Targeted Screening in Older Adults: Hearing Loss and Mild Cognitive Impaired
Bibliographic record
Abstract
Aim: To determine the prevalence of under-diagnosed neurocognitive degeneration and depression in older adults with subjective Hearing Loss (HL) and that of undiagnosed HL in patients with mild cognitive impairment in Hong Kong.Method: Patients aged above 60 with subjective HL and those who attended the NTEC ENT clinic from May 2021 to October 2022 were included.Pure tone audiogram was performed to assess the severity of HL.The Hong Kong Montreal Cognitive Assessment and Patient health questionnaire-9 was used to assess the severity of cognitive impairment and depression respectively.Hearing aid amplification was offered to patients with bilateral HL greater than 40dB.Psychogeriatric referral was given to patients with major cognitive impairment or major depression.Results: 225 older adults with subjective hearing loss and without known cognitive disorders were included in the general ENT clinic.62% had bilateral HL greater than 40dB requiring amplification.98 older adults with diagnosed mild cognitive impairment and without subjective hearing loss were included in the psychiatric out-patient clinic.Overall, significant and positive correlation between hearing loss and dementia as well as between dementia and depression was found.Over 75% of MCI patients were also found to have undetected hearing loss and nearly half requires hearing aid, making them a significantly high-risk group.Conclusion: Screening for dementia may be necessary for hearing loss patients.Patients diagnosed with MCI may also require regular hearing loss screening.This can allow for early diagnosis and management of both hearing loss and cognitive decline to prevent the formation of a vicious cycle.
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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".