Noninvasive Measurement of Edema in Partial Thickness Burn Wounds
Bibliographic record
Abstract
A lack of noninvasive tools to quantify edema has limited our understanding of burn wound edema pathophysiology in a clinical setting. Near-infrared spectroscopy (NIR) is a new noninvasive tool able to measure water concentration/edema in tissue. The purpose of this study was to determine whether NIR could detect water concentration changes or edema formation in acute partial-thickness burn injuries. Adult burn patients within 72 hours postinjury, thermal etiology, partial-thickness burn depth, and <20% TBSA were included. Burn wounds were stratified into partial-thickness superficial or deep wounds based on histology and wound healing time. NIR devices were used to quantify edema in a burn and respective control sites. The sample population consisted of superficial (n = 12) and deep (n = 5) partial-thickness burn injuries. The patients did not differ with respect to age (40 +/- 15 years), TBSA (5 +/- 4%), and mean time for edema assessment (2 days). Water content increased 15% in burned tissue compared with the respective control regions. There were no differences in water content at the control sites. At 48 hours, deep partial-thickness injuries showed a 23% increase in water content compared with 18% superficial partial-thickness burns. NIR could detect differences in water content or edema formation in partial-thickness burns and unburned healthy regions. NIR holds promise as a noninvasive, portable clinical tool to quantify water content or edema in burn wounds.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".