A Feasibility Pilot Trial of Individualized Homeopathic Treatment of Fatigue in Children Receiving Chemotherapy
Bibliographic record
Abstract
BACKGROUND: Fatigue is a major problem in children with cancer. The objective was to examine the feasibility of performing a clinical trial of homeopathic treatment for fatigue in children receiving chemotherapy. MATERIALS: This was a single-institution, open-label, pilot study. Children 2 to 18 years old, diagnosed with cancer, and receiving chemotherapy were eligible. Participants were given individualized homeopathic treatment for a maximum of 14 days. In-home or clinic assessments were conducted up to 3 times weekly. Feasibility was defined as the ability to recruit and administer homeopathy to 10 participants within 1 year. Fatigue was measured using the Symptom Distress Scale daily and the PedsQL Multidimensional Fatigue Module weekly. RESULTS: Between April 2012 and April 2014, 155 potential participants were identified. There were 45 eligible and contacted patients; 36 declined participation, 30 because they were not interested; 9 agreed to participate, but 1 participant withdrew prior to treatment initiation. Median length of homeopathic treatment was 10.5 (range = 6 to 14) days. All parents found homeopathic treatment to be easy or very easy to follow. CONCLUSIONS: Trials of individualized homeopathy for fatigue reduction in pediatric cancer are not feasible in this context; lack of interest was a primary reason. Alternative approaches to evaluating homeopathy efficacy 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".