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The assessment of frailty in older people in acute care

2009· article· en· W1867953464 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAustralasian Journal on Ageing · 2009
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsGerontologyVulnerability (computing)InstitutionalisationScale (ratio)MedicineStressorHealth carePopulation ageingFrailty syndromePopulationEnvironmental healthFrailty IndexPsychiatryComputer scienceComputer security

Abstract

fetched live from OpenAlex

Today in Australia we face an ageing population; this will lead to increasing pressure on an already overtaxed health system. It is imperative that we set in place a refined and unified method to assess and predict health outcomes in frail older people As a person ages there is an accumulation of stressors and lifetime risk factors that combine with multi-organ physiological change to give rise to an increased risk of poor outcomes (e.g. death, institutionalisation, falls and iatrogenic disease). This vulnerability can be quantified by a frailty scale. Frailty can be seen as a measurement of the level of support that is required by a person. This measurement is useful as a predictive tool to determine the health services needed by the patient and for research purposes to assist in public health planning. In recent years effort has been made to determine the predictive strength of these scales and their efficacy in improving patients’ final outcomes. There are a number of different frailty scales currently in use, each with different emphases and measuring different outcomes. The majority of studies looking at frailty to date have been conducted in the community [1,2]. Of those that have looked at patients in a hospital setting [3,4], there has been a trend to use scales that are multifaceted, taking into account the complex nature of frailty, such as the Reported Edmonton Scale reported by Hilmer et al. in this edition of the Journal. The Reported Edmonton Scale has several attractive features: it can be assessed by interviewers without medical training, making it easier to use for larger studies; it has been designed to capture the pre-morbid frailty despite being collected in a hospital setting; and it correlated well with a global assessment of frailty as assessed by a geriatrician involved in comprehensive geriatric assessment. Given that the Reported Edmonton Scale incorporates components of cognition, independence, polypharmacy and comorbidity, it is no surprise that the scale correlated well with established methods of measurement for these domains. However, this finding does emphasise that the scale reflects the complex multi-faceted nature of frailty. Where to next? The challenge for the Geriatric Medicine research community is to identify which frailty measure will be the most useful in our clinical trial, epidemiology and observational research practice. At this stage it is unclear which measure will survive. However, incorporation of frailty measures into routine research must be a good thing, as it implicitly acknowledges that medical research should and must include the frail older person.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.332
Teacher spread0.316 · 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