Assessing frailty in heart failure

I'm not as old as I look! I thought so! F. Scott Fitzgerald, ‘The Curious Case of Benjamin Button’ Heart failure (HF) is a complex syndrome, being characterized by different causes, precipitators and clinical presentations.1 A complete characterization of HF would require assessment of additional pathologic processes that lie beyond the cardiovascular system and reflect the systemic implications of the syndrome.2 In this context, attention has been focused on conditions such as cachexia, wasting, and more recently frailty.3, 4 Frailty is a state of decreased physiologic reserve and increased vulnerability to acute stressors such as falls, resulting in increased risk of hospitalization and mortality.4-6 It is generally associated with advanced age,7 but it also represents a process of accelerated ageing in the context of chronic disease states, in which it affects multiple organ systems and aspects of health, while it is not fully captured by measures of disease severity or progress. Several tools have been used to screen or assess frailty that can be categorized into two basic approaches.8 The first one, also termed ‘physical frailty phenotype’, was developed by Fried et al.,9 who characterized frailty as a physical syndrome depending on five criteria: weak grip strength, involuntary weight loss, exhaustion, slow walking speed, and physical inactivity. The second one, also called the ‘cumulative deficit model’, was developed by Rockwood et al.,10 who characterized frailty as a more complex syndrome resulting from accumulated physical and non-physical health deficits. Frailty occurs quite often in patients with HF.6, 11 The Heart Failure Association (HFA) of the European Society of Cardiology recently defined frailty as ‘a multidimensional dynamic state, independent of age, that makes the individual with HF more vulnerable to the effect of stressors’.4 Frailty actually represents accelerated ageing of HF patients, resulting from largely unknown pathophysiology. The proposed mechanisms include immune and hormonal derangement resulting in inflammation, oxidative stress and neurohormonal activation, cellular dysfunction and senescence, sarcopenia, wasting, and others. All these pathologies exist in HF, but it seems that frailty accelerates their expression or evolution.4 The overall prevalence of frailty in patients with HF is estimated around 45%, being up to 6 times more frequent in comparison with the general population.4 Frailty is frequent in HF patients with reduced (HFrEF) and preserved left ventricular ejection fraction, in whom a prevalence as high as 95% was encountered according to the TOPCAT trial.12 Many of the existing screening or assessment tools have been used in patients with HF (Table 1), but there is a lack of recommended ones in this particular population.8 Warren, 194623 As frailty instrument: Jones et al. 200424 Altimir et al. 200525 Pons et al. 201026 Rodriguez-Pascual et al. 201227 Rodriguez-Pascual et al. 201428 McNallan et al. 201311 Dunlay et al. 201431 Lupón et al. 200832 Parmar et al. 2015 34 Mlynarska et al. 201635 Sze et al. 201736 Uchmanowicz and Gobbens 201541 Uchmanowicz et al. 201542 Sze et al. 20198 Sze et al. 201736 Age ≥65 and a care home resident, or Age ≥75 and confusion, falls or reduced mobility, or Age ≥85 and >4 comorbidities Chiarantini et al. 201048 Reeves et al. 201649 Saitoh et al. 201750 Warraich et al. 201851 Pandey et al. 201952 Boxer et al. 201053 McNallan et al. 201354 Reeves et al. 201649 Vidán et al, 201655 Moayedi et al, 201856 Deek et al. 201758 Ferguson et al. 201759 Newton et al. 201660 Jha et al. 201661 McDonagh et al. 202062 In the present issue of the Journal, Dewan and colleagues investigated frailty in a pooled population of HFrEF patients from the PARADIGM-HF and ATMOSPHERE trials.13 The investigators constructed a 42-item frailty index (FI), based on the Rockwood approach, using multiple health deficits based on patients' history, biomarkers reflecting a wide spectrum of organ systems and 15 questions of the Kansas City Cardiomyopathy Questionnaire. They intentionally avoided to include conventional HF prognosticators such as left ventricular ejection fraction or natriuretic peptides. They managed to construct an index of common health deficits, which are found both in the general population and other diseases,14–18 rather than an index strictly reflected on HF severity. Patients with FI ≤0.210 were classified as non-frail, as previously suggested,19 while patients with higher scores were divided into two categories using scores increments of 0.100 (0.211–0.310, pre-frail and ≥0.311, frail). Importantly, frailty was found to be quite frequent in this selected HFrEF population consisting of relatively young and ambulatory patients with rather mild to moderate symptoms. Out of a total population of 13 625, frailty was present in 63% of patients, a prevalence comparable to that of very elderly individuals in the general population, which reflects the fact that frailty is associated with accelerated ageing.4 In addition, frailty conferred an adjusted 63% higher risk of all-cause mortality or hospitalization. These results are in accordance with previous studies, showing similar risk of death and hospitalization in HF patients regardless of age.4 Notably, the prognostic value of FI was beyond that provided by known prognosticators, such as age, left ventricular ejection fraction, or natriuretic peptides. The FI is thus conceptually diverse from standard risk scores and frailty seems to be more than just a surrogate of advanced syndrome stage according to HF severity measures. Frailty is not just physical impairment and assessing this domain only may lead to misclassification of HF patients.4 A holistic multidimensional approach could better determine frailty in HF. In addition, a cumulative deficit approach seems to have a greater value as a predictor of outcomes than the Fried approach.20,21 In accordance to the above, the HFA4 has recently proposed the development of a multidimensional assessment tool, adopting a previously suggested approach by Gorodeski and colleagues.22 This tool includes four domains of interest, the clinical domain (comorbidities, weight loss and falls), the psycho-cognitive domain (cognitive impairment, dementia, depression), the functional domain (impaired activities of daily living, mobility and balance) and the social domain (living alone, institutionalization and lack of social support). The items in each domain remain to be defined. At a later stage this tool needs to undergo validation. However, there are inherited difficulties in the adoption of these or other similar tools in clinical practice given the complexity of the assessment that needs to address several different domains and incorporate numerous variables. This will require engagement of dedicated personnel, with the HF nurse playing a key role, along with information technology-based support, based on electronic health care records as also Dewan and colleagues suggest. The value of frailty as a predictor of poor outcomes is well described in the current and previous studies. The additive clinical value of measuring frailty in HF patients' monitoring and management requires however further investigations. In this context, the positioning of frailty scales among other surrogates of patient status such as quality of life questionnaires or patient-reported outcomes that are at least partly addressed by cumulative deficit model-based frailty scales, remains to be determined. Frailty measures could potentially be used as additional criteria to refine the indications of device implantation such as implantable cardioverter-defibrillator or to guide interventions such as transcatheter mitral valve repair. At the same time, the appropriate interventions to prevent or treat frailty also remain to be determined. Suggested measures include intensification of disease-specific therapeutic modalities, management of comorbidities, exercise training and other rehabilitation processes and lifestyle interventions. All these approaches have proved effective in improving different aspects of the syndrome, including symptoms, quality of life, morbidity and mortality, but frailty seems to lie beyond these surrogates. The introduction of a widely accepted and validated assessment tool currently attempted by HFA4 may help in identifying intervention that effectively target the frailty process. A proposed conceptual framework for frailty in HF is outlined in Figure 1. Frailty is not synonymous to ageing, physical impairment or disease severity. It is rather a process of accelerated ageing associated with many chronic pathologies such as HF and affecting multiple organ systems and aspects of health. It seems to be a surrogate of what people calls ‘biological age’ in contradiction to chronological one. It is yet quite poorly understood, while there are inherited problems in its assessment. Despite the difficulties, the appreciation of frailty will probably open a new window for the better understanding of HF and other syndromes or diseases. Conflict of interest: D.F. has received modest consultation or lecture fees from Abbott Laboratories, Bayer, Boehringer Ingelheim, Menarini, Novartis, Orion Pharma and Roche Diagnostics. G.F. has served as member of committees in trials sponsored by Bayer, Boehringer Ingelheim, Medtronic, Novartis, Servier and Vifor. M.T. and M.E. have no conflict of interest. Appendix S1. Additional references. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. [The remaining references are available in online supplementary Appendix S1]