Hearing loss impacts gray and white matter across the lifespan: Systematic review, meta-analysis and meta-regression
Bibliographic record
Abstract
Hearing loss is a heterogeneous disorder thought to affect brain reorganization across the lifespan. Here, structural alterations of the brain due to hearing loss are assessed by using unique effect size metrics based on Cohen's d and Hedges' g. These metrics are used to map coordinates of gray matter (GM) and white matter (WM) alterations from bilateral congenital and acquired hearing loss populations. A systematic review and meta-analysis revealed m = 72 studies with structural alterations measured with magnetic resonance imaging (MRI) (bilateral = 64, unilateral = 8). The bilateral studies categorized hearing loss into congenital and acquired cases (n = 7,445) and control cases (n = 2,924), containing 66,545 datapoint metrics. Hearing loss was found to affect GM and underlying WM in nearly every region of the brain. In congenital hearing loss, GM decreased most in the frontal lobe. Similarly, acquired hearing loss had a decrease in frontal lobe GM, albeit the insula was most decreased. In congenital, WM underlying the frontal lobe GM was most decreased. In congenital, the right hemisphere was more negatively impacted than the left hemisphere; however, in acquired, this was the opposite. The WM alterations most frequently underlined GM alterations in congenital hearing loss, while acquired hearing loss studies did not frequently assess the WM metric. Future studies should use the endophenotype of hearing loss as a prognostic template for discerning clinical outcomes.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.025 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".