Traditional dressings used for wound repair, such as gauze, have shortcomings; for example, they cannot provide a suitable microenvironment for wound recovery. Therefore, it is necessary to find a better dressing to overcome shortcomings. Hydrogel provides a suitable wet environment, has good biocompatibility, and has a strong swelling rate to absorb exudate. Nanomaterial in hydrogels has been used to improve their performance and overcome the shortcomings of current hydrogel dressings. Hydrogel dressing can also be loaded with nanodrug particles to exert a better therapeutic effect than conventional drugs and to make the dressing more practical. This article reviews the application of nanotechnology in hydrogels related to wound healing and discusses the application prospects of nanohydrogels. After searching for hydrogel articles related to wound healing, we found that nanomaterial can not only enhance the mechanical strength, antibacterial properties, and adhesion of hydrogels but also achieve sustained drug release. From the perspective of clinical application, these characteristics are significant for wound healing. The combination of nanomaterial and hydrogel is an ideal dressing with broad application prospects for wound healing in the future.

There is still a lack of relevant studies on surgical site infection (SSI) after emergency abdominal surgery (EAS) in China. This study aims to understand the incidence of SSI after EAS in China and discuss its risk factors. All adult patients who underwent EAS in 47 hospitals in China from May 1 to 31, 2018, and from May 1 to June 7, 2019, were enrolled in this study. The basic information, perioperative data, and microbial culture results of infected incision were prospectively collected. The primary outcome measure was the incidence of SSI after EAS, and the secondary outcome variables were postoperative length of stay, ICU admission rate, ICU length of stay, 30-day postoperative mortality, and hospitalization cost. Univariate and multivariate logistic regression were used to analyze the risk factors. The results were expressed as the odds ratio and 95% confidence interval. A total of 953 patients [age 48.8 (SD: 17.9), male 51.9%] with EAS were included in this study: 71 patients (7.5%) developed SSI after surgery. The main pathogen of SSI was Escherichia coli (culture positive rate 29.6%). Patients with SSI had significantly longer overall hospital (p < 0.001) and ICU stays (p < 0.001), significantly higher ICU admissions (p < 0.001), and medical costs (p < 0.001) than patients without SSI. Multivariate logistic regression analysis showed that male (P = 0.010), high blood glucose level (P < 0.001), colorectal surgery (P < 0.001), intestinal obstruction (P = 0.045) and surgical duration (P = 0.007) were risk factors for SSI, whereas laparoscopic surgery (P < 0.001) was a protective factor. This study found a high incidence of SSI after EAS in China. The occurrence of SSI prolongs the patient's hospital stay and increases the medical burden. The study also revealed predictors of SSI after EAS and provides a basis for the development of norms for the prevention of surgical site infection after emergency abdominal surgery.

Wound healing is a significant problem in clinical management. Various functional dressings are studied to promote wound healing through biochemical factors. They are generally expensive, complex to fabricate, and may adversely affect the wound. Mechanical forces are the critical regulators of tissue repair. Although contraction is shown to promote wound healing, the underlying mechanisms are not fully understood. In this study, a novel adhesive temperature‐sensitive mechanically active hydrogel with a simple and inexpensive preparation process is developed. The dressing is able to adhere to the wound surface and actively contract the wound in response to body temperature. This mechanical contraction enhances the proliferative activity of basal cells, reduces the inflammatory response of the wound, and promotes wound healing. Furthermore, RNA‐seq clarifies how the gene regulatory network is regulated by contraction. Finally, using pharmacological inhibitors, YAP and MEK are identified as the key signaling molecules for contraction‐mediated tissue healing in vivo.

Objective: This study aimed to construct and validate a clinical prediction model for surgical site infection (SSI) risk 30 days after gastrointestinal surgery. Materials and methods: This multicentre study involving 57 units conducted a 30-day postoperative follow-up of 17 353 patients who underwent gastrointestinal surgery at the unit from 1 March 2021 to 28 February 2022. The authors collected a series of hospitalisation data, including demographic data, preoperative preparation, intraoperative procedures and postoperative care. The main outcome variable was SSI, defined according to the Centres for Disease Control and Prevention guidelines. This study used the least absolute shrinkage and selection operator (LASSO) algorithm to screen predictive variables and construct a prediction model. The receiver operating characteristic curve, calibration and clinical decision curves were used to evaluate the prediction performance of the prediction model. Results: Overall, 17 353 patients were included in this study, and the incidence of SSI was 1.6%. The univariate analysis combined with LASSO analysis showed that 20 variables, namely, chronic liver disease, chronic kidney disease, steroid use, smoking history, C-reactive protein, blood urea nitrogen, creatinine, albumin, blood glucose, bowel preparation, surgical antibiotic prophylaxis, appendix surgery, colon surgery, approach, incision type, colostomy/ileostomy at the start of the surgery, colostomy/ileostomy at the end of the surgery, length of incision, surgical duration and blood loss were identified as predictors of SSI occurrence (P<0.05). The area under the curve values of the model in the train and test groups were 0.7778 and 0.7868, respectively. The calibration curve and Hosmer–Lemeshow test results demonstrated that the model-predicted and actual risks were in good agreement, and the model forecast accuracy was high. Conclusions: The risk assessment system constructed in this study has good differentiation, calibration and clinical benefits and can be used as a reference tool for predicting SSI risk in patients.