FRAILTY PHENOTYPE AND ITS IMPLICATION ON CARDIOVASCULAR RISK, DEPRESSION, LONELINESS AND NEUROCOGNITION. AN EXPLORATORY STUDY
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".