Retrospective study of factors affecting non-healing of wounds during hyperbaric oxygen therapy
Bibliographic record
Abstract
OBJECTIVE: To identify potential factors, including cigarette smoking and diabetes status, that affect wound-healing outcomes during a six-week course of hyperbaric oxygen therapy (HBOT). METHOD: Seventy-three patients with 85 non-healing lower extremity wounds were treated with hyperbaric oxygen therapy (100% oxygen, 2.4 atmosphere absolute, (ATA), for 90 minutes). The wound area was evaluated over the six-week treatment period. RESULTS: A non-hierarchical clustering analysis of normalised wound-area data revealed that healing responses could be segregated into three groups: robust healing (n=31, over 50% reduction in area), minimal healing (n=33, 15% reduction) and non-healing (n=21,60% increase in area). Further analysis revealed that cigarette smoking was associated with poor response (p<0.0001), whereas diabetes was not. Robust responders had higher blood levels of creatinine and urea nitrogen, increased peripheral oxygenation (TcpO2), and were younger than less responsive patients. CONCLUSION: The results suggest that response to HBOT is variable and some patients do not benefit from it. Clinicians should evaluate available laboratory values, age and social history to determine if a patient is likely to benefit from HBOT.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".