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Enregistrement W1520395661 · doi:10.1111/j.1532-5415.2005.00510.x

Just What Defines Frailty?

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

Notice bibliographique

RevueJournal of the American Geriatrics Society · 2005
Typeletter
Langueen
DomaineMedicine
ThématiqueFrailty in Older Adults
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute on Aging
Mots-clésMedicineGerontologyMEDLINELaw

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,050
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,003
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,005
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,030
Tête enseignante GPT0,295
Écart entre enseignants0,264 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations86
Publié2005
Routes d'admission1
Résumé présentoui

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