Augmented Decision-Making in wound Care: Evaluating the clinical utility of a Deep-Learning model for pressure injury staging.

BACKGROUND: Precise categorization of pressure injury (PI) stages is critical in determining the appropriate treatment for wound care. However, the expertise necessary for PI staging is frequently unavailable in residential care settings. OBJECTIVE: This study aimed to develop a convolutional neural network (CNN) model for classifying PIs and investigate whether its implementation can allow physicians to make better decisions for PI staging. METHODS: Using 3,098 clinical images (2,614 and 484 from internal and external datasets, respectively), a CNN was trained and validated to classify PIs and other related dermatoses. A two-part survey was conducted with 24 dermatology residents, ward nurses, and medical students to determine whether the implementation of the CNN improved initial PI classification decisions. RESULTS: The top-1 accuracy of the model was 0.793 (95% confidence interval [CI], 0.778-0.808) and 0.717 (95% CI, 0.676-0.758) over the internal and external testing sets, respectively. The accuracy of PI staging among participants was 0.501 (95% CI, 0.487-0.515) in Part I, improving by 17.1% to 0.672 (95% CI, 0.660-0.684) in Part II. Furthermore, the concordance between participants increased significantly with the use of the CNN model, with Fleiss' κ of 0.414 (95% CI, 0.410-0.417) and 0.641 (95% CI, 0.638-0.644) in Parts I and II, respectively. CONCLUSIONS: The proposed CNN model can help classify PIs and relevant dermatoses. In addition, augmented decision-making can improve consultation accuracy while ensuring concordance between the clinical decisions made by a diverse group of health professionals.

Protection of superoxide-induced cholesterol oxidation by antioxidants in protic conditions.

It was found in previous experiments that superoxide in the presence of added hydrogen peroxide in protic conditions produces oxysterols. The oxysterols formed under these conditions were 7beta-ketocholesterol, 7alpha-hydroxycholesterol and 7beta-hydroxycholesterol. In the present experiments, the inhibitory effects of three antioxidants, alpha-tocopherol (alpha-T), butylated hydroxyanisole (BHA) and butylated hydroxytoluene (BHT), on the oxidation of cholesterol in the presence of superoxide anion, water and hydrogen peroxide were investigated. It was found that BHA had the highest antioxidant activity on cholesterol oxidation, followed by alpha-T and BHT. The presence of antioxidants markedly retarded the formation of 7-ketocholesterol. The formation of 7beta-hydroxycholesterol or 7alpha-hydroxycholesterol was also reduced, but to a lesser degree.