Frailty Include Multidimensional and Dynamic Factors?

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© Springer Nature Switzerland AG 2020
P. Tandon, A. J. Montano-Loza (eds.)Frailty and Sarcopenia in Cirrhosis

16. Should Frailty Include Multidimensional and Dynamic Factors?

Darryl B. Rolfson1  

Division of Geriatric Medicine, Department of Medicine, University of Alberta, Edmonton, AB, Canada



Darryl B. Rolfson


FrailtyMultidimensionalDynamicModelsMeasuresFunctionGeriatric syndromeImplementation

At the heart of applied research on frailty is a nagging uneasiness about its meaning and therefore its measurement. This problem has been true right from the start, as frailty was emerging as a meaningful clinical paradigm [13], distinct from comorbidity and disability. A narrative emerged that dichotomized frailty either as a clinical syndrome [4], along with pathophysiology and promise for biological markers and treatment, or as a state of “accumulated deficits,” aligning it with robust risk modelling and multidimensionality [5, 6]. In publications since then, a lack of consensus on the nature of frailty is commonly cited, and likewise an operational definition [7] remains elusive. This has left clinicians with a dilemma to adopt one of the traditional viewpoints, move forward with a sense of uncertainty about its meaning, or simply ignore it. If clinicians are having such difficulty, then they should not be surprised to learn that their patients are equally unsettled when they hear the term, and commonly assign negative connotations that their clinicians never intended [8, 9].

Were it not for the evidence that frailty, however defined, was common [10, 11] and strongly associated with adverse outcomes [1215], it would have been discarded long ago as a passing curiosity. Instead, it has been well-described as “the most problematic expression of population aging” [16] and as an emerging public health priority [17] and indeed is estimated to be the most common pattern in the last year of life, exceeding traditional clinical clusters such as single-organ failure, dementia, and cancer [18].

In Frailty and Sarcopenia, one of the two traditional conceptual models of frailty, the physical phenotype, has been largely adopted. This syndrome-based model may be well-suited to questions that frame frailty as a disease with its own pathogenesis and prognosis, raising hope for future markers and interventions. However, here I will argue that the reductionist approach is problematic from a clinical perspective. The messy whole of frailty, along with its multidimensional and dynamic aspects, is a more authentic construct in clinical practice, as it better approximates the experience of the individual who lives with it. I will build this argument by elaborating first on the various conceptual models, then link these to a family of candidate measures, and provide closing remarks on implementation.

  1. 1.

    Frailty in nature. Does frailty exist in the natural world? If so, should we think of it as an observable physical trait such as jaundice, as an illness script such as cirrhosis, or as a state of vulnerability such as the Child-Pugh score [19]? In clinical practice, all three of these entities are meaningful and belong to an interrelated whole.

    One useful way to make sense of a complex entity such as frailty is to distinguish between observable variables (directly observed or measured) and latent variables (inferred from observable variables). In the preceding example, jaundice would be a directly observable variable. By comparison, cirrhosis, as a latent variable, requires a clinician to render and then integrate information from various sources. The diagnosis of cirrhosis becomes a mental construct, framed as an illness script, and based on expert clinical judgment. Illness scripts such as cirrhosis are thought to exist in nature, as are the observable traits such as jaundice that comprise them. Risk modelling tools such as the Child-Pugh score are also latent variables that can apply what we know about a defined population to an individual who has a similar clinical pattern. While a prediction tool is strictly a latent variable, such an entity can be powerful when used in the appropriate setting to model expectations and guide dialogue and decisions.

    Likewise, frailty has been framed as a phenotype with observable characteristics [4, 20], as a clinical syndrome [21, 22] with presumed underlying pathophysiology, and as an exaggerated state of risk [23, 24], with special vulnerability to external variables. There are no hard lines between these definitions, and each part comprises the whole of frailty. Reducing frailty to just one of these frameworks makes it a less authentic representation. Some classify frailty as an emerging “geriatric syndrome” [25, 26], adding it to the pantheon of falls, immobility, polypharmacy, urinary incontinence, delirium, and dementia. It may even prove to have added status as a composite and overarching measure [27], reframing the traditional giants as “frailty syndromes.”

    The unique challenge for the taxonomists is that frailty is not univocal: the same word can be used to mean very different things, which happen to be closely related, but cannot be easily teased apart. Slippage in the meaning of a word makes discourse difficult in both research and clinical settings, as has been recognized about frailty for some time [28]. One option is to abandon the term altogether. Another is to work toward greater particularity and consensus on the definition of the term, in order to destigmatize it. The following different conceptual models of frailty illustrate the attempts to do just that.


  2. 2.

    The physiologic basis of frailty. A physiological basis for frailty has been theorized for some time [29]. In this view, frailty is a decline in homeostatic function, strength, and physiologic reserve leading to increased vulnerability and making it distinct from sarcopenia, which is a loss of muscle mass, and function with age [30]. It was with this physiology in mind that the phenotype model was proposed [4], along with a hypothesized “cycle of frailty” [31]. The phenotype, first derived for use in the Cardiovascular Health Study, includes five single point items (weight loss, slow walking speed, low levels of physical activity, subjective exhaustion, and weakness) in which a score of 1–2 is “pre-frail” and 3 or higher is frail. A number of physiologic, molecular, and genetic alterations were proposed to explain the multisystem nature of frailty.

    This opened doors to a massive research agenda that has inspired investigation in a diverse array of fields. The expectation is that over time such research would be rewarded with a bridge to biological markers that could be used for diagnostic and therapeutic approaches. Indeed, there are many candidate markers based on an association with frailty including hormones (elevated cortisol, low androgens), low vitamin D, glycoproteins, and molecules that relate to inflammation, endothelial dysfunction, insulin resistance, and oxidative damage. However, thus far, none of these have been proven to be “individually of sufficient diagnostic and prognostic capacity to be valid in clinical settings” [32].

    The “frailty phenotype”(FP), as it came to be known, did emerge as the most popular instrument to measure frailty in research settings [33] and offered a viable alternative to chronological age in risk modelling [4, 3436]. Despite this, it has not found widespread acceptance in clinical settings, possibly, because the criteria are not clinically intuitive and special equipment and training are required to administer the test.


  3. 3.

    Frailty as an accumulation of deficits. Almost simultaneously, another approach to understand and measure frailty arose which was designed to include a more broad set of variables that could be drawn from large datasets. In comparison to the FP, which understands frailty as a clinical syndrome, the deficit accumulation model, typified by the Frailty Index (FI) [5, 37, 38], frames frailty as a state of exaggerated vulnerability that can be constructed from a sufficiently rich clinical database or comprehensive geriatric assessment. According to a standard procedure [39], potential deficits (scored as 0 or 1) were defined as any set of variables that accumulate with age, might theoretically threaten health and independence, and collectively cover several body systems. If the list (or denominator) is at least 30, no greater weight need be assigned to any one variable. The FI is the quotient of actual over potential deficits, scored between 0 and 1.

    As with the FP, the validation of the FI was largely based on its theoretical sophistication and its predictive validity. With aging, deficits accumulate with little impact on health or independence due to compensating assets. However, the accumulation is clearly nonlinear, accelerating over time regardless of age, and tends to proceed based on stochastic events such as new chronic diseases and the stable effects of accidents.

    Deficit accumulation helps explain the state of silent vulnerability that becomes apparent only under conditions of stress. It is multidimensional and flexible to apply in different research contexts. Risk modelling is clearly established in various populations for outcomes such as mortality, institutionalization, hospitalizations, and other adverse outcomes [4042] and has been cross-validated in numerous populations internationally.

    The original FI does not intuitively align with the way that frontline clinicians gather and analyze clinical information. It is end-loaded, as its calculation requires a pre-defined database of candidate deficits in the population of interest, populated with the particular deficits, absent or present in selected individuals.

    An electronic version has been implemented in primary care settings in the United Kingdom [43], and the FI based on comprehensive geriatric assessment (FI-CGA) is also beginning to find more mainstream use as an adjunct to comprehensive geriatric assessment [44, 45]. In one regard, the alignment of the FI with multi-morbidity does resonate with clinicians, in the sense that frailty is the logical extension as multi-morbidity accumulates and functional performance begins to supersede any single disease [46].


  4. 4.

    The multidimensional expression of frailty. In a consensus-based process governed by modified Delphi methodology, top experts drawn from both traditions of frailty definition were brought together in 2013 [7], and the level of agreement on a large number of statements regarding frailty was determined. There was broad agreement that frailty is a multidimensional syndrome with decreased reserve and diminished resistance to stressors. Importantly, there was strong agreement that these dimensions should include not only physical performance such as gait speed and mobility but also nutritional status, mental health, and cognition. The group agreed that it is useful to define frailty in clinical settings to allow for prevention and treatment, but could not agree on an operative definition or set of clinical or laboratory biomarkers for this purpose.

    Even social vulnerability, sometimes known as “social frailty,” is an important dimension of frailty also, but is not always included in its expanding multidimensional definition. Still, social gradients appear to be present for frailty [47], and the correlation with the frailty index is strong in various community-based populations worldwide ( [4850)]. Social vulnerability also influences mortality independent of frailty [51].


  5. 5.

    Frailty as a functional construct. Functional status, or the ability to carry out activities of daily living, can be derived from self-report, collateral history and by performance-based measures. Function is right at the interface between the intrinsic capacity of an individual and the surrounding social environment, including stable and unstable variables. Function represents integration and is by nature a multidimensional construct.

    The World Health Organization in 2016 affirmed its emphasis on the transition state (declining capacity) between healthy aging (high functioning and stable) and disability (significant losses) [17]. Although the term frailty is not used explicitly, this transition state is clearly being adopted as a surrogate for frailty. If so, then it will be important to be clear on the frailty constructs in relation to healthy aging and disability, recognizing the multidimensional nature of healthy aging and disability [52, 53].

    Nonetheless, both the 2013 consensus definition and the WHO model emphasize frailty (or the “transition state”) as a public health priority and place functional status as a central feature of its manifestation. The WHO has adopted “intrinsic capacity” as the underlying construct to explain this multidimensional transition, constituting the domains of cognition, locomotion, sensory abilities, psychological status, and “vitality,” including hormonal function, energy metabolism, and cardiorespiratory function [54]. It should be emphasized that apart functional status, no unique measure of intrinsic capacity per se has been validated.


  6. 6.

    The dynamic aspects of frailty. The notion that frailty is by nature unstable and expressed in functional terms was described quite early in its conceptualization. After stating the important differences between disability and frailty, Campbell defined “unstable disability” as an expression of frailty when function fluctuates markedly with minor external events [55]. This early concept of frailty is a lucid illustration of how the various models of frailty work together. Not only does unstable disability acknowledge frailty as both a state and a syndrome, and capture its functional and the multidimensional manifestations, but it also introduces the important role of external events, or stressors, to distinguish frailty from stable disability.

    Recent enthusiasm for clinical research in frailty comes from those clinical specialties that hope to understand its interaction with stress, whether intrinsic or extrinsic. Frailty is of special interest in acute surgical and medical settings where care decisions are being made without accounting for the quiet intrinsic state of frailty. Likewise, frailty may become unmasked in individuals for whom functional status is highly influenced by unstable social factors. The modifiable nature of the physical and social stressors in frailty might make a difference to outcomes such as mortality, institutionalization, quality of life, and functional decline. This has typically motivated a dialogue regarding risk prediction and modification. Risk modelling demonstrated with the FP and FI are not instrument-specific. Similar predictive validity has been demonstrated with frailty measures that are judgment-based, performance-based, functional, and multidimensional [5660].

    Systematic reviews in various populations have shown cross-sectional but independent associations between frailty and adverse outcomes. For example, frailty assessment informs surgical risk for mortality, functional decline, and major adverse cardiac or cerebral events (MACCE) in ways that have not been captured with traditional surgical risk scores. The predictive value was best with those instruments that emphasized mobility, nutrition, and multidimensionality [14].

    Likewise, frailty in those undergoing cardiac surgery significantly raised the risk of MACCE, mortality, and functional decline [61]. Cancer patients with frailty have a higher risk of all cause and postoperative mortality and treatment complications [62]. Heart failure patients with frailty were significantly more likely to experience adverse events, hospitalization, and death [63]. In critical care settings, frailty is independently associated with death in the hospital and long term [64].

    Taken together, these systematic reviews and a countless other cross-sectional studies establish a strong association between frailty and adverse outcomes, but do not establish causality. We are now in a new era of enquiry, which aims to better establish causality through longitudinal cohorts, and more importantly, determine whether interventions that address frailty or its component dimensions prior to anticipated stress might result in improved outcomes.


  7. 7.

    Geriatric syndromes. The dynamic, functional, and multidimensional nature of frailty can perhaps be best illustrated by what is known about the other geriatric syndromes that comprise it. One excellent example of this is delirium, a particular manifestation of “unstable disability,” showing what can happen when a particular predisposition (i.e., the state of frailty) and acute precipitants (the stressors) interact. Over 20 years ago, Inouye et al. demonstrated that delirium is caused by both precipitating and predisposing variables [65, 66]. In older adults who live with frailty and functional dependency, illness presentations such as delirium may be more atypical [67], reflecting not only the acute precipitant but the particular systems of vulnerability of the individual. Thus, when the dominant pattern of frailty in a particular individual leans toward cognitive impairment, acute illness may be first manifest as delirium, rather than another geriatric syndrome such as acute immobility. Here, frailty can be visualized as a balance scale in which assets and deficits are perfectly in balance. Minor acute stressors will have an exaggerated impact and will be expressed in functional decline and in illness presentations that reflect the particular constellation of underlying vulnerabilities.

    Aside from delirium, other geriatric syndromes that seem to follow the same pattern described by Inouye, in which the predisposing variables rival or exceed the precipitating variables in etiologic importance include falls, immobility, urinary incontinence, and acute nutritional crisis. The precipitants may be anything from acute illness to a stressful intervention such as surgery, or even an acute decline in social supports

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Aug 3, 2021 | Posted by in GASTROENTEROLOGY | Comments Off on Frailty Include Multidimensional and Dynamic Factors?

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