Miller, Wayne L.

Background: Blood volume (BV) in patients with chronic heart failure (HF) is characterized by heterogeneity in volume profiles; one profile being "normal BV". While overall intravascular volume may be considered normal clinically, the relative contributions of red blood cell (RBC) mass and plasma volume (PV) may not be. Objective: Assess how normal is a "normal BV" based on quantitative measures of RBC mass and PV. Methods: Retrospective analysis was undertaken in 395 patients with Class II-III HF. BV was quantitated using indicator-dilution methodology. Cohort was stratified by normal and hypervolemic BV. Results: Of the cohort, 31% (123/395) demonstrated normal total BV and 62% (244/395) hypervolemic BV. Of patients with "normal BV", 36% (44/123) demonstrated normal RBC mass and 60% normal PV (74/123). Importantly, 60% (74/123) demonstrated a deficit in RBC mass (true anemia), while a low hemoglobin (<12 g/dL) was present in just 29% (36/123). An excess in RBC mass (erythrocytosis) in 4% (5/123). Notably, true normal BV (i.e., normal RBC mass and normal PV) was observed in only 30% (37/123) of patients with an overall "normal" intravascular volume. Conclusions: Findings reveal that "normal BV" can be misleading by concealing substantial variability in RBC mass (including unrecognized anemia and erythrocytosis) as well as different degrees of PV expansion and contraction. An actual normal BV was identified in a minority of "normal BV" patients. This underscores the importance of looking beyond overall "normal BV" to the contributing elements of RBC mass and PV with significant implications for patient management and outcomes.

This analysis provides a novel assessment of the relationship between the severity of right ventricular dysfunction (RVD) and blood volume expansion (BVE) on clinical outcomes in patients with chronic left-sided heart failure. Findings demonstrate that despite the high prevalence of moderate or greater RVD, persistent BVE was associated with better 1-year event-free survival relative to normal BV. Hypothesis-generating, this suggests that BVE may provide an adaptive response compensating in part for the impact of RVD in chronic HF.

Background Venous hematocrit (vHct) is commonly used to inform blood volume (BV) status and stratify cardiovascular risk. However, vHct defines a percentage of red blood cells (RBCs) to total BV; therefore, similar vHcts can reflect significantly different absolute BVs and RBC mass/plasma volume profiles. This analysis explores how quantitative measures of BV enhance vHct reliability as a biomarker in heart failure. Methods A retrospective analysis was undertaken in 395 patients stratified by vHcts reflecting clinically heart failure–relevant cut points (35% and 40%). BV was quantitated by the indicator‐dilution methodology using iodinated‐131 labeled albumin. Kaplan–Meier analyses compared outcomes. Results Quantitative absolute BVs on average did not differ between vHct subgroups above or below cut points; however, the distribution of RBC mass and plasma volume profiles varied significantly. A normal BV profile was measured in approximately one third of cohort patients and BV hypervolemia in 58%, driven largely by plasma volume expansions (72% of cohort), all with similar distributions above and below cut points. In contrast, profiles of deficits in RBC mass (anemia) and excess (erythrocythemia) were more frequent below and above cut points, respectively, but not exclusively, with 14% of patients demonstrating contrasting RBC mass profiles. Kaplan–Meier analyses provided aggregate support for vHct to stratify heart failure–related outcomes but do not account for misclassified patients. Conclusions VHcts lack capacity to discriminate absolute BVs or the variability in RBC mass and plasma volume profiles above or below cut points. Therefore, quantitative BV measurements are key to adding specificity to individual vHct values, which permits reliable identification of BV status, assignment of appropriate risk, and guidance in management.

Abstract Aims Quantitative methods have shown clinically significant heterogeneity in blood volume (BV) profiles across heart failure (HF) phenotypes. These profiles extend from hypovolaemia to normal BV and to variable degrees of BV hypervolaemia, frequently with similar clinical presentations. However, a comprehensive survey of BV profiles providing practical clinical guidance for the interpretation and management of quantitative plasma volume (PV) and red blood cell (RBC) mass findings has not been reported. The intent of this study is to advance this concept through a multicentre analysis. Methods and results A retrospective analysis of clinical and BV data was undertaken in stable NYHA class II–III HF patients (N = 546). BV was quantitated using established nuclear medicine indicator-dilution methodology. Differing combinations of PV and RBC mass were identified contributing to marked heterogeneity in overall BV profiles. A quantitatively normal BV was identified in 32% of the cohort but of these only ~1/3 demonstrated a true normal BV (i.e., normal PV + normal RBC mass). The remaining portion of normal BV profiles reflected balanced combinations of compensatory PV expansion with RBC mass deficit (anaemia) (14% of cohort) and PV contraction with RBC mass excess (erythrocythemia) (6% of cohort). Main contributors to BV hypervolaemia were PV excess with a normal RBC mass (21% of cohort; 23% female) and PV excess with erythrocythemia (24% of cohort; 26% female). Hypovolaemia was predominately defined by RBC mass deficit with a normal PV (6% of cohort; 57% female) or RBC mass deficit with PV contraction (5% of cohort; 48% female). Conclusions Findings support the clinical relevance of identifying and accurately interpreting the varying combinations of PV and RBC mass in patients with chronic HF. This in turn helps guide appropriate individualized patient management strategies. A practical volume-based guideline is provided in an effort to aid clinician interpretation.

BACKGROUND: Blood volume (BV) profiles vary markedly in patients with heart failure (HF), but how HF phenotypes and patient sex impact volume profiles remain to be explored. The aim of the study was to differentiate BV, plasma volume, and red blood cell mass profiles by phenotypes of preserved and reduced left ventricular ejection fractions and assess the impact of patient sex on profile heterogeneity. METHODS: Retrospective analysis of clinical and BV data was undertaken in patients with chronic New York Heart Association II–III heart failure. BV was quantitated using the nuclear medicine indicator-dilution methodology. RESULTS: A total of 530 BV analyses (360 HF with reduced ejection fraction and 170 HF with preserved ejection fraction) were identified in 395 unique patients. Absolute BV was greater in HF with reduced ejection fraction (6.7±1.8 versus 5.9±1.6 liters: P <0.001); however, large variability in frequency distribution of volume profiles was observed in both phenotypes (−22% deficit to +109% excess relative to normal volumes). HF with reduced ejection fraction was characterized by a higher prevalence of BV expansion ≥+25% of normal (39% versus 26%; P =0.003), and HF with preserved ejection fraction was characterized a by more frequent normal BV (42% versus 24%; P <0.001). Male sex in both phenotypes was associated with a larger absolute BV (7.0±1.6 versus 5.1±1.3 liters; P <0.001) and higher frequency of large BV and plasma volume expansions above normal (both P <0.001), while females in both phenotypes demonstrated a higher prevalence of normal BV and plasma volume (both P <0.001). CONCLUSIONS: Findings support significant differences in BV, plasma volume, and red blood cell mass profile distributions between heart failure phenotypes, driven in large part by sex-specific factors. This underscores the importance of identifying and distinguishing individual patient volume profiles to help guide volume management strategies.

Background: Disease progression in heart failure (HF) reflects multiple neurohormonal derangements resulting in adverse prognosis in the absence of overt clinical events. ST2 is up-regulated in response to cardiac injury/hemodynamic stress while modulating cardiac remodeling via inflammatory and apoptotic pathways. Accordingly, we evaluated changes in ST2 over time in conjunction with troponin T (cTnT) and BNP in ambulatory patients with chronic HF. Methods: A cohort of 191 NYHA class III-IV HF patients was prospectively evaluated with serial specimens collected every 3 months over a 2-year period. Primary end points were death or cardiac transplantation; secondary end points were combined death/transplantation and HF-related hospitalization. Plasma ST2 (Critical Diagnostics) was evaluated against contemporary cTnT (Roche 4th generation) and BNP (Shinogi) assays. Gender specific cut-points (>49.3 and >33.5 ng/mL for males and females, respectively) and a clinically defined optimal cut-point for ST2 (>35 ng/mL) were evaluated. Results: Time-dependent analyses (dichotomous and continuous variable) demonstrated ST2 gender specific cut-points were superior to a single ST2 cut-point and associated with an increased risk of death or transplantation (HR 4.8, 95% CI 2.8 to 8.3, p<0.0001) and combined death/transplantation/HF-hospitalization (HR 2.1, 95% CI 1.7 to 2.5, p<0.0001). Although cTnT remained the strongest predictor of death/transplantation (HR 3.2, 95% CI 1.6 to 5.4, p<0.0001) in multivariate analyses adjusted for cTnT and BNP, ST2 (HR 3.0, 95% CI 1.6 to 5.4, p=0.0003) added significantly to predictive accuracy. Furthermore, elevated ST2 was the only independent predictor of HF-hospitalization (HR 1.7, 95% CI 1.4 to 2.1, p<0.0001). In these models BNP was no longer significantly predictive (HR 1.2, 95% CI 0.7 to 2.2, p=0.58). Conclusions: Serial monitoring of changes in ST2 using gender specific cut-points adds to the diagnostic ability of cTnT in predicting mortality and/or transplantation in outpatients with chronic HF. ST2 uniquely predicts HF-hospitalization/death/transplantation, suggesting a serial monitoring strategy with cTnT and ST2 will optimize identification of HF patients at increased risk for events.