Long-term hearing loss assessment and PEACH scores of children exposed to platinum chemotherapy
Bibliographic record
Abstract
AbstractIntroduction: Platinum drugs (cisplatin and carboplatin) used in chemotherapy is responsible for permanent hearing loss with higher incidence rates in pediatric populations. This ototoxicity can be immediate and/or progressive. To date, there are no implemented treatments to prevent this issue resulting in a lower quality of life of cancer survivors. Objectives: To determine the length of time for platinum-induced ototoxicity to occur and assess the ability of using Evaluation of Aural/Oral Performance of Children (PEACH) questionnaire to identify this type of hearing loss. Methods: A cohort of 98 children treated with cisplatin and/or carboplatin from the CHU Sainte-Justine and the Montreal Children’s Hospital. Hearing was assessed audiograms using the ASHA criteria and the Chang grading system at the following time points: pre-treatment, end of treatment, first follow-up (3-9 months), second follow-up (15-24 months), third follow-up (24-60 months), fourth follow-up (60-96 months) and final follow-up (96 or more months) following platinum-based chemotherapy. The parents of 56 children in this cohort completed the PEACH questionnaire either before or after platinum treatment.Results: 58% of children demonstrated hearing loss following treatment and in 14% of these cases, hearing loss progressed up to 2 years following treatment. Out of the participants who completed the PEACH questionnaires, individuals with hearing loss demonstrated lower survey scores and the more significant the hearing loss, the worse the lower PEACH scores. Conclusion: Due to the presence of progressive nature of hearing loss, it is important for medical professionals to follow pediatric cancer and identify the presence of progressive hearing loss. Implementing the PEACH questionnaire in the follow-up of patients undergoing platinum treatments may facilitate this inquiry.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".