Effect of hearing loss on cognitive function in patients with mild cognitive impairment: A prospective, randomized, and controlled study
Bibliographic record
Abstract
Background Hearing loss (HL) may increase the risk of cognitive decline in the elderly. However, the randomized controlled study on the effect of HL on cognitive function in mild cognitive impairment (MCI) is very limited. Methods From 1 November 2020 to 30 March 2022, 1,987 individuals aged 55–65 years were randomly divided into the MCI with hearing impairment (MCI-HI), MCI without HI (MCI-nHI), and no MCI (nMCI) groups by stratified sampling, with 30 participants in each group. The Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the pure tone audiometry (PTA), and the auditory brainstem response (ABR) were measured at baseline and a follow-up 12 months later. The trial protocol was registered with ClinicalTrials.gov with the registration number NCT05336942. Results Among the 90 participants, the average age was 60.41 ± 6.48 years. In the MCI-HI group at baseline, the PTA score of both the ears was negatively correlated with the naming and memory score (p < 0.05), and the PTA score of both the ears was negatively correlated with the MoCA and abstraction score at the 12-month follow-up (p < 0.05). However, there were no significant differences among the PTA, the ABR, the MMSE, and the MoCA scores in the MCI-nHI and nMCI groups (p > 0.05). Regression analysis showed that the PTA score of the right ear at baseline was an important factor associated with the MoCA, visuospatial/executive, naming, and abstraction scores at the 12-month follow-up (β = −0.776 to −0.422, p < 0.05). Conclusion HL was significantly negatively associated with cognitive function only in patients with MCI with hearing impairment (HI), and the PTA of the right ear may be a predictor of cognitive decline after 1 year in patients with MCI with HI. This information may help primary healthcare clinicians to prevent MCI by screening and intervening in care for elderly patients with HL.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".