Aloe vera for Prevention of Radiation-Induced Dermatitis: A Self-Controlled Clinical Trial
Bibliographic record
Abstract
To evaluate an Aloe vera lotion for prevention of radiation-induced dermatitis, all patients with a prescription of radiotherapy to a minimum dose of 40 Gy were eligible provided that their treatment area could be divided into two symmetrical halves. Patients were given a lotion of Aloe vera to use on one half of the irradiated area, with no medication to be used on the other half. The grade of dermatitis in each half was recorded weekly until 4 weeks after the end of radiotherapy. The trial enrolled 60 patients (mean age: 52 years; 67% women). Most patients had breast cancer (38%), followed by pelvic (32%), head-and-neck (22%), and other cancers (8%). Field size was 80-320 cm(2) (mean: 177 cm(2)), and the dose of radiotherapy was 40-70 Gy (mean: 54 Gy). Concurrent chemotherapy was administered in 20 patients. From week 4 to week 6 of radiotherapy and then at weeks 2 and 4 after radiotherapy, the mean grade of dermatitis with and without Aloe vera was 0.81 and 1.10 (p < 0.001), 0.96 and 1.28 (p < 0.001), 1.00 and 1.57 (p = 0.006), 0.59 and 0.79 (p = 0.003), and 0.05 and 0.21 (p = 0.002) respectively. Age and radiation field size had a significant effect on the grade of dermatitis. Based on these results, we conclude that the prophylactic use of Aloe vera reduces the intensity of radiationinduced dermatitis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".