Correlation between Mild Cognitive Impairment and Functional Status among Elderly
Bibliographic record
Abstract
Background: Recently, no standard criteria exist with regard the specific or theoretical definition of minimal functional limitation in people with MCI.Aim: To Correlate mild cognitive impairment and functional status among elderly.Methods: A cross sectional study conducted on 225 participants at nursing homes in Egypt. A comprehensive geriatric assessment including medical history and physical examination was carried out for each participant. Cognitive functions were evaluated using both the Arabic translation of the Mini-Mental State Examination (MMSE) and the Arabic version of the Montreal Cognitive Assessment test (MoCA). Taking in account educational level, where diagnoses of mild cognitive impairment (MCI) if MMSE≤17 for illiterates; MMSE ≤20 for primary school graduates (≥6 years of education), MMSE≤24 for junior school graduates or above (≥9 years of education) and MoCA with Score less than or equal 24 indicates MCI in illiterate, Functional assessment was done by the Activities of Daily Living (ADL) scale, and the Instrumental Activities of Daily Living (IADL) scale.Results: This study indicates that there is no significant difference between those with MCI and those with normal cognitive function in ADL and IADL.Conclusions: MCI is frequent in older people. Our study suggests that there is no significant difference between those with MCI and those with normal cognitive function in ADL and IADL. Further studies are needed to determine the correlation between MCI and function status.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".