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Record W7056693888

FRAILTY PHENOTYPE AND ITS IMPLICATION ON CARDIOVASCULAR RISK, DEPRESSION, LONELINESS AND NEUROCOGNITION. AN EXPLORATORY STUDY

2024· dissertation· en· W7056693888 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2024
Typedissertation
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessNeurocognitiveDepression (economics)PopulationGeriatric Depression ScaleExploratory researchQuality of life (healthcare)Vulnerability (computing)Cognition
DOInot available

Abstract

fetched live from OpenAlex

Given the aging population and its associated pathologies, it is essential to better understand frailty syndrome to enhance quality care and daily life for the elderly.. Frailty is a biological syndrome of reduced reserve and resistance to stressors, resulting from the cumulative decline of multiple physiological systems, leading to vulnerability and poor outcomes. The current study aims to determine the influence of frailty phenotype on cardiovascular risk, depression, loneliness, neurocognitive functioning, and in community-dwelling older people. Our sample consisted of 26 participants aged above 60, each of whom underwent a protocol to assess our different variables, subjects were grouped based on their frailty phenotype. Neurocognitive functioning was measured with the Addenbrooke Cognitive Examination III (ACE-III), Depression was assessed with Geriatrice Depression Scale (GDS), loneliness with the Échelle de solitude de l'Université Laval (ESUL) and cardiovascular risk was measured with the U-Prevent algorithm. Results showed that frailty was significantly associated with memory impairments and loneliness in the overall sample. There were no significant differences in cardiovascular risk, depression and other neurocognitive functions, according to the frailty phenotype. Frailty may be a particularly important factor in memory loss and loneliness, highlighting the need for prevention and intervention strategies to decrease the risks for frailty.

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.065
GPT teacher head0.369
Teacher spread0.304 · 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 teacher head, not a consensus.

Study designOther design
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

Citations0
Published2024
Admission routes1
Has abstractyes

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