研究目的
To determine if temperature differences in burns assessed by infrared thermography could be used predict the treatment modality of either healing by re-epithelization, requiring skin grafts, or requiring amputations, and to validate the clinical predication algorithm in an independent cohort.
研究成果
Digital infrared thermography can be used as an independent predictor of burn wound healing clinical outcomes such as healing by re-epithelization, requiring a skin graft, or the need of amputation. The prediction algorithm based on the difference of temperature between the injured and healthy tissue offers a simple and accurate data acquisition protocol in the first days of treatment, which can easily be incorporated into current wound management protocols to rationalize treatment.
研究不足
1. The study only included patients with burns in extremities, so results cannot be extrapolated to other body areas.
2. The algorithm was trained to make the same treatment decisions as the burn surgeons at the study center, which may limit generalizability.
3. The study did not record burn conversion or dynamic changes in ΔT values, which could provide further insights.
4. ΔT was measured as an average, but wounds may have areas with different temperature values.
1：Experimental Design and Method Selection:
The study was a prospective observational study approved by the Ethics Committee. Infrared thermography was used to assess burn depth by measuring the temperature difference (ΔT) between injured and healthy skin within the first three days after injury. A prediction algorithm was developed using a recursive partitioning Random Forest machine learning algorithm.
2：Sample Selection and Data Sources:
Patients with partial or full thickness burns in extremities covering >25 cm2 of the total body surface, admitted within 24 hours from injury, were included. Exclusion criteria included previous comorbidities, BMI <19.9 for adults or below the 5th percentile for children, foreign bodies in the tissue, gross edema, systemic causes of distal hypoperfusion, or local infection.
3：9 for adults or below the 5th percentile for children, foreign bodies in the tissue, gross edema, systemic causes of distal hypoperfusion, or local infection.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials:
- FLIR T400 infrared camera (FLIR System, Wilsonville, OR, 2013) with a 320 x 240 focal plane array of uncooled microbolometers, spectral range of 7.5 to 13 μm, and thermal sensitivity of 50 mK at 30?C.
4：5 to 13 μm, and thermal sensitivity of 50 mK at 30?C.
- FLIR Tools Quick-Report v.2 software (FLIR Systems, version 70, 2016) for thermographic analysis.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow:
Infrared thermography was performed at the bedside following the TISEM checklist and Glamorgan protocol. Images were acquired at a distance of 0.5 or 1.5 m, at an angle of 90? relative to the body, under controlled conditions. The skin emissivity was set at 0.98. Thermographic analysis was performed by an investigator blinded to the clinical characteristics of the wound.
5：5 or 5 m, at an angle of 90? relative to the body, under controlled conditions. The skin emissivity was set at Thermographic analysis was performed by an investigator blinded to the clinical characteristics of the wound.
Data Analysis Methods:
5. Data Analysis Methods:
Statistical analysis was performed using R v.3.3.2 and RStudio. ANOVA and linear regression were used to compare ΔT and identify confounding factors. Multiple linear regression models adjusted for significant confounding factors. ROC curves, Random Forest algorithms, and k-means clustering were used for predictive modeling. Weighted kappa analysis tested agreement between predicted and actual treatment.
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