Functionality and socio‐demographic factors in chilean’s community‐dwelling elderly with subjective cognitive complaints . The GERO Cohort
Bibliographic record
Abstract
Abstract Background Subjective cognitive complaints (SCCs), defined as cognitive concerns of people who may or may not have deficits in objective, is considered a predictor for cognitive and functional decline and incident to dementia risk of progression to dementia. SCC is a heterogeneous condition associated. Most of the studies have been carried out in populations other than those of Latin America. The objective of this study was to analyze the socio‐demographic and functional profile in SCC elderly with and without cognitive impairment. Method The GERO cohort is a prospective cohort study of community‐dwelling elderly with SCC, without dementia, aged 70 or older living in Santiago, Chile. Participants were identified by a household census and information on demographics, biomedical, psychosocial, neuropsychological, neuropsychiatric, and motor function were collected by means of questionnaires and evaluations. Montreal Cognitive Assessment (MOCA) was used to compare individuals with and without cognitive impairment (MOCA score ≤ 21 and > 21 respectively). Functionality was measured with the Pfeffer Functional Activities Questionnaire (FAQ) and Technology Activities of Daily Living Questionnaire (T‐ADLQ) that yield a global score and score by domain of activities of daily living (ADL), i.e basic (BADL), instrumental (IADL), and advanced ADL (a‐ADL). Result From May 2017 to December 2020, a total of 17,759 households were successfully approached, identifying 2,533 eligible subjects, of which 299 individuals were included. After evaluation, 7 individuals were excluded for different reasons and 291 individuals were analyzed, female 80% (n = 243). The age of the individuals was 76.8 ± 5 years old, 60% of the participants were older than 75 years old. Participants with cognitive impairment compared to those without it were older (p = 0.003), with lower education years (p = <0.001), lower income (p = 0.036), lower MMSE score (p = <0.001), decline in a‐ADL (p = 0.006) and with more hypertension prevalence (p = 0.009) Conclusion Few other studies addressed cognitive complaint and functionality decline in recruited elderly at home. Older adults with cognitive impairments are characterized by less years of education, income, poor functionality and more comorbidities. Future multidimensional and prospective analysis of this cohort could bring more information about this association.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".