Is type 2 diabetes mellitus associated with alterations in hearing? A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: The aim of this study was to systematically and quantitatively review the available evidence on the effects of type 2 diabetes mellitus on hearing function. DATA SOURCES AND REVIEW METHODS: Eligible studies were identified through searches of eight different electronic databases and manual searching of references. Articles obtained were independently reviewed by two authors using predefined inclusion criteria to identify eligible studies. Meta-analysis was performed on pooled data using Cochrane's Review Manager. RESULTS: Eighteen articles fulfilled the inclusion criteria. Hearing loss (HL) was defined by all studies as pure tone average greater than 25 dB in the worse ear. The incidence of HL ranged between 44% and 69.7% for type 2 diabetics, significantly higher than in controls (OR 1.91; 95% confidence interval 1.47-2.49). The mean PTA (pure tone audiometry) thresholds were greater in diabetics than in controls for all frequencies [test or overall effect Z = 3.68, P = 0.0002]. Auditory brainstem response (ABR) wave V latencies were also statistically significantly longer in diabetics when compared to control groups [OR 3.09, 95% CI 1.82- 4.37, P < 0.00001]. CONCLUSIONS: Type 2 diabetic patients had significantly higher incidence for at least the mild degree of HL when compared with controls. Mean PTA thresholds were greater in diabetics for all frequencies but were more clinically relevant at 6000 and 8000 Hz. Prolonged ABR wave V latencies in the diabetic group suggest retro-cochlear involvement. Age and duration of DM play important roles in the occurrence of DM-related 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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.025 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".