School of Health Sciences, University of Nottingham, Nottingham, UK
Infection Prevention and Control, Guy's and St Thomas' NHS Foundation Trust, London, UK.
BMJ Open. 2024 Sep 17;14(9):e086486. doi: 10.1136/bmjopen-2024-086486.
Digital surgical wound monitoring for patients at home is becoming an increasingly common method of wound follow-up. This regular monitoring improves patient outcomes by detecting wound complications early and enabling treatment to start before complications worsen. However, reviewing the digital data creates a new and additional workload for staff. The aim of this study is to assess a surgical wound monitoring platform that uses artificial intelligence to assist clinicians to review patients' wound images by prioritising concerning images for urgent review. This will manage staff time more effectively.
This is a feasibility study for a new artificial intelligence module with 120 cardiac surgery patients at two centres serving a range of patient ethnicities and urban, rural and coastal locations. Each patient will be randomly allocated using a 1:1 ratio with mixed block sizes to receive the platform with the new detection and prioritising module (for up to 30 days after surgery) plus standard postoperative wound care or standard postoperative wound care only. Assessment is through surveys, interviews, phone calls and platform review at 30 days and through medical notes review and patient phone calls at 60 days. Outcomes will assess safety, acceptability, feasibility and health economic endpoints. The decision to proceed to a definitive trial will be based on prespecified progression criteria.
Permission to conduct the study was granted by the North of Scotland Research Ethics Committee 1 (24/NS0005) and the MHRA (CI/2024/0004/GB). The results of this Wound Imaging Software Digital platfOrM (WISDOM) study will be reported in peer-reviewed open-access journals and shared with participants and stakeholders.
ISRCTN16900119 and NCT06475703.
患者居家的数字化手术伤口监测正成为一种越来越常见的伤口随访方法。这种定期监测通过早期发现伤口并发症并在并发症恶化之前开始治疗，从而改善患者的治疗效果。然而，审查数字数据会给工作人员带来新的、额外的工作量。本研究旨在评估一种使用人工智能辅助临床医生审查患者伤口图像的手术伤口监测平台，通过优先审查有问题的图像来管理工作人员的时间，从而更有效地处理伤口。
这是一项针对具有新人工智能模块的可行性研究，纳入了来自两个中心的 120 名心脏手术患者，涵盖了各种患者种族以及城市、农村和沿海地区。每个患者将使用混合大小的 1:1 随机分配，接受带有新检测和优先级模块的平台（最长 30 天术后）加标准术后伤口护理或仅标准术后伤口护理。评估通过 30 天的问卷调查、访谈、电话和平台审查以及 60 天的医疗记录审查和患者电话进行。结果将评估安全性、可接受性、可行性和健康经济学终点。是否进行确定性试验的决定将基于预设的进展标准。
北苏格兰研究伦理委员会 1（24/NS0005）和 MHRA（CI/2024/0004/GB）已批准进行该研究。Wound Imaging Software Digital platfOrM（WISDOM）研究的结果将在同行评议的开放获取期刊上报告，并与参与者和利益相关者共享。
ISRCTN83434122 和 NCT06475703。
