The ‘ring of fire’ phenomenon in chronic wounds: A new insight using fluorescence imaging
Bibliographic record
Abstract
Aim: To describe the ‘ring of fire’ phenomenon observed during fluorescence imaging of chronic wounds. Methods: The Fluorescence Imaging Assessment and Guidance (FLAAG) trial evaluated 350 patients with a variety of chronic wounds. During the FLAAG trial, the investigators observed a phenomenon when wounds were imaged using the MolecuLight i:X imaging device: bacteria fluorescence aggregated at the margin of the wound. This was most pronounced in diabetic foot ulcers. The term ‘ring of fire’ was coined to describe this clinical observation. Results: Six representative patients taken from the FLAAG trial are presented to demonstrate the ‘ring of fire’ in a variety of wound types. This included three diabetic foot ulcers, two venous leg ulcers and a surgical site infection following lumbar back surgery. Conclusion: This is the first clinical report of this phenomenon. It highlights the importance of focusing on the wound edge when managing nonhealing wounds.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".