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Dry skin and pressure injuries in older persons have become global health care problems. This was a multicentre, prospective cross‐sectional study in 44 hospitals and 8 long term care institutions from 20 provinces, autonomous regions and municipalities in China and aimed to explore the relationship between the two skin problems in older patients. We mainly found 11 602 cases with dry skin and 1076 cases with pressure injuries in a total of 33 769 valid participants. The overall prevalence of dry skin and pressure injuries was 34.4% (95% confidence interval [CI] 33.9–34.9) and 3.1% (95% CI 2.9–3.3). Stage 2+ pressure injuries were the most (32.9%), followed by stage 1 (32.4%). The patients with dry skin had more pressure injuries than ones without dry skin (50.0% vs 33.9%). The patients with very severe and severe dry skin had more pressure injury risk (OR 2.22 and 1.90) and more stage 2+ pressure injury risk (OR 2.83 and 1.63). Other nine predictors associated with overall pressure injuries and stage 2+ pressure injuries. The area under receiver operating characteristic (ROC) curve of the predictive models of overall pressure injuries and stage 2+ pressure injuries were 0.89 (95% CI 0.88–0.90) and 0.91 (95% CI 0.90–0.92), respectively. [ABSTRACT FROM AUTHOR]

Background: Silica gel fiber (SGF) dressing is a novel patch for wound healing., Objective: To compare the efficacy and safety of SGF dressing with alginate dressing in local treatment of venous leg ulcers., Methods: Patients with venous leg ulcers who had undergone effective treatment of venous hypertension and debridement were randomized to receive wound care with either SGF dressing or alginate dressing for 4 weeks. Wounds were assessed weekly during the first 4 weeks and then every 2 weeks until the 8th week. The primary endpoint was the efficacy rate. Secondary endpoints included ulcer area reduction rate, healing rate, frequency of dressing changes, pain score, patient satisfaction, and treatment-related adverse events., Results: A total of 130 patients were enrolled, 67 treated with SGF and 63 with alginate dressing, and the efficacy rates were 89.6% (SGF group) and 84.1% (alginate group). SGF induced a higher "no pain" rate than alginate at week 2 (61.4% vs 43.5%) and week 3 (67.6% vs 53.1%), and a higher "highly satisfied" rate at week 4 (83.3% vs 78.8%) and week 8 (75% vs 59.1%). Markedly fewer dressing changes were required in the SGF group., Conclusions: SGF dressing is non-inferior to alginate dressing in treating venous leg ulcers. It even substantially decreased the frequency of dressing changes when compared with alginate dressing.

Objectives: Diabetes foot ulcers (DFUs) are characterized by immune infiltration of M1 macrophages observed in foot skin, in which immune-associated genes (IRGs) play a prominent role. The precise expression of IRGs as well as any possible regulatory mechanisms that could be present in DFUs is yet unknown. Methods: The sequencing data of single-cell RNA (scRNA) in the foot skin of patients with DFUs were analyzed, screening out the cluster marker genes of foot skin obtained from the ImmPort database. IRG activity was assessed with the AUCell software package. The IRGs of DFUs were explored by analyzing the batch sequencing dataset of DFU skin tissue. HumanTFDB was adopted to identify relevant regulatory transcription factors (TFs). The STRING dataset was used to build the main TF protein-protein interaction networks. WB and immunofluorescence methods were used to verify M1 macrophage-related immune regulators. Results: There were 16 clusters found: SMC1, fibro, t-lympho, he fibro, vasendo, baselkera, diffkera, SMC2, M1 macro, M2 macro, sweet/seba, B-Lympho, Melanio, lymphendo, plasma, and Schwann. M1 and M2 macrophages both had considerably higher AUC ratings than patients with DFUs compared to other sub-populations of cells. The proportion of M1 macrophages was the highest in the non-healing group. According to scRNA analysis and batch sequencing data by GO and KEGG, DEGs were enriched in immune response. Some 106 M1 macro-IRGs were finally identified and 25 transcription factors were revealed as associated with IRG expression. The PPI network indicated NFE2L2, REL, ETV6, MAF, and NF1B as central transcription factors. Conclusion: Based on the bio-informatics analysis of scRNA and high-throughput sequencing data, we concluded that M1 macrophages may serve as the influencing factor of DFUs' non-union. In addition, NFE2L2 could be involved in the regulation of IRG expression within M1 macrophages., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Li, Ju, Li, Zhou, Wang, Cai and Dong.)

Background: Diabetes foot ulcers (DFUs) are a type of foot infection, ulcer, and/or deep tissue destruction caused by neuropathy and vascular disease in the distal extremities of diabetic patients. Its pathogenesis and its microenvironment are not entirely understood., Methods: Initially, the GSE165816 data set from the GEO database was utilized for single cell analysis to reveal the microenvironment and functional status of DFUs. The GSE199939 RNA-seq data set was utilized for external validation. On the basis of the logistic regression machine learning algorithm (OCLR), pseudo time series analysis, dryness index analysis, and drug target gene analysis were then performed. By constructing drug-gene and gene-gene networks, we can locate the most recent DFUs treatments. Finally, immunofluorescence technology was used to detect the cell-related markers of the DFUs microenvironment, and qPCR was used to detect the expression of drug targets in DFUs., Results: Firstly, we used the Cell Maker database to obtain information about human cells and related gene markers, and manually reviewed a total of 45 kinds of cells and maker information that may appear in the DFUs microenvironment, which were divided into 17 cell clusters after annotation. Subsequently, we counted the proportions of DM and DFUs in different types of cells, and the results showed that the proportions of macrophages, white blood cells, and monocytes were higher in patients with DFUs, while the proportions of pluripotent stem cells and stromal cells were higher in patients with DM. The Pseudo-time series analysis of cells in DFUs showed that the differentiation pathways of immune cells, mesenchymal cells and stem cells were similar in the three states, while the other cells were distributed in different stages. At the level of a single cell, the scores of both multipotential stem cells and hematopoietic stem cells were significantly lower in DFU healing and non-healing than in DM. Additionally, the highly expressed genes in DFU were chosen as drug targets. We identified seven potential target genes and discovered twenty drugs with high significance. Finally, the colocalization relationship between CD19, ITGAM, and HLA-DR expression in monocytes and macrophages of DFU skin tissue and healthy subjects was analyzed by laser confocal microscopy with the immunofluorescence triple labeling method. The results showed that the expressions of CD19, ITGAM, and HLA-DR in the skin of DFUs were significantly higher than those in the skin of healthy subjects, and the co-localization relationship was significant in DFUs., Conclusion: This study can serve as a resource for the treatment of DFUs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Ju, Li, Li, Zhou, Wang, Cai and Dong.)

Objective: To explore the clinical characteristics, risk factors and factors affecting the severity of the disease in patients with diabetic foot at the current stage through a multi-center cross-sectional survey.
 Methods: Clinical data of 326 patients with diabetic foot (205 males and 121 females) from 13 general hospitals nationwide were collected from October to November 2017 using a unified clinical data collection table. The clinical characteristics were analyzed, and the influential factors for severe diabetic foot were analyzed by logistic regression analysis.
 Results: Among 326 patients with diabetic foot, 68.4% of the patients were more than 60 years old, and 60.1% of the patients received primary or junior high school education; 96.3% of the patients developed Type 2 diabetes; 80.1% of patients had glycated hemoglobin (HbA1c)≥7%; 60.1% of patients suffered dyslipidemia. Improper wearing of footwear (38.5%) is the main cause of diabetic foot. Diabetic neuropathy (76.7%), diabetic retinopathy (62.3%) and lower limb vascular disease (57.4%) were the most common complications. Logistic regression analysis showed that diabetic nephropathy, diabetic lower extremity vascular disease, and HbA1c levels were independent risk factors for severe diabetic foot, and receiving foot care education can be regarded as a protective factor.
 Conclusion: The diabetic foot occurs mostly in male patients, and Type 2 diabetes with older age, lower education level, poor glycemic control and dyslipidemia are the risk factors. Diabetic nephropathy, diabetic lower extremity vascular disease, HbA1c, and receiving foot care education are independent influential factors for the severity of diabetic foot.

The study aims to develop and assess and validate a brief diabetic foot ulceration risk checklist among diabetic patients through a longitudinal study. Patients who had diabetes mellitus and had no foot ulceration and severe systematic disorders were recruited from eleven tertiary hospitals in nine provinces or municipalities of China. Internal consistency reliability, construct validity, concurrent validity, item property, and measurement invariance of the tool were assessed. The predictive capability of the tool was validated by the follow-up data using the receiver operating characteristic curve. At baseline, 477 valid cases were collected. Twelve items were remained after initial selection. Cronbach's alpha was 0.56. Confirmatory factor analysis showed that the model had acceptable goodness-of-fit yet local dependency between two items. Item response theory showed that most items had acceptable discrimination and difficulty parameters. Differential item functioning showed that tool had measurement invariance. 278 were followed up one year after the baseline. Follow-up showed that one-year incidence of ulceration among the patients was 3.6%, and the area under the receiver operating characteristic curve was 0.77 (95% confidence interval: 0.61-0.93). The cut-off point of the tool was 4, when sensitivity and specificity were 0.62 and 0.75 respectively. The checklist has good psychometric properties according to mixed evidences from classical and modern test theory, and has good predictive capability.