Vaccination for prevention of hearing loss: a scoping review
Bibliographic record
Abstract
BACKGROUND: Infectious diseases in childhood and adolescence are significant and often preventable causes of hearing loss, especially in low- and middle-income countries. We conducted a scoping review to examine the extent, range and nature of available evidence on the role of vaccination for prevention of hearing loss worldwide. METHODS: We reviewed the published scientific literature to identify studies providing quantitative information on the relationship between vaccination and hearing loss. We searched four databases: MEDLINE, EMBASE, Cochrane Library and Global Index Medicus. No date, language, or geographical restrictions were imposed. Two independent reviewers assessed eligibility and charted data. RESULTS: Here we show that vaccination may be a key, underexploited strategy for primary prevention of child and adolescent hearing loss. Although the important contributions of rubella and meningitis vaccinations to hearing loss prevention are widely recognised, we identify 26 distinct known or potential infectious causes of hearing loss that are preventable or possibly preventable through vaccination. Notwithstanding, we find a dearth of empirical evidence on the impacts of vaccination on hearing loss prevention. In addition, the review identifies no research from low- and middle-income countries, which bear the overwhelming burden of child and adolescent hearing loss. Finally, it shows that numerous vaccines that address priority infectious diseases relevant to hearing loss are in development and could be brought into use. CONCLUSIONS: We recommend strategic investment in research concerning vaccination as a strategy for primary prevention of child and adolescent hearing loss.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".