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Enregistrement W2608069909 · doi:10.1093/ageing/afx052

Acute hospital admission of the frail older person: an opportunity to discuss future care

2017· editorial· en· W2608069909 sur OpenAlexaboutno aff
Lucy Pocock, Debbie Sharp

Notice bibliographique

RevueAge and Ageing · 2017
Typeeditorial
Langueen
DomaineMedicine
ThématiqueFrailty in Older Adults
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute for Health and Care Research
Mots-clésMedicineAcute hospitalGerontologyOlder peopleHospital admissionAcute careHealth careInternal medicine

Résumé

récupéré en direct d'OpenAlex

More than a 3rd of the UK population now lives to the age of 85 [1] and the absolute number of older adults in the population is increasing significantly [2]. Frailty is defined by Clegg et al. [3] as ‘a state of increased vulnerability to poor resolution of homoeostasis after a stressor event, which increases the risk of adverse outcomes, including falls, delirium and disability’. The prevalence increases with age, with up to half of adults over the age of 85 estimated to be frail [3, 4]. It is now well reported that increasing frailty is important as a prognostic indicator, with frailty status being strongly associated with both quality of patient outcome and mortality [5]. A recent NHS Benchmarking Network report suggests that 52% of Trusts in the UK now have a specialist frailty unit [6] and, in primary care, the new GP contract will require practices to actively identify their frail patients and review them appropriately [7]. Measurement of frailty can be performed in several ways and there are a number of tools in use. The Comprehensive Geriatric Assessment (CGA), the gold standard for the management of frailty in older people, is an holistic, multidimensional, interdisciplinary assessment of an individual and has been demonstrated to be associated with improved outcomes in a variety of settings [8]. The CGA can also be used to quantify an individual's degree of frailty in a Frailty Index (FI-CGA) [9]. In this edition of Age and Ageing Hatheway et al. present data from secondary analysis of a cohort study, initially reported in 2011, including 409 elderly patients admitted to a tertiary care teaching hospital in Canada [9]. The current study examines the relationship between the recovery of mobility and balance, initial treatment response and underlying frailty. Patients who were more frail at baseline, as reported by the patient or their family, were less likely to recover their balance and mobility (odds of no or incomplete recovery increased by 1.06 with each 0.1 increment in the FI-CGA at baseline) and this was similarly dependent on age (1.010). Improvement in mobility and balance over the first 48 h was associated with greater improvement overall and with shorter recovery times. Patients with only mild mobility impairment recovered sooner—by Day 5 about 50% with mild impairment had recovered, compared to 25% of those with moderate impairment and 10% with severe impairment. Declining mobility in the first 48 h represented a relative risk of death of 17.1. The relationship between degree of baseline frailty and recovery was independent of the extent of mobility impairment at admission. This study has immediate clinical relevance and contributes to the growing evidence base on this important topic. Although secondary analysis of existing data can be problematic, as the available data are not collected to address the particular research question, this study makes appropriate use of routinely collected data with a reasonable sample size. To improve generalisability, it would be helpful to see the analysis of data from a number of hospital sites. Almost two-thirds of people in the UK, aged over 85, die during a hospital admission [10]. The likelihood of dying in the 12 months following a hospital admission increases with age [11], however, it is difficult to predict which older patients are at risk of dying during, or soon after, a hospital admission. This study offers one approach to assessing and managing the frail older patient with acute illness to appropriately tailor their ongoing care. If we are able to identify the patients who are most likely to recover, we can target them for intensive rehabilitation and early discharge planning. Equally, those patients who are at greater risk of dying can be offered the opportunity to have advance care planning discussions and palliative care input, ensuring that unnecessary interventions are minimised. Frailty is recognized as an increasing challenge in the care of older people. This study offers a simple approach to assessing the likelihood of recovery of frail older people who are acutely unwell. Identification of patients who are less likely to recover will allow appropriate care planning decisions to be made.

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)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,048
Score d'incertitude au seuil0,778

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
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 Opus0,014
Tête enseignante GPT0,291
Écart entre enseignants0,277 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

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

En bref

Citations3
Publié2017
Routes d'admission1
Résumé présentoui

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