Clinical prediction models and risk tools for early detection of patients at risk of surgical site infection and surgical wound dehiscence: a scoping review

医学 裂开 伤口裂开 手术伤口 重症监护医学 手术部位感染 风险评估 伤口感染 感染风险 外科 普通外科 计算机安全 计算机科学
作者
Kylie Sandy‐Hodgetts,Ojan Assadian,Thomas W. Wainwright,Melissa Rochon,Zhavandre Van der Merwe,Rhidian Jones,Thomas E. Serena,Paulo Alves,George Smith
出处
期刊:Journal of Wound Care [Mark Allen Group]
卷期号:32 (Sup8a): S4-S12 被引量:6
标识
DOI:10.12968/jowc.2023.32.sup8a.s4
摘要

Despite advances in surgical techniques, intraoperative practice and a plethora of advanced wound therapies, surgical wound complications (SWCs), such as surgical site infection (SSI) and surgical wound dehiscence (SWD), continue to pose a considerable burden to the patient and healthcare setting. Predicting those patients at risk of a SWC may give patients and healthcare providers the opportunity to implement a tailored prevention plan or potentially ameliorate known risk factors to improve patient postoperative outcomes.A scoping review of the literature for studies which reported predictive power and internal/external validity of risk tools for clinical use in predicting patients at risk of SWCs after surgery was conducted. An electronic search of three databases and two registries was carried out with date restrictions. The search terms included 'prediction surgical site infection' and 'prediction surgical wound dehiscence'.A total of 73 records were identified from the database search, of which six studies met the inclusion criteria. Of these, the majority of validated risk tools were predominantly within the cardiothoracic domain, and targeted morbidity and mortality outcomes. There were four risk tools specifically targeting SWCs following surgery.The findings of this review have highlighted an absence of well-developed risk tools specifically for SSI and/or SWD in most surgical populations. This review suggests that further research is required for the development and clinical implementation of rigorously validated and fit-for-purpose risk tools for predicting patients at risk of SWCs following surgery. The ability to predict such patients enables the implementation of preventive strategies, such as the use of prophylactic antibiotics, delayed timing of surgery, or advanced wound therapies following a procedure.
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