and compared the HFSS and SHFM in 715 patients referred for heart transplantation. Results: Over a follow-up of 962 ± 912 days, 354 patients died or received an urgent heart transplantation or a ventricular assist device. One-year event-free survival was 89%, 72% and 60%, respectively, for the low-, medium- and high-risk HFSS strata, and 93%, 76%, and 58%, respectively, for the low-, medium- and high-risk SHFM strata. The HFSS and SHFM were modestly correlated (R = −0.48, p < 0.001). In receiver operating characteristic curve analysis, areas under the curves (AUCs) for the HFSS and SHFM were comparable (1 year: 0.72 vs 0.73; 2-year: 0.70 vs 0.74, respectively) and incremental to New York Heart Association class. The 1- and 2-year combined HFSS+SHFM AUCs were 0.77 and 0.76, respectively, significantly better than the HFSS or SHFM alone. Conclusions: The HFSS and SHFM provide accurate and comparable risk stratification in CHF patients referred for transplantation. Combining the HFSS and SHFM improves predictive ability. [ABSTRACT FROM AUTHOR]

Background: Left ventricular assist devices (LVADs) are increasingly used in advanced heart failure patients. Despite proven efficacy, optimal timing of LVAD implantation is not well defined. Methods: Patients receiving an LVAD were prospectively recorded. Laboratory and clinical data were extracted and used to calculate the predicted survival with medical therapy using the Seattle Heart Failure Model (SHFM). This was compared with observed survival, hospital length of stay and timeliness of discharge. Results: We identified 104 patients. Survival with an LVAD vs SHFM predicted survival was 69% vs 11% at 1 year, corresponding to a hazard ratio of 0.17 (p < 0.0001). SHFM-estimated 1-year survival with medical therapy increased from 4% in 1997 to 2004 to 25% in 2007–2008 (p < 0.0001). Subgroup analysis of higher vs lower risk LVAD patients showed observed 1-year survival of 83% vs 57% (p = 0.04). The lower risk group had a shorter length of stay (46 vs 75 days, p = 0.03), along with higher rates of discharge prior to transplant (88% vs 61%, p = 0.01) and discharge within 60 days of LVAD placement (77% vs 52%, p = 0.03). Conclusions: The SHFM allows prediction of important features of a patient''s hospital course post-operatively, including length of stay and 1-year survival. Given evidence of improved survival and shorter hospital stay in lower risk patients, earlier LVAD placement based on a prediction model like the SHFM should be considered in advanced heart failure patients. The SHFM may have utility as a virtual control arm for single-arm LVAD trials. [Copyright &y& Elsevier]

Abstract: Background: Multi-marker risk scores accurately predict prognosis in heart failure patients but calculation is complex. Aims: To compare the prognostic accuracy of the Seattle Heart Failure Survival Score (SHFS) and a model derived from the CHARM programme, with laboratory parameters NT-proBNP and glomerular filtration rate (GFR). Methods and results: In a sample of 290 heart failure patients, 39 patients died, 22 were hospitalised with acute heart failure and 4 underwent urgent cardiac transplantation during a median follow-up of 498 days. NT-proBNP, GFR, CHARM and SHFS showed an AUC for an endpoint during 1-year of 0.80, 0.72, 0.79 and 0.69, respectively. The hazard ratio for an endpoint during follow-up was 2.1, 2.6, 1.9 and 2.1 per 1 SD increase of log NT-proBNP and CHARM and per 1 SD decrease of GFR and SHFS, respectively. In multivariate analysis, log NT-proBNP and GFR added independent prognostic information to CHARM and SHFS, respectively. Conclusion: NT-proBNP and GFR independently predicted endpoint-free survival in systolic heart failure patients, with NT-proBNP being superior and equally predictive to the SHFS and CHARM score, respectively. Assessment of both laboratory markers can simplify prognostic stratification, addition to multi-marker scores should be evaluated. [Copyright &y& Elsevier]

Background: Score-based survival prediction in patients with advanced heart failure (HF) is complicated. Easy-to-use prognostication tools could inform clinical decision-making and palliative care delivery., Objective: To compare the prognostic utility of the Seattle HF model (SHFM), the surprise question (SQ), and the number of HF hospitalizations (NoH) within the last 12 months for predicting 1-year survival in patients with advanced HF., Methods: We retrospectively analyzed data from a cluster-randomized controlled trial of advanced HF patients, predominantly with reduced ejection fraction. Primary outcome was the prognostic discrimination of SHFM, SQ ("Would you be surprised if this patient were to die within 1 year?") answered by HF cardiologists, and NoH, assessed by receiver operating characteristic (ROC) curve analysis. Optimal cut-offs were calculated using Youden's index (SHFM: <86% predicted 1-year survival; NoH ≥ 2)., Results: Of 535 subjects, 82 (15.3%) had died after 1-year of follow-up. SHFM, SQ, and NoH yielded a similar area under the ROC curve [SHFM: 0.65 (0.60-0.71 95% CI); SQ: 0.58 (0.54-0.63 95% CI); NoH: 0.56 (0.50-0.62 95% CI)] and similar sensitivity [SHFM: 0.76 (0.65-0.84 95% CI); SQ: 0.84 (0.74-0.91 95% CI); NoH: 0.56 (0.45-0.67 95% CI)]. As compared to SHFM, SQ had lower specificity [SQ: 0.33 (0.28-0.37 95% CI) vs. SHFM: 0.55 (0.50-0.60 95% CI)] while NoH had similar specificity [0.56 (0.51-0.61 95% CI)]. SQ combined with NoH showed significantly higher specificity [0.68 (0.64-0.73 95% CI)]., Conclusion: SQ and NoH yielded comparable utility to SHFM for 1-year survival prediction among advanced HF patients, are easy-to-use and could inform bedside decision-making., Competing Interests: SP is a consultant to Cordio Medical Ltd., and has received consulting fees from Abbott, CareDx, Medtronic, NuPulse, Procyrion, and Transmedics. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Blum, Gelfman, McKendrick, Pinney and Goldstein.)

Objectives: We built and validated a new heart failure (HF) prognostic model which integrates cardiopulmonary exercise test (CPET) parameters with easy-to-obtain clinical, laboratory, and echocardiographic variables., Background: HF prognostication is a challenging medical judgment, constrained by a magnitude of uncertainty., Methods: Our risk model was derived from a cohort of 2716 systolic HF patients followed in 13 Italian centers. Median follow up was 1041days (range 4-5185). Cox proportional hazard regression analysis with stepwise selection of variables was used, followed by cross-validation procedure. The study end-point was a composite of cardiovascular death and urgent heart transplant., Results: Six variables (hemoglobin, Na(+), kidney function by means of MDRD, left ventricle ejection fraction [echocardiography], peak oxygen consumption [% pred] and VE/VCO2 slope) out of the several evaluated resulted independently related to prognosis. A score was built from Metabolic Exercise Cardiac Kidney Indexes, the MECKI score, which identified the risk of study end-point with AUC values of 0.804 (0.754-0.852) at 1year, 0.789 (0.750-0.828) at 2years, 0.762 (0.726-0.799) at 3years and 0.760 (0.724-0.796) at 4years., Conclusions: This is the first large-scale multicenter study where a prognostic score, the MECKI score, has been built for systolic HF patients considering CPET data combined with clinical, laboratory and echocardiographic measurements. In the present population, the MECKI score has been successfully validated, performing very high AUC., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)