The Oxygen–Ozone Adjunct Medical Treatment According to the Protocols from the Italian Scientific Society of Oxygen–Ozone Therapy: How Ozone Applications in the Blood Can Influence Clinical Therapy Success via the Modulation of Cell Biology and Immunity
Bibliographic record
Abstract
Background. Ozone is an allotrope of oxygen whose use in medicine has rapidly grown in recent years. Ozonated blood allows for the use of ozone in a safe modality, as plasma and blood cells are endowed with an antioxidant system able to quench ozone’s pro-oxidant property and to elicit the Nrf2/Kwap1/ARE pathway. Methods. We present two clinical studies, a case-series (six patients) observational study adopting ozone as a major autohemotherapy and topical ozone to address infected post-surgical wounds with multi-drug resistant bacteria and an observational study (250 patients) using ozonated blood for treating knee osteoarthritis. Results. Ozonated blood via major autohemotherapy reduced the extent of infections in wounds, reduced the inflammatory biomarkers by more than 75% and improved patients’ QoL, whereas ozonated blood via minor autohemotherapy improved significantly (p < 0.001) WOMAC and Lequesne’s parameters in knee osteoarthritis. Conclusions. The models described, i.e., ozone autohemotherapy in wound antimicrobial treatment and ozonated blood in knee osteoarthrosis, following our protocols, share the outstanding ability of ozone to modulate the innate immune response and address bacterial clearance as well as inflammation and pain.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".