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

Kylie Sandy-Hodgetts, Ojan Assadian, Thomas W. Wainwright, Melissa Rochon, Zhavandre Van Der Merwe, Rhidian Morgan Jones, Thomas Serena, Paulo Alves, George Smith

Research output: Contribution to journalArticlepeer-review


OBJECTIVE: 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. METHOD: 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'. RESULTS: 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. CONCLUSION: 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.

Original languageEnglish
Pages (from-to)S4-S12
Number of pages8
JournalJournal of wound care
Issue numberSup8a
Publication statusPublished - 1 Aug 2023


  • Algorithms
  • Early detection
  • Prediction
  • Prevention
  • Surgical site infection
  • Surgical wound complication
  • Surgical wound dehiscence
  • Wound
  • Wound care
  • Wound dressing
  • Wound healing


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