BackgroundMalnutrition is a common condition that is associated with adverse prognosis in patients with heart failure (HF). The Prognostic Nutritional Index (PNI), Geriatric Nutritional Risk Index (GNRI) and controlling nutritional status (CONUT) have all been used as objective indices for evaluating nutritional status. We aimed to clarify the relationship between these nutritional indices and the parameters of inflammatory markers, cardiac function and exercise capacity, as well as to compare the ability of these indexes for predicting mortality.MethodsWe evaluated PNI, GNRI and CONUT in consecutive 1307 patients with HF.ResultsFirst, there were significant correlations between nutritional indices and the following: C reactive protein; tumour necrosis factor-α; adiponectin; B-type natriuretic peptide; troponin I; inferior vena cava diameter and peak VO2 (P<0.05, respectively). Second, in the Kaplan-Meier analysis (follow-up 1146 days), all-cause mortality progressively increased from normal to mild, moderate and severe disturbance groups in the indices (log-rank, P<0.01, respectively). In the Cox proportional hazard analysis, each index was an independent predictor of all-cause mortality in patients with HF (P<0.001, respectively). Third, receiver operating curve demonstrated that the areas under the curve of PNI and GNRI were larger than that of CONUT score (P<0.05, respectively).ConclusionPatients with HF being malnourished had higher mortality accompanied by higher levels of C reactive protein, tumour necrosis factor-α, adiponectin, B-type natriuretic peptide, troponin I, right-sided volume overload and impaired exercise capacity, rather than left ventricular systolic function. Additionally, PNI and GNRI were superior to CONUT score in predicting mortality in patients with HF.

AimsHeart failure with preserved ejection fraction (HFpEF) has several pathophysiological aspects, including stiffness and/or congestion of multiple organs. Poor prognosis is expected in heart failure patients with liver stiffness, which has recently been assessed by non‐alcoholic fatty liver disease fibrosis score (NFS; based on aspartate aminotransferase to alanine aminotransferase ratio, platelet counts, and albumin). We aimed to investigate the impact of NFS on prognosis of HFpEF patients, with consideration for the peripheral collagen markers such as procollagen type III peptide (PIIIP), type IV collagen 7S, and hyaluronic acid.Methods and resultsWe performed a prospective observational study. Consecutive 492 hospitalized HFpEF patients were divided into four groups based on their NFS: first–fourth quartiles (n = 123). The fourth quartile group had the highest levels of PIIIP, type IV collagen 7S, hyaluronic acid, and B‐type natriuretic peptide (P<0.001 each). In addition, there were significant positive correlations between PIIIP, type IV collagen 7S, hyaluronic acid, B‐type natriuretic peptide, and NFS (P < 0.001 each). In the follow‐up period (mean 1107 days), 93 deaths occurred. All‐cause mortality increased in all four quartiles (8.1%, 12.2%, 23.6%, and 31.7%, P < 0.001). In the multivariable Cox proportional hazard analysis, NFS was an independent predictor of all‐cause mortality in the HFpEF patients.ConclusionsNFS, a novel indicator of liver fibrosis, correlates with circulating systemic markers of fibrosis and congestion and is associated with higher all‐cause mortality in HFpEF patients. NFS can be calculated simply and may be a useful tool to assess liver stiffness and prognosis in HFpEF patients.

ObjectiveLiver dysfunction due to heart failure (HF) is known as congestive hepatopathy. It has recently been reported that liver stiffness assessed by transient elastography reflects increased central venous pressure. The Fibrosis-4 (FIB4) index (age (years) × aspartate aminotransferase (IU/L)/platelet count (109/L) × square root of alanine aminotransferase (IU/L)) is expected to be useful for evaluating liver stiffness in patients with non-alcoholic fatty liver disease. We aimed to investigate the impact of the FIB4 index on HF prognosis, with consideration for liver fibrosis markers and underlying cardiac function.MethodsConsecutive 1058 patients with HF who were admitted to our hospital were divided into three groups based on their FIB4 index: first (FIB4 index <1.72, n=353), second (1.72≤FIB4 index <3.01, n=353) and third tertiles (3.01≤FIB4 index, n=352). We prospectively followed for all-cause mortality.ResultsDuring the follow-up period (mean 1047 days), 246 deaths occurred. In the Kaplan-Meier analysis, all-cause mortality progressively increased from the first to third groups (12.2%, 21.0% and 36.6%, p<0.01). In the Cox proportional hazard analysis, FIB4 index was an independent predictor of all-cause mortality in patients with HF (p<0.05). In comparisons of laboratory and echocardiographic findings, the third tertile had higher levels of type IV collagen 7S, procollagen type III peptide, hyaluronic acid, left atrial volume, mitral valve E/e’, inferior vena cava diameter and right atrial end systolic area (p<0.01, respectively).ConclusionThe FIB4 index, a marker of liver stiffness, is associated with higher all-cause mortality in patients with HF.

AimsEffective pharmacotherapy for heart failure with preserved left ventricular ejection fraction (HFpEF) is still unclear. Sleep-disordered breathing (SDB) causes cardiovascular dysfunction, giving rise to factors involved in HFpEF. However, it remains unclear whether adaptive servo-ventilation (ASV) improves cardiovascular function and longterm prognosis of patients with HFpEF and SDB. Methods and resultsThirty-six patients with HFpEF (LVEF .50%) and moderate to severe SDB (apnoea -hypopnoea index .15/h) were enrolled. Study subjects (LVEF 56.0%, apnoea-hypopnoea index 36.5/h) were randomly assigned to two groups: 18 patients treated with medications and ASV (ASV group) and 18 patients not treated with ASV (non-ASV group). NYHA class, cardiac function including LVEF, left atrial volume index (LAVI), E/E', vascular function including flowmediated dilatation (FMD) and cardio-ankle vascular index (CAVI), and levels of BNP and troponin T were determined at baseline and 6 months later. Patients were followed to register cardiac events after enrolment (follow-up 543 days). ASV therapy improved cardiac diastolic function and decreased CAVI and BNP (NYHA class, 2.3 to 1.5; LAVI, 48.6 to 42.6 mL/m 2 ; E/E', 12.8 to 7.1; CAVI, 9.0 to 7.7; BNP, 121.5 to 58.1 pg/mL, P , 0.0125, respectively). LVEF, FMD, and troponin T did not change significantly in either group. Importantly, the event-free rate was significantly higher in the ASV group than in the non-ASV group (94.4% vs. 61.1%, log-rank P , 0.05). ConclusionASV may improve the prognosis of HFpEF patients with SDB, with favourable effects such as improvement of symptoms, cardiac diastolic function, and arterial stiffness. ASV may be a useful therapeutic tool for HFpEF patients with SDB.--

Aims We aimed to determine the differences of impact of cardiopulmonary exercise testing (CPX) parameters on prognosis of heart failure with reduced left ventricular ejection fraction (HFrEF), preserved ejection fraction (HFpEF) and mid-range ejection fraction (HFmrEF). Methods We compared clinical characteristics and CPX parameters among the three groups, and the value of each CPX parameter to predict adverse cardiac events (cardiac deaths and re-hospitalizations for heart failure), cardiac deaths and all-cause deaths. Results Of 1190 patients, 41.9% had HFrEF, 36.8% had HFpEF and 21.3% had HFmrEF. The patients in HFrEF group had higher rates of adverse cardiac events, cardiac death and all-cause death than those of HFpEF and HFmrEF groups. In HFrEF, the independent predictors of adverse cardiac events were peak oxygen consumption and oxygen uptake efficiency slope, predictors of cardiac death were peak oxygen consumption and oxygen uptake efficiency slope, and the predictor of all-cause death was peak oxygen consumption. In HFpEF, the predictor of adverse cardiac events was peak oxygen consumption, predictors of cardiac deaths and all-cause deaths were peak oxygen consumption and exertional oscillatory ventilation. In HFmrEF, predictors of adverse cardiac events were peak oxygen consumption and oxygen uptake efficiency slope, and the predictor of cardiac deaths and all-cause deaths was peak oxygen consumption. Conclusion Peak oxygen consumption is the strong predictor for adverse events in all groups. Oxygen uptake efficiency slope predicts adverse prognosis in HFrEF, but not in HFpEF. In contrast, exertional oscillatory ventilation is the predictor only in HFpEF. Thus, different CPX parameters may be able to differentially predict prognosis in HFrEF and HFpEF. Those for predicting prognosis in HFmrEF may be intermediate between HFrEF and HFpEF.