Hearing Impairment in Oral Submucous Fibrosis: A Systematic Review
Bibliographic record
Abstract
Background: With serious oral and systemic implications, oral submucous fibrosis (OSMF) is a crippling disorder that is common in some areas, especially among areca nut chewers. A thorough investigation of the relationship between OSMF and hearing impairment is necessary due to the growing evidence that, despite its well-established effects on dental health, there may be a connection. Aim: To investigate the association between OSMF and hearing impairment, particularly the mechanisms behind Eustachian tube dysfunction (ETD) and auditory dysfunction in OSMF patients. Methodology: This systematic review aimed to assess the association between hearing impairment and OSMF using the PICOS framework. A comprehensive search of 1137 articles published between 2015 and 2024 across various databases was conducted, resulting in 18 studies meeting the inclusion criteria. Data on population demographics, audiological assessments, and outcomes were extracted independently by 3 reviewers. The quality of the included studies was evaluated using the Cochrane Risk of Bias Tool and the Newcastle–Ottawa Scale. Risk of bias assessments was conducted to categorize studies as low, moderate, or high risk. Results: The review identified 18 studies examining the link between OSMF and hearing impairment, revealing a significant correlation between OSMF severity and hearing loss. Patient-reported hearing issues ranged from 27.69% to 76.7%. Conductive hearing loss was prevalent, particularly in advanced OSMF stages. Most studies employed pure tone audiometry and tympanometry, highlighting ETD as a common contributor. Quality assessments indicated that most studies had good methodological rigor, with several rated as very good, underscoring the need for comprehensive evaluations in understanding the audiological implications of OSMF. Conclusion: There is a substantial association between OSMF and hearing loss, particularly through ETD. Multidisciplinary management and early audiological screening are essential for improving outcomes in OSMF patients.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".