Complementary and Alternative Medicines (CAM) in the Management of Asthma: An Examination of the Evidence
Bibliographic record
Abstract
Although individuals are using Complementary and Alternative Medical (CAM) therapies to help manage their asthma, there is no clear direction in the current guidelines for the use of CAM in asthma. This literature review undertakes to determine the current science regarding the use of CAM in asthma management. Electronic literature searched all EBM Reviews, Medline, OVID full text, and PubMed and National Complementary and Alternative Medication databases for Randomised Controlled Trials (RCT) published in English between 1997 and 2002 with keywords "asthma" and "complementary medicine" or "complementary therapy" or "alternative medicine" or "alternative therapy." Abstracts (N=197) were reviewed for inclusion in the review and duplicates discarded (N=65). Abstracts of non-RCT studies, review articles, and surveys were also discarded (N=66). Abstracts discussing environmental control measures and pharmaceutical alternatives to steroid therapy were discarded (N=9). The 15 final studies were grouped within three categories: mind-body and relaxation, manual therapies, and diet and reviewed for statistical and clinical significance, suggesting some CAM therapies have shown minimally significant improvements in asthma quality of life (breathing exercises) or pulmonary function (relaxation) and immune function (relaxation and acupuncture) in select asthma populations. Although CAM therapy is being used in the management of asthma, these 15 studies show a tendency to little or no significant difference between placebo or sham therapy. This may be due, in part, to the enhanced placebo effect of sham therapies used as control and the small size of most studies. Although the changes in the immune function seen in two studies are provocative, these changes did not translate to changes in lung function. More research is needed to assist in determining the efficacy of CAM therapies in asthma management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 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".