What is the Edmonton Frail Scale?

This scale:

• Frames frailty in terms that are meaningful to clinicians.

• Can be administered quickly, but is rich with information.

• Includes stand-alone items that are individually valid.

• Bridges to more in-depth assessments, care, and support.

The EFS defines frailty in a way that works.

In the past, health professionals have had difficulty understanding frailty, perhaps because it doesn’t fit their paradigm for medical problems. But an improved understanding of frailty should lead to better decisions about patient care. The following descriptions of frailty are the basis for the Edmonton Frail Scale, and help demonstrate how it should empower clinicians in their work:

Frailty is a state of exaggerated vulnerability.

In one sense, frailty is a state of heightened risk for future decline in vitality and function, resulting from the accumulation of non-specific deficits over time. “Deficits” are permanent health problems, acquired over the life course, that that threaten a person’s future independence. “Assets” are those factors that tend to promote independence. To the extent that deficits are not compensated by assets, the person who lives with frailty is more likely to experience a loss of independence over time. As the number of deficits rise, there is a diminished repertoire of assets to compensate, and deficit accumulation becomes self-reinforcing and accelerates. At this point, the state of frailty becomes more apparent in the form of a syndrome.

For Clinicians: A state of exaggerated vulnerability should help make decisions about care. That risk state for functional decline can be estimated by noting the number of deficits. Risks can be mitigated by making the most of existing assets.

Frailty manifests as a multidimensional syndrome.

Some might limit their definition of frailty to impairments in physical performance measures such as grip strength or gait speed. Here, we assert that frailty is manifest as a multidimensional syndrome that may include problems physical performance, but also in cognition, mood, nutrition, multi-morbidity, poly-pharmacy, continence, health attitudes, functional capacity, social support, and other domains. These dimensions of health are highly interactive. The whole of frailty is more than the sum of these parts, but each part deserves meaningful consideration.

For Clinicians: An understanding of the unique components of frailty should prompt further investigation and definition. For example, if the case finding of frailty reveals possible issues with cognitive impairment, polypharmacy and nutritional risk, then the clinician can coordinate further assessment and management of these problems.

Frailty involves a “dynamic interaction between individual capacity, external resources, and stress”.

The state of frailty can be quiet and unnoticed unless there is stress. In the context of new stress such as acute illness, surgery, a new medication, or even a change in social support, frailty is expressed in multidimensional terms through the systems of greatest vulnerability. Multidimensional frailty measures help define these vulnerable systems. In this sense, the expression frailty encompasses many of the “acute geriatric syndromes” such as delirium, new immobility, falls, new incontinence and nutritional crises.

For Clinicians: Acute illness or changes in social support constitutes health related stress and may the reason individuals seek help from clinicians. Conversely, clinicians may introduce additional stress by recommending new medications or interventions such as surgery. Frailty is the sum of an individual’s intrinsic capacity and their external resources. When clinicians understand the dynamic interaction between frailty status and stress in an individual, they are able to optimize care.

Now let’s consider how a multidimensional frailty measure such as the EFS can be used for case-finding, estimating severity, and defining components.

Case Finding

The Target Population for Case-Finding

We recommend case-finding in individuals with apparent age-related decline, or when functional independence is apparently threatened. Age is a continuous risk factor for frailty, and as such, the choice of any age cut-off as a starting point for case-finding would be an arbitrary but reasonable strategy. At the same time, it is reasonable to conduct case-finding in selected younger individuals.

What is Age-Related Decline?

Age-related decline is suspected when health conditions cause a greater functional impact than would be expected. For example, when stable chronic diseases accumulate, the collective impact on independent daily living is more than expected. When there is age-related decline, the chronic diseases in an individual interact, resulting in additional burdens. There might be an acceleration in the accumulation of these problems, and to an outside observer, the individual may appear to be aging more quickly than they had before. Clinicians may observe geriatric syndromes such as cognitive decline, falls, immobility, polypharmacy, urinary incontinence, or malnutrition. Alternatively, the age-related decline might become first apparent in the context of acute illness or other stress; the impact could be exaggerated, and symptoms (ie. the presentation of illness) might be atypical. For example, a relatively benign problem such as a urinary tract infection might cause dramatic changes such as delirium, immobility, or a nutritional crisis. Collectively, age-related decline, and especially acute and chronic geriatric syndromes are the authentic phenotype of frailty, and should motivate confirmation through case-finding.

Simple Case-Finding of Frailty

Case-finding tools can be used proactively or opportunistically. Proactive case-finding uses measures which emphasize the frailty state, such as the electronic frailty index (eFI) (1). This is practical when the measure is already built into an existing electronic medical record.

Opportunistic measures tend to emphasize frailty is a syndrome that can be observed directly in clinical settings. The EFS is one of many opportunistic case-finding measures that capture the syndrome of frailty at the bedside, though not all will define components. Examples of simple case-finding tools include judgement-based measures such as the Clinical Frailty Scale (CFS) (2), physical performance-based measures such as gait speed (3), the frailty phenotype (4), and questionnaire-based measures such as the PRISMA-7 (5). A further comparison of these measures is discussed in the next section: When should I use it?

Estimating Severity

The degree of frailty has been defined using different paradigms. In one paradigm, there is a continuum from fitness to frailty. Here, a robust individual (more fit) has very few deficits and many assets. As the number of deficits accumulate, their status changes, silently at first. They become ‘apparently vulnerable’. Frailty then progresses with more deficit accumulation, moving from grades of mild to moderate to severe. This is the paradigm used by the Edmonton Frail Scale, the EFI (1), and CFS (2). Performance-based measures, the frailty phenotype and questionnaires typically do not typically estimate severity.

Clinicians should be cognisant of frailty severity in their communications with patients. Frailty severity is a strong predictor of outcomes such as mortality and institutionalization. It should influence the care and support strategy that clinicians recommend.

Defining Components

Component definition is the unique characteristic of multidimensional frailty measures such as the EFS. When we understand frailty as a “multidimensional syndrome”, the assessment of frailty should lead clinicians into action. The EFS walks us through case-finding and grading for prognosis and general care decisions, into a personalized analysis of the areas that require the greatest attention.

Some multidimensional frailty measures, such as the Frailty Index based on Comprehensive Geriatric Assessment (FI-CGA) (6), are derive the frailty score from CGA (comprehensive geriatric assessment). Other multidimensional measures, such as the EFS, are intended to be used earlier in the assessment, and not necessarily by experts in geriatric assessment. The EFS can thus be used to support individuals who are not trained in CGA to move the assessment and management plan forward. These may include physicians, nurse practitioners, therapists, social workers, pharmacists, community care workers, transition coordinators, and others.

Does the use of the EFS replace CGA or the involvement of experts? On the contrary, it should help better define the need and ensure the most appropriate referral. For example, specialists in the care of older adults might be appropriate when frailty is more severe or complex, or when there are difficult presentations of illness, high risk procedures under consideration, diagnostic uncertainty, or problems with symptom control.

References

1. Clegg A, Bates C, Young J, Ryan R, Nichols L, Ann Teale E, et al. Development and validation of an electronic frailty index using routine primary care electronic health record data. Age and ageing. 2016;45(3):353-60.

2. Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ 2005;173(5):489-95.

3. Cesari M. Role of gait speed in the assessment of older patients. JAMA. 2011;305(1):93-4.

4. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. The journals of gerontology Series A, Biological sciences and medical sciences. 2001;56(3):M146-56.

5. Raîche M. HR, Dubois MF, and the PRISMA partners. . User guide for the PRISMA-7 questionnaire to identify elderly people with severe loss of autonomy. In Integrated service delivery to ensure persons' functional autonomy. Edisem.147-65.

6. Jones, D., X. Song, A. Mitnitski and K. Rockwood (2005). "Evaluation of a frailty index based on a comprehensive geriatric assessment in a population based study of elderly Canadians." Aging Clinical and Experimental Research 17(6): 465-471.