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Just What Defines Frailty?

2005· letter· en· W1520395661 on OpenAlexaboutno aff
Alfred L. Fisher

Bibliographic record

VenueJournal of the American Geriatrics Society · 2005
Typeletter
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersNational Institute on Aging
KeywordsMedicineGerontologyMEDLINELaw

Abstract

fetched live from OpenAlex

The term frailty is frequently used within the geriatrics world to describe patients who are in poor overall health, are vulnerable to the ill effects of a variety of environmental stressors, and are further at high risk for worsened morbidity, worsened disability, and mortality.1–4 Clinical experience and clinical research demonstrate that these patients exist, are heavy users of medical services, and have a tough lot in life. Despite our ability to conceptualize and study these patients in the aggregate, a simple consensus definition and criteria for frailty has remained elusive.2,5–7 The elusiveness of the definition of frailty reflects not only the challenges in defining a clinical syndrome where the exact etiology and pathophysiology are unknown but also the challenges of defining the boundaries of a syndrome that has medical, functional, and social components. The work of Mitnitski et al. in this issue adds to this debate.8 They present data from 11 clinical cohorts with 36,424 patients and examine the relationship between a frailty index and age and mortality. The frailty index is a measure that converts the percentage of deficits present or absent in a particular patient into an index score that varies between 0 and 1, with 0 reflecting no deficits and 1 the presence of all deficits.9 This measure was previously developed and validated on cohorts from Canada alone, so a major goal of this study was to determine the extent to which the frailty index can be generalized to other populations.9,10 To accomplish this goal, they used data from longitudinal studies of older patients drawn from Canada, Australia, Sweden, and the United States. They determined frailty index scores for the patients in the cohorts using primary data from the underlying studies. Because the primary data collected from each study was somewhat different, the deficits examined in each cohort vary. They include data from institutional and disease-specific (cardiovascular disease and breast cancer) cohorts for comparison. They find that the frailty index score correlates strongly with age for men and women in the general cohorts but not the disease-specific or institutional cohorts. The importance of the frailty index score is its strong association with mortality. Increasing frailty index scores lead to an exponential increase in mortality rate, and this association holds true for men and women, with women having a slightly lower death rate for any given score. An important point to bear in mind about the frailty index is that it includes not only physiological problems, such as lack of strength or stamina, but also disease-related, psychological, and social problems. It is the inclusion of these additional dimensions in the frailty index that puts the frailty index at odds with findings of other groups who have defined frailty in more-limited terms.2,3,5,11 For example, a recent review defined frailty in physiological terms independent of comorbid illnesses and disability, with frailty representing the decline in physiological constitution due to aging and disease. The comorbid illnesses present in many frail patients and the disability resulting from illness and frailty are developed as separate concepts that interact with physical frailty but remain separate. These ideas are an extension of prior work that began to reframe frailty as a biological syndrome characterized by declines in physiological reserves and difficulty in coping with stressors.1,3,11 In contrast, Mitnitski et al. opt to take a broad view of frailty and include a range of comorbid illnesses, measures of disability, and social and psychological issues into their frailty index. The issue of whether frailty is simply defined by physical manifestations of vulnerability or should have a broader definition appears to be the crux of the current debate. Considering social and psychological issues, disability, and medical illnesses as parts of frailty is conceptually simpler and more holistic than considering them separately. As has recently been pointed out, this holistic approach is consistent with the principles of geriatric medicine practice and offers the potential to capture the full effect of frailty.6 It is appealing to think that a patient who has not only physical frailty but also depression and functional dependence would be “frailer” and have a worse prognosis than one who lacks these problems. In the frailty index developed by Mitnitski et al., this patient would be clearly identified as more frail. Nevertheless, could frailty simply be physical, with comorbid illnesses and disability being linked but independent entities? Work in experimental animals, such as mice, fruit flies, and worms, demonstrates a component of physical decline during aging.12–14 For example, in the nematode Caenorhabditis elegans, dramatic declines in muscle mass and mobility as well as multiple physiological parameters accompany aging.12,14–16 These declines are not uniform between genetically identical individuals of the same age in a population; instead there is significant variation that likely reflects some of the random effects of organismal aging. Just as in humans, physical frailty in these experimental animals has prognostic implications.12,14,16 The development and progression of frailty identifies the individuals in the population who are at high risk for short-term mortality. Additionally, genetic mutations or dietary manipulations that extend lifespan also delay the development of frailty.13 This delay in frailty is an obvious and striking aspect of these mutants and has been commented on.12,14 Together, these findings argue for a physical component of frailty that is tied to individual aging and independent of disability and comorbid disease. Limiting the definition of frailty to physical frailty may serve to simplify and expedite research. Frailty may ultimately prove to be too complex to study without applying a reductionist approach to create criteria that are specific and perhaps even quantifiable at a physiological level. Often, simpler definitions are more practical for research purposes by helping to streamline study design and by making comparisons between different centers and studies more uniform. Criteria have been proposed based upon hypotheses about the underlying pathophysiology about the physical dimension of frailty.3,11 Application of these criteria to a patient cohort finds that these criteria are also successful in identifying patients at high risk of mortality. A challenge of this approach will be finding criteria and mechanisms that are able to accurately classify frail and nonfrail patients and are present before frailty becomes irreversible. But could the inclusion of disability or comorbidity provide this additional power? Perhaps the declines in functioning or worsening of comorbid illness might be more sensitive markers of frailty than physical parameters alone. There is probably little debate about whether frailty has physical components or that aging contributes to frailty, but whether limiting the definition and study of frailty to these physical components will help or hurt efforts to understand frailty is still an open question. Although the theoretical, practical, and philosophical issues surrounding the definition of frailty can be a source of continued debate, solutions to the standoff will need to come from clinical studies examining the performance of models based upon the broad and limited definitions. The goal of frailty research is to finally be able to understand the biological, medical, and environmental factors that together create the phenomenon of frailty and then to be able to intervene in this process.17 Current data, as exemplified by the paper from Mitnitski et al., suggest that both approaches can work, but the concern for future studies is which approach will prove more accurate and practical for the development of successful intervention studies. Until this time, keeping an open mind is the best approach. Future work on this issue will greatly enhance understanding of frailty and be of great interest to the geriatrics community. The author has no conflicts of interest to disclose. This work was funded by a grant from the National Institute on Aging. The sponsor had no role in the data and preparation of his paper.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0020.011
Scholarly communication0.0040.010
Open science0.0020.003
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.295
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations86
Published2005
Admission routes1
Has abstractyes

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