Understanding the variability in red cell and plasma volume combinations can help guide management in heart failure

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.

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).

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.