Thyroid Functions and Cognitive Decline in the Elderly
Bibliographic record
Abstract
Background The maintenance of cognitive health depends on thyroid hormones, and it is becoming more widely acknowledged that thyroid hormone issues may be a factor in cognitive decline in the aged. Objective This study aimed to investigate the association between thyroid hormone levels and cognitive decline among elderly individuals, considering the influence of age-related factors and comorbidities. Methodology Over the course of two years, 218 adults 60 years of age and older with clinically diagnosed hypothyroidism or subclinical thyroid disease were included in a prospective observational research. Serum levels of thyroid-stimulating hormone (TSH), free thyroxine (T4), and free triiodothyronine (T3) were measured at baseline and at 6, 12, 18, and 24-month intervals to evaluate thyroid function. The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were used to assess cognitive function at the same intervals. Factors linked to cognitive deterioration were identified using multivariate regression analysis. Results The study found that TSH levels decreased from 3.20 ± 1.82 µIU/mL at baseline to 2.80 ± 1.51 by 24 months (p < 0.001), while free T4 levels increased from 13.50 ± 2.53 pmol/L to 14.20 ± 2.52 pmol/L (p = 0.020). Cognitive scores declined significantly, with MMSE scores dropping from 23.27 ± 4.64 to 21.80 ± 4.89 (p = 0.005) and MoCA scores from 21.20 ± 5.11 to 20.03 ± 5.51 (p = 0.012). Conclusion The results show a strong correlation between thyroid malfunction and cognitive loss in the elderly, emphasizing the need to closely monitor thyroid function to maintain cognitive function in this population.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".