Meta-analysis of the efficacy of amifostine in the prevention of cisplatin ototoxicity.
Bibliographic record
Abstract
OBJECTIVE: The effectiveness of amifostine in the prevention of cisplatin ototoxicity remains controversial. The objective of this meta-analysis was to determine whether amifostine is successful in preventing ototoxicity secondary to cisplatin chemotherapy. DESIGN: Meta-analysis. METHODS: We conducted a systematic review of all randomized, controlled trials using amifostine in patients of all ages receiving cisplatin chemotherapy. Data extraction was performed by two independent reviewers using predefined data fields, including study quality indicators. Heterogeneity was evaluated using the I2 test. The meta-analysis was performed using the random effect method. MAIN OUTCOME MEASURE: Ototoxicity. RESULTS: Four randomized, controlled trials were included in this meta-analysis. The odds ratio of grade 2 or greater ototoxicity was 0.54 (95% CI 0.27-1.11), and the odds ratio of grade 3 ototoxicity or greater was 0.78 (95% CI 0.29-2.10). The side effects from amifostine use included hypocalcemia, hypotension, vomiting, and sneezing. CONCLUSIONS: This meta-analysis reveals a trend toward decreased ototoxicity in patients receiving amifostine infusion prior to receiving cisplatin chemotherapy. However, the results did not reach statistical significance. Further large randomized, controlled trials of amifostine use to prevent cisplatin-induced ototoxicity are needed.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.033 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".