Glutamine for prevention and alleviation of radiation‐induced oral mucositis in patients with head and neck squamous cell cancer: Systematic review and meta‐analysis of controlled trials
Bibliographic record
Abstract
We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) that investigated glutamine efficacy in preventing and alleviating radiation-induced oral mucositis (OM) among patients with head and neck (H&N) cancer. We screened five databases from inception till February 4, 2021 and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We included 11 RCTs, comprising 922 patients (458 and 464 patients were assigned to glutamine and control group, respectively). The incidence and onset of radiation-induced OM of any grade did not substantially differ between both groups. However, glutamine substantially reduced the severity of radiation-induced OM, as reflected by the reduced incidence of severe OM and reduced mean maximal OM grade score. Additionally, glutamine significantly decreased the rates of analgesic opioid use, nasogastric tube feeding, and therapy interruptions. Oral glutamine supplementation demonstrated various therapeutic benefits in preventing and ameliorating radiation-induced OM among patients with H&N cancer.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.020 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".