There are multiple definitions of frailty across medical literature, and despite more focus on this condition in academia, no consensus on frailty's definition or criteria has been agreed (Panza et al, 2011). The principal features of physical frailty include a decline in reserve capacity, characterised by an increase of adverse health outcomes such as falls, vulnerability to functional decline and disability, institutionalisation, hospitalisation, morbidity and mortality (Fried et al, 2001; Gobbens et al, 2010; Aarts et al, 2015). It is now accepted that these features can extend beyond the confines of age, with frailty no longer being limited to a ‘geriatric syndrome’ (Bonner and Lone, 2016; NHS England, 2017).
The UK's population is ageing and the Office for National Statistics (ONS) (2019) predicted that by 2066 there will be an additional 8.6 million people in the UK aged 65 years and over. While frailty and old age are not inevitably linked, it is widely acknowledged that one of the consequences of an increased life expectancy is an increased prevalence of older people living with frailty (Fried et al, 2004; Rockwood et al, 2006; Szanton et al, 2009; Royal College of Nursing, 2018). Indeed, NHS England (2017) argued that frailty is projected to be the most challenging aspect of ageing in modern healthcare.
Dementia is an umbrella term for a progressive disorder that results in a diminished ability to think, reason and remember in comparison to a previous level of social function (Alzheimer's Society, 2019). It encompasses a variety of conditions including Alzheimer's disease, vascular dementia, frontotemporal dementia and Lewy body dementia. Evans (2018) acknowledged that although dementia is not an inevitable consequence of ageing, the risk of having dementia increases with the age; therefore the majority of those affected are over 65 years old. Consequently, a changing population structure poses clear challenges for local and national services, and for the UK economy (ONS, 2019).
Definitions of frailty
While age-related cognitive dysfunction has long been the subject of studies, such as the Geriatric Giants study (Isaacs, 1965), definitions have not considered cognitive frailty to be consistent with physical frailty (Woods et al, 2013). The term ‘cognitive frailty’ is problematic due to the variety of definitions available. It has frequently been used as a general descriptor of age-related cognitive impairment (Woods et al, 2013). ‘Cognitive frailty’ has also referred to pre-dementia states associated with medical conditions (Chouliara et al, 2004). Kelaiditi et al (2013) advocated that the term ‘cognitive frailty’ should be used only for the simultaneous presence of both cognitive impairment and physical frailty, and proposed that concurrent dementias be excluded from its definition. Therefore, the definition of cognitive frailty is ambiguous.
Panza et al (2018) noted how the majority of frailty definitions have prioritised frailty's physical factors, and it has been argued that factors such as cognition, depression and nutrition can also affect frailty (Panza et al, 2011; Mezuk et al, 2012; Kelaiditi et al, 2014).
As the UK's population ages, it is more likely that practice nurses will increasingly see patient's living with frailty and Alzheimer's in primary care
Trails to date
Buffel du Vaure et al (2016) undertook a review of 319 ongoing randomised controlled trials (RCTs) that were registered between 2014 and 2015. They systematically assessed the exclusion criteria and recorded interventions for patients with common chronic conditions in order to determine the prevalence of such conditions being either excluded from RCTs or specifically targeted. Chronic conditions identified included dementia, depression, type 2 diabetes, atrial fibrillation, heart failure, coronary heart disease, pain, chronic obstructive pulmonary disease, hypertension and stroke/transient ischaemic attack. The authors noted that patients with concomitant conditions were excluded in 79% (n=251) of the registered RCTs, irrespective of their high prevalence (Buffel du Vaure et al, 2016).
The 319 RCTs reviewed by Buffel du Vaure et al (2016) amounted to a sample size of 237 544 patients. Of the RCTs reviewed, only 2% (n=7) targeted dementia. For patients with dementia, 95% of participants had a concomitant chronic condition, but of the seven RCTs that targeted patients with dementia, 86% excluded patients with concomitant chronic conditions. The sample size of dementia-targeted RCTs was a limitation, yet it highlighted the limited number of trials for this patient group. In addition, the article focused only on ongoing trials that were registered with ClinicalTrials.gov, therefore it is feasible that the records were not wholly representative of all ongoing trial records. However, ClinicalTrials.gov is the most commonly used register, therefore this decision is reasonable.
Comorbidities
Salisbury et al (2011) and Alwan (2011) maintained that multi-morbidity has become the norm in primary care settings. The Gold Standards Framework Prognostic Indicator guidance (Royal College of General Practitioners, 2011) identified comorbidity as the leading predictive indicator of morbidity and mortality. Buffel du Vaure et al (2016) argued that RCTs should not preclude patients with concomitant chronic conditions when assessing treatment for specific chronic conditions, and that the research agenda should more accurately reflect the prevalence of concomitant chronic conditions. According to Barnett et al (2012), only 5.3% of patients with dementia do not have a concomitant chronic condition, therefore to exclude them from trials would not be an accurate representation.
Frailty assessment
There are myriad definitions and models of frailty (Azzopardi et al, 2016; 2018). Two of the principal frailty models are Fried et al's (2001) frailty phenotype model, and the cumulative deficit model, on which the Canadian Study of Health and Aging (CSHA) frailty index (Mitnitsky et al, 2001) is predicated.
The definition offered by Fried et al (2001) stated that frailty was classed as a clinical syndrome, and an individual is to be considered frail should three of more of the listed criteria be present, or pre-frail if one or two criteria are present. Criteria included:
- Reduced muscle strength
- Slow walking speed
- Self-reported exhaustion
- Unintentional weight loss
- Low levels of physical activity.
In this definition, Fried et al (2001) recognised frailty as a geriatric syndrome comprising five clinical features pertaining exclusively to physical health. This model was developed having undertaken a secondary analysis of data involving a cohort of 5317 people aged 65 years and older who had participated in a cardiovascular health study from 1989–1993 (Fried et al, 2001). The original cohort of 5201 members were recruited from American communities, and a further 687 members were recruited specifically from African American communities. Although the cohort number is large, it is questionable whether the results would be translatable across other ethnicities or nationalities in less economically developed countries.
What is pertinent to patients with Alzheimer's disease is that the phenotype model (Fried et al, 2001) excluded those with cognitive impairment (Mini-Mental score <18) (n=84), on antidepressants, Sinemet or Aricept (n=235), with Parkinson's disease (n=47) and a previous stroke (n=245) (Fried et al, 2001; Clegg et al, 2013). This was justified on the basis that these patient groups potentially present with frailty owing to another condition.
At present, frailty is regarded as ‘primary’ when it is not directly associated with a specific disease, such as dementia (Boockvar and Meier, 2006; Panza et al, 2018). By this definition, the physical phenotype model (Fried et al, 2001) appears appropriate to define frailty. However, when a known comorbidity such as Alzheimer's is associated with frailty, the literature views frailty as ‘secondary’ (Strandberg and Pitkälä, 2007). In this instance, the Alzheimer's patient would arguably be better represented by the cumulative deficit model (Mitnitski et al, 2001; Rockwood et al, 2005).
The frailty index was developed as a product of the CSHA (Mitnitsky et al, 2001) which involved a large cohort of 10 263 participants in a 5-year prospective study. Mitnitski et al (2001) used the sample to investigate the epidemiology of dementia in the elderly in Canada and its associated burdens. To identify frailty, 92 baseline parameters of signs, symptoms, disabilities and abnormal laboratory values collectively compose the deficits are used.
Vulnerability
Frailty is often referred to as a non-specific state of vulnerability involving physiological change across multiple body systems. Panza et al (2011; 2018) acknowledged the heterogeneity of frailty and stated that the accumulation of additional health conditions has now prompted a different approach to frailty that extends to cognitive, psychological and social domains. Furthermore, the biopsychosocial model of health (Gobbens et al, 2010; 2012; Maggio, 2016) also supports a more holistic approach to frailty by widening the frailty construct to incorporate the aforementioned domains. Indeed, Maggio (2016) argued that an individual's level of vulnerability is not sufficiently captured by a purely biological perspective, and that a biopsychosocial model adds value in the frailty assessment and target intervention process.
Panza et al (2011) maintained that it is imperative that the cognitive aspects of frailty are embedded in its definition, thereby supporting an emerging consensus that promotes a frailty definition based on a multidimensional approach (De Vries et al, 2010; Fulop et al, 2010; Gobbens et al, 2010; Sourial et al, 2010).
Since April 2017, the General Medical Services contract (NHS England, 2017) requires GP services to screen for moderate and severe frailty in the 65-and-over age group using the electronic frailty index (eFI). For patients identified as severely frail, practices are required to undertake annual medication reviews, identify falls history and other clinically relevant information. They are also required to seek patient permission to activate an enriched summary care record (NHS England, 2017).
Conclusion
There is a marked disparity in the recognition and management of frailty. This inconsistency has meant that some patient groups, such as dementia patients or other cognitively frail patients, are under-represented by certain frailty models that favour physical symptoms. With numerous iterations of the ‘frailty’ definition, it has become increasingly accepted that frailty encompasses not only the biological factors, but also psychosocial aspects. Furthermore, there is an evident ambiguity regarding the definition of cognitive frailty, which potentiates the frailty recognition problem.
‘The GP contractual changes mean that the eFI model is used across primary care to identify frailty among patients. Both the eFI and cumulative deficit models recognise psychological signs of frailty, such as memory, mood and cognitive problems, which hold no value in other models’
The GP contractual changes mean that the eFI model is used across primary care to identify frailty among patients. Both the eFI and cumulative deficit models recognise psychological signs of frailty, such as memory, mood and cognitive problems, which hold no value in other models, such as the phenotype model. For the dementia patient, this can only serve to further support them as they move along their disease course.
The effects of dementia are far-reaching, impacting not only on those living with the disease but also their carers and relatives (Alzheimer's Society, 2019). It is clear that the emotional sequelae of dementia is profound for all involved – as recognised in the 2014 Care Act policy changes – and that there are numerous concomitant stressors related specifically to caring for the dementia patient.
KEY POINTS
- Patients with cognitive impairment, such as in Alzheimer's disease, may be under-represented in frailty research and literature
- Frailty includes biological and psychosocial and cognitive elements
- The cumulative deficit model of identifying frailty lends itself better to a patient with Alzheimer's disease
- Carer burden and the impact of frailty and Alzheimer's disease on carers must be considered as a core part of any assessment
CPD reflective practice
- Reflect upon on a time when you have assessed a cognitively frail patient. How did you adapt your communication or behaviour during this assessment?
- Reflect upon a time when you have dealt with the family or carers of cognitively frail patients and how you offered support.
- How would you teach a newly qualified or student nurse to communicate effectively with a patient with dementia?