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Eschar dermabrasion is an easy, cost-effective and dependable technique for debriding deep partial-thickness burn wounds, highly suitable for paediatric scalds. Postoperative dressing plays a crucial role in the subsequent healing process. While allogenic skin (AGS) has long been considered as the optimal coverage for abraded burn wounds by Chinese burn specialists, its clinical application on children has encountered challenges. In recent years, our department has observed promising results in the application of bacterial cellulose dressing on paediatric burn wounds after dermabrasion surgery. This study aimed to retrospectively review qualified cases from the past 5 years and categorize them into two groups: 201 cases in the AGS group and 116 cases in the bacterial cellulose dressing (BCD) group. Upon statistical analysis, no differences were oberved between the groups in terms of demographic information and wound characteristics. However, the BCD group had a significantly longer surgery time (44.3 ± 7.0 min vs. 31.5 ± 6.1 min, p < 0.01) and shorter healing time (19.6 ± 2.2 days vs. 24.4 ± 4.3 days, p < 0.01) compared to the AGS group. Moreover, the BCD group required fewer dressing changes (3.5 ± 0.8 vs. 6.7 ± 2.1, p < 0.01) and demonstrated lower rates of skin grafting (10/116 vs. 46/201, p = 0.036). In conclusion, our findings suggest that the bacterial cellulose material may serve as an optimal coverage option for paediatric abraded scald wounds.
The current methods for the prediction of mortality and amputation for inpatients with diabetic foot (DF) use only conventional, simple variables, which limits their performance. Here, we used a random survival forest (RSF) model and multicomponent variables to improve the prediction of mortality and amputation for these patients. We performed a retrospective cohort study of 175 inpatients with DF who were recruited between 2014 and 2021. Thirty-one predictors in six categories were considered as potential covariates. Seventy percent (n = 122) of the participants were randomly selected to constitute a training set, and 30% (n = 53) were assigned to a testing set. The RSF model was used to screen appropriate variables for their value as predictors of 2-year all-cause mortality and amputation, and a multicomponent prediction model was established. Model performance was evaluated using the area under the curve (AUC) and the Hosmer–Lemeshow test. The AUCs were compared using the Delong test. Seventeen variables were selected to predict mortality and 23 were selected to predict amputation. Uric acid and alanine transaminase were the top two most useful variables for the prediction of mortality, whereas urine protein and platelet were the top variables for the prediction of amputation. The AUCs were 0.913 and 0.851 for the prediction of mortality for the training and testing sets, respectively; and the equivalent AUCs were 0.963 and 0.893 for the prediction of amputation. There were no significant differences between the AUCs for the training and testing sets for both the mortality and amputation models. These models showed a good degree of fit. Thus, the RSF model can predict mortality and amputation in inpatients with DF. This multicomponent prediction model could help clinicians consider predictors of different dimensions to effectively prevent DF from clinical outcomes .
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