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Prediction of Age-Related Hearing Loss Based on Comprehensive Risk Factors

NCT07612618 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2026-05-29

No results posted yet for this study

Summary

This study aims to develop a predictive model for age-related hearing loss (ARHL) based on multi-source risk factors and artificial intelligence techniques. A retrospective analysis will be conducted on 1,000 cases with 15-year longitudinal clinical data, including audiological assessments and noise exposure history. Machine learning algorithms will be employed to construct a predictive model for hearing loss progression. Additionally, a prospective cohort of 100 community-dwelling elderly individuals will be enrolled. Blood samples will be collected for low-abundance targeted proteomics analysis to screen for biomarkers associated with cognitive impairment. This study will establish an early risk identification tool for ARHL and propose strategies for the screening and prevention of dementia in individuals with hearing impairment, thereby providing evidence-based support for early intervention in auditory and cognitive health in the elderly.

Conditions

  • Age-related Hearing Loss

Interventions

OTHER

Not applicable- observational study

Not applicable-observational study

Sponsors & Collaborators

  • Chinese PLA General Hospital

    lead OTHER

Eligibility

Min Age
60 Years
Max Age
100 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2026-06-01
Primary Completion
2027-12-31
Completion
2027-12-31

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07612618 on ClinicalTrials.gov