Liver function and prognosis, and influence of sacubitril/valsartan in patients with heart failure with reduced ejection fraction

Suzuki, Kota; Claggett, Brian; Minamisawa, Masatoshi; Packer, Milton; Zile, Michael R.; Rouleau, Jean L.; Swedberg, Karl; Lefkowitz, Martin; Shi, Victor; McMurray, John J.V.; Zucker, Stephen D.; Solomon, Scott D.

doi:10.1002/ejhf.1853

Cited by 38 publications

(43 citation statements)

References 32 publications

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“…Abnormal liver function may lead to increased fluid overload due to hypoalbuminemia and low-osmolality state, which may lead to deterioration of heart failure. This explains the liver function indicators as powerful predictors of prognosis in patients with CHF comorbid with AF in our study, and is consistent with other studies [15][16][17].…”

Section: Discussionsupporting

confidence: 93%

Time-to-event prediction analysis of patients with chronic heart failure comorbid with atrial fibrillation: a LightGBM model

Zheng

Tian

Wang

et al. 2021

BMC Cardiovasc Disord

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Background Chronic heart failure (CHF) comorbid with atrial fibrillation (AF) is a serious threat to human health and has become a major clinical burden. This prospective cohort study was performed to design a risk stratification system based on the light gradient boosting machine (LightGBM) model to accurately predict the 1- to 3-year all-cause mortality of patients with CHF comorbid with AF. Methods Electronic medical records of hospitalized patients with CHF comorbid with AF from January 2014 to April 2019 were collected. The data set was randomly divided into a training set and test set at a 3:1 ratio. In the training set, the synthetic minority over-sampling technique (SMOTE) algorithm and fivefold cross validation were used for LightGBM model training, and the model performance was performed on the test set and compared using the logistic regression method. The survival rate was presented on a Kaplan–Meier curve and compared by a log-rank test, and the hazard ratio was calculated by a Cox proportional hazard model. Results Of the included 1796 patients, the 1-, 2-, and 3-year cumulative mortality rates were 7.74%, 10.63%, and 12.43%, respectively. Compared with the logistic regression model, the LightGBM model showed better predictive performance, the area under the receiver operating characteristic curve for 1-, 2-, and 3-year all-cause mortality was 0.718 (95%CI, 0.710–0.727), 0.744(95%CI, 0.737–0.751), and 0.757 (95%CI, 0.751–0.763), respectively. The net reclassification index was 0.062 (95%CI, 0.044–0.079), 0.154 (95%CI, 0.138–0.172), and 0.148 (95%CI, 0.133–0.164), respectively. The differences between the two models were statistically significant (P < 0.05). Patients in the high-risk group had a significantly higher hazard of death than those in the low-risk group (hazard ratios: 12.68, 13.13, 14.82, P < 0.05). Conclusion Risk stratification based on the LightGBM model showed better discriminative ability than traditional model in predicting 1- to 3-year all-cause mortality of patients with CHF comorbid with AF. Individual patients’ prognosis could also be obtained, and the subgroup of patients with a higher risk of mortality could be identified. It can help clinicians identify and manage high- and low-risk patients and carry out more targeted intervention measures to realize precision medicine and the optimal allocation of health care resources.

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Section: Discussionsupporting

confidence: 93%

Time-to-event prediction analysis of patients with chronic heart failure comorbid with atrial fibrillation: a LightGBM model

Zheng

Tian

Wang

et al. 2021

BMC Cardiovasc Disord

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“…The heterogeneity of CHF patients resulting from pooling HFpEF and HFrEF could be a reason for these inconsistent results. A recent post-hoc analysis of the PARADIGM-HF trial found that ALT was associated with worse prognosis in chronic HFrEF patients, as well as TBIL, but not AST ( 29 ). Of note, as they included chronic HFrEF patients, some of them could be with bilateral HF.…”

Section: Discussionmentioning

confidence: 99%

Prognostic Implication of Liver Function Tests in Heart Failure With Preserved Ejection Fraction Without Chronic Hepatic Diseases: Insight From TOPCAT Trial

Liang

et al. 2021

Front. Cardiovasc. Med.

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Background: Liver dysfunction is prevalent in patients with heart failure (HF), but the prognostic significance of liver function tests (LFTs) remains controversial. Heart failure with preserved ejection fraction (HFpEF) had been introduced for some time, but no previous study had focused on LFTs in HFpEF. Thus, we aim to evaluate the prognostic significance of LFTs in well-defined HFpEF patients.Methods and Results: We conveyed a post-hoc analysis of the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist Trial (TOPCAT). The primary outcome was the composite of cardiovascular mortality, HF hospitalization, and aborted cardiac arrest, and the secondary outcomes were cardiovascular mortality and HF hospitalization. In Cox proportional hazards models, aspartate transaminase (AST) and alanine transaminase (ALT) were not associated with any of the outcomes. On the contrary, increases in total bilirubin (TBIL) and alkaline phosphatase (ALP) were associated with increased risks of the primary outcome [TBIL: adjusted hazard ratio (HR), 1.17; 95% confidence interval (CI) 1.08–1.26; ALP: adjusted HR, 1.12; 95% CI 1.04–1.21], cardiovascular mortality (TBIL: adjusted HR, 1.16; 95% CI 1.02–1.31; ALP: adjusted HR, 1.16; 95% CI 1.05–1.28), and HF hospitalization (TBIL: adjusted HR, 1.22; 95% CI 1.12–1.33; ALP: adjusted HR, 1.12; 95% CI 1.03–1.23).Conclusion: Elevated serum cholestasis markers TBIL and ALP were significantly associated with a poor outcome in HFpEF patients without chronic hepatic diseases, while elevated ALT and AST were not.

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“…The reported prevalence of comorbidities varied with HF severity ( 5 ). As shown in Figure 1 , we summarized the prevalence of major comorbidities according to the different organs and systems involved, such as hypertension (65%), atrial fibrillation (45%), chronic obstructive pulmonary disease (COPD)/asthma(40%), iron deficiency (30%), diabetes (40%), chronic kidney diseases (CKD) (25%), obesity (45%) ( 6 , 7 ), ischaemic heart disease (50%), hyperlipidaemia (55%) ( 8 ), depression (40%) ( 9 – 11 ), sleep apnea (40%) ( 12 ), sarcopenia (40%) ( 13 ) and liver dysfunction (10%) ( 14 ). The high prevalence of multi morbidity is associated with poor prognosis and heavy heath burdens, and therapy for multi morbidity in HF is still a challenge ( 15 ).…”

Section: Introductionmentioning

confidence: 99%

Metabolism and Chronic Inflammation: The Links Between Chronic Heart Failure and Comorbidities

Zhao

Wang

2021

Front. Cardiovasc. Med.

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Heart failure (HF) patients often suffer from multiple comorbidities, such as diabetes, atrial fibrillation, depression, chronic obstructive pulmonary disease, and chronic kidney disease. The coexistance of comorbidities usually leads to multi morbidity and poor prognosis. Treatments for HF patients with multi morbidity are still an unmet clinical need, and finding an effective therapy strategy is of great value. HF can lead to comorbidity, and in return, comorbidity may promote the progression of HF, creating a vicious cycle. This reciprocal correlation indicates there may be some common causes and biological mechanisms. Metabolism remodeling and chronic inflammation play a vital role in the pathophysiological processes of HF and comorbidities, indicating metabolism and inflammation may be the links between HF and comorbidities. In this review, we comprehensively discuss the major underlying mechanisms and therapeutic implications for comorbidities of HF. We first summarize the potential role of metabolism and inflammation in HF. Then, we give an overview of the linkage between common comorbidities and HF, from the perspective of epidemiological evidence to the underlying metabolism and inflammation mechanisms. Moreover, with the help of bioinformatics, we summarize the shared risk factors, signal pathways, and therapeutic targets between HF and comorbidities. Metabolic syndrome, aging, deleterious lifestyles (sedentary behavior, poor dietary patterns, smoking, etc.), and other risk factors common to HF and comorbidities are all associated with common mechanisms. Impaired mitochondrial biogenesis, autophagy, insulin resistance, and oxidative stress, are among the major mechanisms of both HF and comorbidities. Gene enrichment analysis showed the PI3K/AKT pathway may probably play a central role in multi morbidity. Additionally, drug targets common to HF and several common comorbidities were found by network analysis. Such analysis has already been instrumental in drug repurposing to treat HF and comorbidity. And the result suggests sodium-glucose transporter-2 (SGLT-2) inhibitors, IL-1β inhibitors, and metformin may be promising drugs for repurposing to treat multi morbidity. We propose that targeting the metabolic and inflammatory pathways that are common to HF and comorbidities may provide a promising therapeutic strategy.

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Liver function and prognosis, and influence of sacubitril/valsartan in patients with heart failure with reduced ejection fraction

Abstract: The prevalence of liver function abnormalities is common in patients with heart failure (HF) with reduced ejection fraction (HFrEF). We assessed the impact of liver function on prognosis and the effect of sacubitril/valsartan on measures of liver function in patients with HFrEF.

Cited by 38 publications

References 32 publications

Time-to-event prediction analysis of patients with chronic heart failure comorbid with atrial fibrillation: a LightGBM model

Time-to-event prediction analysis of patients with chronic heart failure comorbid with atrial fibrillation: a LightGBM model

Prognostic Implication of Liver Function Tests in Heart Failure With Preserved Ejection Fraction Without Chronic Hepatic Diseases: Insight From TOPCAT Trial

Metabolism and Chronic Inflammation: The Links Between Chronic Heart Failure and Comorbidities

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