Pathophysiologic Processes and Novel Biomarkers Associated With Congestion in Heart Failure.

BACKGROUND: Congestion is the main driver behind symptoms of heart failure (HF), but pathophysiology related to congestion remains poorly understood. OBJECTIVES: Using pathway and differential expression analyses, the authors aim to identify biological processes and biomarkers associated with congestion in HF. METHODS: A congestion score (sum of jugular venous pressure, orthopnea, and peripheral edema) was calculated in 1,245 BIOSTAT-CHF patients with acute or worsening HF. Patients with a score ranking in the bottom or top categories of congestion were deemed noncongested (n = 408) and severely congested (n = 142), respectively. Plasma concentrations of 363 unique proteins (Olink Proteomics Multiplex CVD-II, CVD-III, Immune Response and Oncology II panels) were compared between noncongested and severely congested patients. Results were validated in an independent validation cohort of 1,342 HF patients (436 noncongested and 232 severely congested). RESULTS: Differential protein expression analysis showed 107/363 up-regulated and 6/363 down-regulated proteins in patients with congestion compared with those without. FGF-23, FGF-21, CA-125, soluble ST2, GDF-15, FABP4, IL-6, and BNP were the strongest up-regulated proteins (fold change [FC] >1.30, false discovery rate [FDR], P < 0.05). KITLG, EGF, and PON3 were the strongest down-regulated proteins (FC <-1.30, FDR P < 0.05). Pathways most prominently involved in congestion were related to inflammation, endothelial activation, and response to mechanical stimulus. The validation cohort yielded similar findings. CONCLUSIONS: Severe congestion in HF is mainly associated with inflammation, endothelial activation, and mechanical stress. Whether these pathways play a causal role in the onset or progression of congestion remains to be established. The identified biomarkers may become useful for diagnosing and monitoring congestion status.

The value of spot urinary creatinine as a marker of muscle wasting in patients with new-onset or worsening heart failure.

BACKGROUND: Muscle wasting and unintentional weight loss (cachexia) have been associated with worse outcomes in heart failure (HF), but timely identification of these adverse phenomena is difficult. Spot urinary creatinine may be an easily accessible marker to assess muscle loss and cachexia. This study investigated the association of urinary creatinine with body composition changes and outcomes in patients with new-onset or worsening HF (WHF). METHODS: In BIOSTAT-CHF, baseline spot urinary creatinine measurements were available in 2315 patients with new-onset or WHF in an international cohort (index cohort) and a validation cohort of 1431 similar patients from Scotland. RESULTS: Median spot urinary creatinine concentrations were 5.2 [2.7-9.6] mmol/L in the index cohort. Median age was 69 ± 12 years and 73% were men. Lower spot urinary creatinine was associated with older age, lower height and weight, worse renal function, more severe HF, and a higher risk of >5% weight loss from baseline to 9 months (odds ratio = 1.23, 95% CI = 1.09-1.39 per log decrease; P = 0.001). Spot urinary creatinine was associated with Evans criteria of cachexia (OR = 1.26 per log decrease, 95% CI = 1.04-1.49; P = 0.016) and clustered with markers of heart failure severity in hierarchical cluster analyses. Lower urinary creatinine was associated with poorer exercise capacity and quality of life (both P < 0.001) and predicted a higher rate for all-cause mortality [hazard ratio (HR) = 1.27, 95% CI = 1.17-1.38 per log decrease; P < 0.001] and the combined endpoints HF hospitalization or all-cause mortality (HR = 1.23, 95% CI = 1.15-1.31 per log decrease; P < 0.001). Significance was lost after addition of the BIOSTAT risk model. Analyses of the validation cohort yielded similar findings. CONCLUSIONS: Lower spot urinary creatinine is associated with smaller body dimensions, renal dysfunction, and more severe HF in patients with new-onset/WHF. Additionally, lower spot urinary creatinine is associated with an increased risk of weight loss and a poorer exercise capacity/quality of life. Urinary creatinine could therefore be a novel, easily obtainable marker to assess (risk of) muscle wasting in HF patients.

Clinical value of pre-discharge bio-adrenomedullin as a marker of residual congestion and high risk of heart failure hospital readmission.

AIMS: Recently, bio-adrenomedullin (bio-ADM) was proposed as a congestion marker in heart failure (HF). In the present study, we aimed to study whether bio-ADM levels at discharge from a hospital admission for worsening HF could provide additional information on (residual) congestion status, diuretic dose titration and clinical outcomes. METHODS AND RESULTS: Plasma bio-ADM was measured in 1236 acute HF patients in the PROTECT trial at day 7 or discharge. Median discharge bio-ADM was 33.7 [21.5-61.5] pg/mL. Patients with higher discharge bio-ADM levels were hospitalised longer, had higher brain natriuretic peptide levels, and poorer diuretic response (all P < 0.001). Bio-ADM was the strongest predictor of discharge residual congestion (clinical congestion score > 3) (odds ratio 4.35, 95% confidence interval 3.37-5.62; P < 0.001). Oedema at discharge was one of the strongest predictors of discharge bio-ADM (ß = 0.218; P < 0.001). Higher discharge loop diuretic doses were associated with a poorer diuretic response during hospitalisation (ß = 0.187; P < 0.001) and higher bio-ADM levels (ß = 0.084; P = 0.020). High discharge bio-ADM levels combined with higher use of loop diuretics were independently associated with a greater risk of 60-day HF rehospitalisation (hazard ratio 4.02, 95% confidence interval 2.23-7.26; P < 0.001). CONCLUSION: In hospitalised HF patients, elevated pre-discharge bio-ADM levels were associated with higher discharge loop diuretic doses and reflected residual congestion. Patients with combined higher bio-ADM levels and higher loop diuretic use at discharge had an increased risk of rehospitalisation. Assessment of discharge bio-ADM levels may be a readily applicable marker to identify patients with residual congestion at higher risk of early hospital readmission.