The predictive capacity and additional prognostic power of N-terminal pro-B-type natriuretic peptide in Chinese elderly with chronic heart failure

The Associations of Two Novel Inflammation Biomarkers, SIRI and SII, with Mortality Risk in Patients with Chronic Heart Failure

Background

The associations of two novel inflammation biomarkers, systemic inflammation response index (SIRI) and systemic immune inflammation index (SII), with mortality risk in patients with chronic heart failure (CHF) are not well-characterized.

Methods

This retrospective cohort study included patients with CHF in two medical centers of Chinese People's Liberation Army General Hospital, Beijing, China. The outcomes of this study included in-hospital mortality and long-term mortality. Associations of SIRI and SII with mortality were assessed using multivariable regressions and receiver operating characteristic (ROC) analyses.

Results

A total of 6232 patients with CHF were included in the present study. We documented 97 cases of in-hospital mortality and 1738 cases of long-term mortality during an average 5.01-year follow-up. Compared with patients in the lowest quartile of SIRI, those in the highest quartile exhibited 134% higher risk of in-hospital mortality (adjusted odds ratio, 2.34; 95% confidence interval [CI], 1.16-4.72) and 45% higher risk of long-term mortality (adjusted hazard ratio, 1.45; 95% CI, 1.25-1.67). Compared with patients in the lowest quartile of SII, those in the highest quartile exhibited 27% higher risk of long-term mortality (adjusted hazard ratio, 1.27; 95% CI, 1.11-1.46). In ROC analyses, SIRI showed better prognostic discrimination than C-reactive protein (area under the curve: 69.39 vs 60.91, P = 0.01, for in-hospital mortality; 61.82 vs 58.67, P = 0.03, for 3-year mortality), whereas SII showed similar prognostic value with C-reactive protein.

Conclusion

SIRI and SII were significantly associated with mortality risk in patients with CHF. SIRI may provide better prognostic discrimination than C-reactive protein.

Neutrophil to lymphocyte ratio (NLR) prognostic effects on heart failure; a systematic review and meta-analysis

BACKGROUND

Neutrophil to lymphocyte ratio (NLR), as a recent inflammatory index, has been reported to be a prognostic tool in different diseases. However, implication of this ratio in heart failure (HF) is less investigated. In this systematic review and meta-analysis, we aimed to assess the potential impact of NLR on HF clinical outcomes.

METHODS

Relevant English published records in PubMed, Scopus, Embase, and Web of Science were screened up to July 2023. Articles reporting clinical outcomes (follow-up or in-hospital mortality, readmission, HF prediction, extended hospital stay length, pulmonary vascular resistance, atrial fibrillation, renal disease and functional capacity) in HF sufferers were collected for further analysis with addition of NLR difference stratified by death/survived and HF status.

RESULTS

Thirty-six articles (n = 18231) were finally selected which reported NLR in HF sufferers (mean: 4.38, 95% confidence interval (CI): 4.02-4.73). We found 25 articles reported NLR and total mortality (either follow-up death (N = 19): 4.52 (95% CI: 4.03-5.01) or in-hospital death (N = 10): 5.33 (95% CI: 4.08-6.57)) with mean NLR of 4.74 (95% CI: 4.28-5.20). NLR was higher among deceased patients compared to survived ones (standard mean difference: 0.67 (95% CI: 0.48-0.87), P < 0.001)). NLR was found to be related with higher mortality risk (continuous variable: hazard ratio (HR): 1.12, 95% CI: 1.02-1.23, P = 0.013), categorical variable: HR: 1.77, 95% CI: 1.27-2.46, P = 0.001, T2 vs. T1: HR:1.56, 95%CI: 1.21-2.00, P = 0.001, T3 vs. T1: HR:2.49, 95%CI: 1.85-3.35, P < 0.001). Other aforementioned variables were not feasible to analyze due to presence of few studies.

CONCLUSIONS

NLR is a simple and acceptable prognostic tool for risk stratification and prioritizing high risk patients in clinical settings, especially in resource limited nations.

Heart failure with preserved ejection fraction based on aging and comorbidities

Heart failure (HF) with preserved ejection fraction (HFpEF) is a leading cause of hospitalizations and mortality when diagnosed at the age of ≥ 65 years. HFpEF represents multifactorial and multisystemic syndrome and has different pathophysiology and phenotypes. Its diagnosis is difficult to be established based on left ventricular ejection fraction and may benefit from individually tailored approaches, underlying age-related changes and frequent comorbidities. Compared with the rapid development in the treatment of heart failure with reduced ejection fraction, HFpEF presents a great challenge and needs to be addressed considering the failure of HF drugs to improve its outcomes. Further extensive studies on the relationships between HFpEF, aging, and comorbidities in carefully phenotyped HFpEF subgroups may help understand the biology, diagnosis, and treatment of HFpEF. The current review summarized the diagnostic and therapeutic development of HFpEF based on the complex relationships between aging, comorbidities, and HFpEF.

The neutrophil to lymphocyte ratio in heart failure: a comprehensive review

INTRODUCTION

Heart failure (HF) and systemic inflammation are interdependent processes that continuously potentiate each other. Distinct pathophysiological pathways are activated, resulting in increased neutrophil count and reduced lymphocyte numbers, making the neutrophil to lymphocyte ratio (NLR) a potential indirect marker of severity. We conducted this comprehensive review to characterize the role of NLR in HF.

METHODS

We searched the PubMed (MEDLINE) database using the key words "neutrophil", "lymphocyte", "heart failure", "cardiomyopathy", "implantable cardioverter defibrillator", "cardiac resynchronization therapy" and "heart transplant".

RESULTS

We identified 241 publications. 31 were selected for this review, including 12,107 patients. NLR was correlated to HF severity expressed by clinical, biological, and imaging parameters, as well as to short and long-term prognosis. Most studies reported its survival predictive value. Elevated NLR (>2.1-7.6) was an independent predictor of in-hospital mortality [adjusted HR 1.13 (95% CI 1.01-1.27) - 2.8 (95% CI 1.43-5.53)] as well as long-term all-cause mortality [adjusted HR 1.43 (95% CI 1.1-1.85) - 2.403 (95% CI 1.076-5.704)]. Higher NLR levels also predicted poor functional capacity [NLR > 2.26/2.74, HR 3.93 (95% CI 1.02-15.12) / 3.085 (95% CI 1.52-6.26)], hospital readmissions [NLR > 2.9/7.6, HR 1.46 (95% CI 1.10-1.93) / 3.46 (95% CI 2.11-5.68)] cardiac resynchronization therapy efficacy [NLR > 3.45/unit increase, HR 12.22 (95% CI 2.16-69.05) / 1.51 (95% CI 1.01-2.24)] and appropriate implantable cardioverter defibrillator shocks (NLR > 2.93), as well as mortality after left ventricular assist device implantation [NLR > 4.4 / quartiles, HR 1.67 (95% CI 1.03-2.70) / 1.22 (95% CI 1.01-1.47)] or heart transplant (NLR > 2.41, HR 3.403 (95% CI 1.04-11.14)].

CONCLUSION

Increased NLR in HF patients can be a valuable auxiliary biomarker of severity, and most of all, of poor prognosis.

An Appraisal of Biomarker-Based Risk-Scoring Models in Chronic Heart Failure: Which One Is Best?

PURPOSE OF REVIEW

While prediction models incorporating biomarkers are used in heart failure, these have shown wide-ranging discrimination and calibration. This review will discuss externally validated biomarker-based risk models in chronic heart failure patients assessing their quality and relevance to clinical practice.

RECENT FINDINGS

Biomarkers may help in determining prognosis in chronic heart failure patients as they reflect early pathologic processes, even before symptoms or worsening disease. We present the characteristics and describe the performance of 10 externally validated prediction models including at least one biomarker among their predictive factors. Very few models report adequate discrimination and calibration. Some studies evaluated the additional predictive value of adding a biomarker to a model. However, these have not been routinely assessed in subsequent validation studies. New and existing prediction models should include biomarkers, which improve model performance. Ongoing research is needed to assess the performance of models in contemporary patients.

Prognostic value of neutrophil to lymphocyte ratio in heart failure patients

BACKGROUND

Neutrophil to lymphocyte ratio (NLR) has been indicated to be an independent predictor for all-cause mortality or adverse events in a variety of diseases. However, no consistent conclusions regarding it's relevance to patients with heart failure have been made. This meta-analysis was conducted to assess the significance of NLR in patients with heart failure.

METHODS

Pubmed and Embase databases were searched for eligible studies that reported the association between NLR and heart failure through September 2017. The overall hazard ratio (HR) and corresponding 95% confidence interval (CI) were used to assess the associations.

RESULTS

Ten studies met the eligibility criteria and a total of 5979 heart failure patients were included in the meta-analysis. The overall hazard ratio (HR) for all-cause mortality was 1.28 (95% CI 1.14-1.43) and the HR of renal dysfunction was 1.23 (95% CI 1.07-1.41) comparing the highest with the lowest category of NLR. However, the total pooled adjusted HR for in-hospital mortality (HR = 1.18, 95% CI 0.88-1.59) and rehospitalization (HR = 2.19, 95% CI 0.94-5.09) were not statistically significant. A subgroup analysis showed that sample size with moderate heterogeneity may be the origin of heterogeneity in all-cause mortality. Sensitivity analysis proved the stability of results of our meta-analysis.

CONCLUSIONS

The meta-analysis demonstrates that NLR is a predictor of all-cause mortality in patients with heart failure. Because the quality of the included studies varies, further well-designed studies are needed to confirm this association.

Biomarkers in Cardiorenal Syndromes

There is a consensus that cardiorenal syndromes (CRS) are defined as the disorders of heart and kidney where acute or chronic dysfunction in one organ may induce acute or chronic dysfunction in another. Patients with CRS have increased hospitalization and mortality rates, and thus their identification is of great implication. Biomarkers are not only predictive in heart failure or renal diseases, but also useful in identifying cardiac dysfunction in renal diseases and renal injury in heart failure. Thus, they may be applied in order to identify patients with CRS and even assess prognosis and guide therapy in these patients. However, studies on biomarkers have just begun in CRS. Future studies are essential to observe current biomarkers and find novel biomarkers in CRS so as to improve diagnosis, therapy, and prognosis of CRS.