Abusive routes of application in ozone therapy, a critical review
Bibliographic record
Abstract
Ozone used within the determined therapeutic windows is absolutely safe and more effective than golden standard medications in numerous pathologies. However, there are practitioners who for the interest of increasing cost effectiveness and increasing speed in treatments, pretend to cure chronic diseases applying alternative administration ways, using high ozone doses, which are neither standardized, nor supported by pre-clinical / clinical data, nor evaluated toxicologically. In this review an analysis of the bibliographical data concerning efficacy and safety of this methods was analyzed. The search included a review of scientific articles and experimental results papers in the MEDLINE and Zotero ISCO3 Ozone Database, between the years 1980-2018. Descriptors: ozone therapy, toxicology, side effects were used. The primary (original articles) sources of information were located. The most representative emerging therapies: direct intra venous application (DIV), Robins method of direct intravenous ozone therapy℠ (RMDIV ℠), Hyperbaric (HBO3) multi passes method, high dose ozone therapy (HDO), and Intraperitoneal Ozone (IPO3) are lack of clinical evidences and represent a serious risk for the human health. A rational clinical protocol fits to the good clinical practice and supported by and ethic committee is needed to prof it efficacy prior to be introduced in clinical practice. The emergent are not recommend for its clinical application (except patients enrolled in a clinical trial) until new scientific evidence of the benefit/risk ratio is provided
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".