Handheld fluorescence imaging device detects subclinical wound infection in an asymptomatic patient with chronic diabetic foot ulcer: a case report
Bibliographic record
Abstract
Chronic wounds are a significant burden to global patient and health care infrastructures, and there is a need for better methods of early wound diagnosis and treatment. Traditional diagnosis of chronic wound infection by pathogenic bacteria, using clinical signs and symptoms, is based on visual inspection under white light and microbiological sampling (e.g. swabbing and/or biopsy) of the wound, which are subjective and suboptimal. Diagnosing microbial infection based on traditional clinical signs and symptoms in wounds of asymptomatic patients is especially challenging at the bedside. Bacteria are invisible to the unaided eye and wound sampling for diagnostic testing can cause unacceptable delays in diagnosis and treatment. To address this problem, we developed a new prototype handheld, portable fluorescence imaging device that enables non-contact, real-time, high-resolution visualisation of pathogenic bacteria and tissues in wounds. Herein, we report the clinical use of this imaging device in detecting subsurface heavy bacterial load and subclinical local infection in an asymptomatic 50-year-old patient with a non-healing diabetic foot ulcer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".