Frailty as a predictor of clinical problems and events that require elderly patients with heart failure to use health resources

The burden of frailty in heart failure: Prevalence, impacts on clinical outcomes and the role of heart failure medications

BACKGROUND

Frailty often coexists with heart failure (HF), which significantly aggravates the clinical outcomes of older adults. However, studies investigating the interplay between frailty and HF in older adults are scarce. We aimed to assess the prevalence of frailty using the cumulative deficit approach and evaluate the impacts of frailty on health utilization, use of HF-related medications and adverse clinical outcomes (all-cause mortality, all-cause readmissions and HF readmissions) among older HF patients.

METHODS

A total of 38 843 newly admitted HF patients were identified from Taiwan's National Health Insurance Research Database and categorized into three frailty subgroups (fit, mild frailty and severe frailty) based on the multimorbidity frailty index. Cox regression models and Fine and Gray subdistribution hazard models were used to estimate the impacts of frailty on clinical outcomes at 1 and 2 years of follow-up. Generalized estimating equation models were further conducted to evaluate the associations between longitudinal and time-varying use of HF-related medications and clinical outcomes among distinct frailty subgroups.

RESULTS

Of 38 843 older HF patients (mean age 80.4 ± 8.5 years, 52.3% females) identified, 68.3% were categorized as frail (47.5% of mild frailty and 20.8% of severe frailty). The median number of readmissions (fit: 1 [inter-quartile range-IQR 2], mild frailty: 1 [IQR 2] and severe frailty: 2 [IQR 3]) increased with the severity of frailty. Only 27.3% of HF patients died of cardiovascular diseases regardless of their frailty status. Compared with the fit group, the severe frailty group was associated with increased risk of all-cause mortality (adjusted hazard ratio 1.16, 95% confidence interval [CI] 1.11-1.21), all-cause readmissions (subdistributional hazard ratio (sHR) 1.21, 95% CI 1.16-1.25) and HF-related readmissions (sHR 1.14, 95% CI 1.09-1.20) at 2 years of follow-up. Those who used triple or more HF-related medications were at lower risk for all-cause readmissions (adjusted odds ratio [aOR] 0.49, 95% CI 0.44-0.54) and HF-related readmissions (aOR 0.42, 95% CI 0.37-0.47) at 2 years of follow-up even in the severe frailty group.

CONCLUSIONS

Frailty is highly prevalent and associated with increased risk of all-cause mortality, all-cause readmissions and HF readmissions among older HF patients. Those who were using triple or more HF-related medications were at lower risk of adverse clinical outcomes across distinct frailty subgroups. Further studies are needed to optimize the treatment strategies for older HF patients with distinct frailty status.

Association between natriuretic peptides and C-reactive protein with frailty in heart failure: a systematic review and meta-analysis

BACKGROUND

Heart failure (HF) and frailty are accompanied by a bidirectional relationship, sharing common risk factors including elevated levels of natriuretic peptides and inflammation. The aim of this study was to compare biomarkers associated with poor clinical outcomes, that is, plasma brain natriuretic peptide (BNP), N-terminal-pro B-type natriuretic peptide (NT-proBNP), and C-reactive protein (CRP) in patients with HF and frailty vs. patients with HF without frailty.

METHODS

From inception until July 2023, PubMed, Scopus, Web of Science, and Cochrane Library a systematic literature search was conducted. To evaluate whether frailty is linked with greater levels of BNP, NT-proBNP, and CRP, a meta-analysis using a random-effects model was used to calculate the pooled effects (CRD42023446607).

RESULTS

Fifty-three studies were included in this systematic review and meta-analysis. Patients with HF and frailty displayed significantly higher levels of BNP (k = 11; SMD: 0.53, 95%CI 0.30-0.76, I2 = 86%, P < 0.01), NT-proBNP (k = 23; SMD: 0.33, 95%CI 0.25-0.40, I2 = 72%, P < 0.01), and CRP (k = 8; SMD: 0.30, 95%CI 0.12-0.48, I2 = 62%, P < 0.01) vs. patients with HF without frailty. Using meta-regression, body mass index (BMI) and age were deemed potential moderators of these findings.

CONCLUSIONS

Frailty in HF is linked to increased concentrations of BNP, NT-proBNP, and CRP, which have been epidemiologically associated with adverse outcomes. The increased risk of NYHA III/IV classification further emphasizes the clinical impact of frailty in this population.