Application of an infrared thermography-based model to detect pressure injuries: a prospective cohort study

Outcome Evaluation of Reconstructive Septorhinoplasty in Patients with a History of Nasal Skin Necrosis

Background: Nasal skin necrosis represents a severe rhinoplasty complication, potentially leading to nasal deformity and psychological distress. Objectives: To assess the safety, nasal function enhancement, and esthetic satisfaction in individuals with a history of nasal skin necrosis following reconstructive septorhinoplasty using patient-reported outcome measures. Methods: The case series included patients who underwent reconstructive septorhinoplasty 1 year after experiencing skin necrosis. Skeletal reconstruction was performed with an open approach using various autografts and techniques. The data collected encompassed demographics, medical history, operative reports, and postoperative events. The Standardized Cosmesis and Health Nasal Outcomes Survey (SCHNOS) was administered preoperatively and 1 year postoperatively. Results: Most patients were female (35/38, 92%), with median age of 33.5 years (17-57) and 2 prior rhinoplasties (1-5) by 1 surgeon (1-2). The follow-up median was 23.78 months (11.83-54.23). Necrosis predominantly affected the nasal tip and soft tissue triangles. Septorhinoplasty utilized 11 V-shaped columellar base and 27 mid-columella incisions, lasting on average 274 min (175-405). Septal grafts were adequate for reconstruction in only three cases. Autografts for reconstruction encompassed auricular cartilage (31), rib cartilage (22), temporal fascia (14), and rectus fascia (6). SCHNOS scores improved significantly, with the obstruction domain decreasing from a preoperative mean of 75.92 (±22.83) to 34.08 (±27.87) and the cosmesis domain from 85.43 (±19.06) to 39.73 (±23.77). No postoperative severe vascular complication occurred. More previous surgeries linked to decreased patient satisfaction. Conclusion: Reconstructive septorhinoplasty can be successful in restoring relatively normal nasal contour following prior soft tissue necrosis, with limited risk for complications.

Apoptotic Bodies Derived from Fibroblast-Like Cells in Subcutaneous Connective Tissue Inhibit Ferroptosis in Ischaemic Flaps via the miR-339-5p/KEAP1/Nrf2 Axis

Preventing and treating avascular necrosis at the distal end of the flaps are critical to surgery success, but current treatments are not ideal. A recent study shows that apoptotic bodies (ABs) generated near the site of apoptosis can be taken up and promote cell proliferation. The study reveals that ABs derived from fibroblast-like cells in the subcutaneous connective tissue (FSCT cells) of skin flaps promoted ischaemic flap survival. It is also found that ABs inhibited cell death and oxidative stress and promoted M1-to-M2 polarization in macrophages. Transcriptome sequencing and protein level testing demonstrated that ABs promoted ischaemic flap survival in endothelial cells and macrophages by inhibiting ferroptosis via the KEAP1-Nrf2 axis. Furthermore, microRNA (miR) sequencing data and in vitro and in vivo experiments demonstrated that ABs inhibited KEAP1 by delivering miR-339-5p to exert therapeutic effects. In conclusion, FSCT cell-derived ABs inhibited ferroptosis, promoted the macrophage M1-to-M2 transition via the miR-339-5p/KEAP1/Nrf2 axis and promoted ischaemic flap survival. These results provide a potential therapeutic strategy to promote ischaemic flap survival by administering ABs.

A novel deep-learning based weighted feature fusion architecture for precise classification of pressure injury

Introduction: Precise classification has an important role in treatment of pressure injury (PI), while current machine-learning or deeplearning based methods of PI classification remain low accuracy. Methods: In this study, we developed a deeplearning based weighted feature fusion architecture for fine-grained classification, which combines a top-down and bottom-up pathway to fuse high-level semantic information and low-level detail representation. We validated it in our established database that consist of 1,519 images from multi-center clinical cohorts. ResNeXt was set as the backbone network. Results: We increased the accuracy of stage 3 PI from 60.3% to 76.2% by adding weighted feature pyramid network (wFPN). The accuracy for stage 1, 2, 4 PI were 0.870, 0.788, and 0.845 respectively. We found the overall accuracy, precision, recall, and F1-score of our network were 0.815, 0.808, 0.816, and 0.811 respectively. The area under the receiver operating characteristic curve was 0.940. Conclusions: Compared with current reported study, our network significantly increased the overall accuracy from 75% to 81.5% and showed great performance in predicting each stage. Upon further validation, our study will pave the path to the clinical application of our network in PI management.

Can technology change the status quo for pressure injury prevention?

Linked Article:  Jiang et al. Br J Dermatol 2022; 187:571–579.