Critical Review of Hearing Rehabilitation in Pediatric Oncology: Specific Considerations and Barriers
Bibliographic record
Abstract
Childhood cancer treatments, including chemotherapy, radiation therapy, and combined modalities, pose significant risks to auditory function due to their ototoxic effects. Cisplatin, a chemotherapeutic agent commonly used in pediatric oncology, causes dose-dependent irreversible sensorineural hearing loss by damaging the inner ear structures, primarily through the generation of reactive oxygen species and the activation of apoptotic pathways. Radiation therapy exacerbates these effects, contributing to both sensorineural and conductive hearing loss via mechanisms such as vascular injury, inflammation, and fibrosis. The severity of hearing loss is influenced by the treatment timing, the cumulative dose, patient age, genetics, and concurrent therapies. The damaging effects of chemotherapy and radiation extend beyond the cochlea, involving the surrounding temporal bone as well as multiple levels of the auditory pathway. While pediatric patients may be candidates for bone-anchored hearing devices or cochlear implants, the need for serial imaging and the potential for implant-related MRI artifacts can complicate the timing of hearing rehabilitation. Moreover, the impact on the subcortical and cortical auditory structures may further influence the rehabilitation outcomes. This scoping review lays the foundation for future clinical and research efforts focused on the development of comprehensive pediatric guidelines for hearing preservation, monitoring, and rehabilitation, while also fostering multidisciplinary collaboration.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".