Treatment of Chronic Nonhealing Leg Ulceration with Gaseous Nitric Oxide: A Case Study
Bibliographic record
Abstract
BACKGROUND: Despite the best clinical practice, chronic nonhealing ulcers of the lower extremities present a significant challenge. Nitric oxide (NO) has been shown to play a significant role in biological functions including wound healing and as an antimicrobial agent in nonspecific immune response. OBJECTIVE: Our goal was to study the effect of gaseous NO (gNO) administered directly to a two-year-old nonhealing chronic venous ulcer in a 55-year-old male presenting with a 30-year history of severe venous disease. METHODS: gNO (200 ppm) was applied to the lower extremity using a delivery system connected to a "single patient use" plastic boot, at 1.0 L/min. RESULTS: The patient received an average of 8.1-h treatments for 14 consecutive nights. On day 0 the wound was malodorous and covered by bacterial biofilm with little healthy granulation tissue present. Following 3 days of gNO treatment, healthy granulation tissue was noted with absence of malodorous odor. At day 14, the ulcer was significantly reduced in size (p = 0.014) and almost completely reepithelialized. Day 10 post-treatment did not reveal any deterioration in healing. Six weeks later, the wound was 90% healed. At 26 weeks post gNO discontinuation, the ulcer was completely healed. CONCLUSIONS: This single case study demonstrated that gNO as a topical agent was well tolerated by the patient without any report of discomfort or side effect. The result of wound healing was very promising and warrants future exploration.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".