Mediator Role of Frailty and Biological Deficits in Dementia Prognosis—Retrospective Cohort Study
Bibliographic record
Abstract
Background and Objectives: Dementia is increasing worldwide. This study aimed to examine the impact of comorbidity burden and frailty on dementia prognosis in patients with dementia. Materials and Methods: This retrospective cohort study was conducted with 47 patients with dementia who were followed for up to two years. The Modified Charlson Comorbidity Index (MCCI), Mini-Mental State Examination (MMSE-E), and Edmonton Fragility Scale were used besides laboratory and clinical findings. Results: The mean age of the 47 patients was 78.77 ± 12.44 years. During the follow-up period, MMSE-E scores were observed to improve in 50% of the patients. Initial MMSE-E scores were found to be lowest in men and patients with coronary artery disease or depression, while final MMSE-E scores were observed to be lowest in patients with depression and low vitamin B12 or vitamin D levels. The rates of decrease in MMSE-E scores in non-, moderately and severely frail patients were 21.4%, 55.6%, and 70.6%, respectively. There was a moderate negative correlation between MMSE-E scores and both comorbidity burden and frailty scores. The mediation analysis revealed that frailty was a complete mediator, and that comorbidity burden led to an increase in frailty and a decrease in MMSE-E scores. During the follow-up period, patients with moderate frailty, hypertension, diabetes mellitus, alcohol and tobacco use, low B12 levels, or hypothyroidism showed an increased risk of decrease in cognitive functions. Conclusions: There was a significant association between dementia prognosis and both frailty and biological deficits. We recommend the adoption of a syndemic approach in the follow-up of dementia, as we believe that the prevention of frailty and associated biological deficits will contribute to slowing dementia’s clinical course.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".