Hearing Loss as a Cognitive Risk Factor: Exploring the Connection Between Presbycusis and Dementia: About 120 Cases
Bibliographic record
Abstract
Background: Dementia and presbycusis (age-related hearing loss) are common conditions among the elderly, both contributing to significant declines in quality of life. Emerging evidence suggests a link between hearing impairment and cognitive decline, but the strength and mechanisms of this relationship remain under investigation. Objective: This study aims to assess the incidence of presbycusis in patients with dementia and examine the correlation between hearing loss severity and cognitive impairment. Methods: A retrospective analytical study was conducted on 120 patients aged ≥65 years with confirmed diagnoses of dementia and presbycusis, treated at the Mohamed VI University Hospital in Marrakech from 2020 to 2023. Hearing loss was classified via pure tone audiometry, while cognitive function was measured using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Statistical analyses, including regression modeling, were used to evaluate associations, adjusting for age, sex, and comorbidities. Results: Among the 120 patients (mean age 78.6 ± 6.2 years), 70% had Alzheimer's disease, and 54.2% used hearing aids. A significant negative correlation was found between hearing loss severity and cognitive scores (p < 0.001). Regression analysis confirmed this association even after adjusting for confounding factors. Additionally, patients fitted with hearing aids demonstrated a statistically significant improvement in cognitive scores (p < 0.001). Conclusion: This study supports a strong association between presbycusis and cognitive decline in dementia patients, suggesting that hearing loss may exacerbate cognitive impairment. The observed benefits of hearing aid use highlight the importance of auditory rehabilitation in dementia care. Future research should further explore causal pathways and interventional strategies to improve outcomes in aging populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".