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Record W2771753769 · doi:10.1111/ajag.12487

Frailty prevalence and factors associated with the Frailty Phenotype and Frailty Index: Findings from the North West Adelaide Health Study

2017· article· en· W2771753769 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAustralasian Journal on Ageing · 2017
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsDalhousie University
FundersResthaven Incorporated
KeywordsMedicinePolypharmacyFrailty IndexGerontologySocioeconomic statusObesityDemographyEnvironmental healthInternal medicinePopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence of frailty and associated factors in the North West Adelaide Health Study (2004-2006) using the Frailty Phenotype (FP) and Frailty Index (FI). METHODS: Frailty was measured in 909 community-dwelling participants aged ≥65 years using the FP and FI. RESULTS: The FP classified 18% of participants as frail and the FI 48%. The measures were strongly correlated (r = 0.76, P < 0.001) and had a kappa agreement of 0.38 for frailty classification, with 37% of participants classified as non-frail by the FP being classified as frail by the FI. Being older, a current smoker, and having multimorbidity and polypharmacy were associated with higher frailty levels by both tools. Female, low income, obesity and living alone were associated with the FI. CONCLUSION: Frailty prevalence was higher when assessed using the FI. Socioeconomic factors and other health determinants contribute to higher frailty levels.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.062
GPT teacher head0.316
Teacher spread0.254 · 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