Neuropsychological profile of hearing-impaired patients and the effect of hearing aid on cognitive functions: an exploratory study
Bibliographic record
Abstract
Few studies have investigated the neuropsychological profile of Hearing Loss (HL) subjects and the effects of hearing-aid on cognitive decline. We investigated the neuropsychological profile of HL patients at baseline and compared the neuropsychological profiles of patients with and without hearing-aid at 6 month. Fifty-six HL patients and 40 healthy subjects (HC) underwent neuropsychological and behavioral examination and were compared at baseline. Changes at follow-up were compared between HL patients with (N = 25) and without (N = 31) hearing-aids. At baseline, significant differences between HL and HC were found in MOCA test, Raven's Coloured Progressive Matrices (CPM) and SF-36. Among mild-HL patients, patients with hearing-aid significantly improved on the Clock Drawing Test (CDT) as compared to patients without hearing-aid. Our findings indicate that hearing loss is associated with both a reduced efficiency of the global cognitive state and a worse quality of life as compared to HC, supporting the association between HL and cognitive impairment. Moreover, only patients with mild-HL shows some cognitive improvement after using hearing-aid, suggesting that rehabilitative strategies may be more effective to delay cognitive decline in such patients. However, we cannot exclude that hearing-aids may affect cognitive decline in more severe-HL, but a longer follow-up is needed.
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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) | 0.001 | 0.001 |
| 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) | 0.002 | 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".