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Record W2963982118 · doi:10.1159/000501168

Exploring Cognitive Frailty: Prevalence and Associations with Other Frailty Domains in Older People with Different Degrees of Cognitive Impairment

2019· article· en· W2963982118 on OpenAlexaboutno aff
Ellen De Roeck, Anne van der Vorst, Sebastiaan Engelborghs, G. A. Rixt Zijlstra, Eva Dierckx

Bibliographic record

VenueGerontology · 2019
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionGerontologyClinical Dementia RatingDementiaCognitive declineCognitive impairmentMedicineEffects of sleep deprivation on cognitive performanceMontreal Cognitive AssessmentPsychologyPsychiatryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cognitive frailty has long been defined as the co-occurrence of mild cognitive deficits and physical frailty. However, recently, a new approach to cognitive frailty has been proposed: cognitive frailty as a distinct construct. Nonetheless, the relationship between this relatively new construct of cognitive frailty and other frailty domains is unclear. OBJECTIVES: The aims of this study were to explore the prevalence of cognitive frailty in groups with different degrees of cognitive impairment, as well as to explore the associations between frailty domains, and if this varies with level of objective cognitive impairment. METHOD: Cross-sectional, secondary data from 3 research projects among community-dwelling people aged ≥60 years, with different degrees of objective cognitive impairment, were used: (1) a randomly selected sample (n = 353); (2) a sample at an increased risk of frailty (n = 95); and (3) a sample of memory clinic patients who scored 0.5 on the Clinical Dementia Rating scale - according to the "original" definition of cognitive frailty (n = 47). Multidimensional frailty was assessed with the Comprehensive Frailty Assessment Instrument - Plus and general cognitive functioning with the Montreal Cognitive Assessment. Descriptive statistics and linear regression were used to determine the prevalence of cognitive frailty and to explore the relationship between cognitive frailty and the other types of frailty in each sample. RESULTS: The prevalence of cognitive frailty increased along with the degree of objective cognitive impairment in the 3 samples (range 35.1-80.9%), while its co-occurrence with (one of) the other types of frailty was most frequent in the frail and community samples. Regarding its relationship with the other domains, cognitive frailty was positively associated with psychological frailty's subdomain mood disorder symptoms in all 3 samples (p ≤ 0.01), while there was no significant association with environmental frailty and social loneliness. The associations between cognitive frailty and the other types of frailty differed between the samples. CONCLUSION: Psychological and cognitive frailty are strongly associated, irrespective of the objective degree of cognitive impairment. In addition, it is shown that cognitive frailty can occur independently from the other frailty domains, including physical frailty, and therefore it can be seen as a distinct concept.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.300
Teacher spread0.238 · 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 designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2019
Admission routes1
Has abstractyes

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