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The Perth Surgical Wound Dehiscence Risk Assessment Tool (PSWDRAT): development and prospective validation in the clinical setting
Journal article   Peer reviewed

The Perth Surgical Wound Dehiscence Risk Assessment Tool (PSWDRAT): development and prospective validation in the clinical setting

Kylie Sandy-Hodgetts, Keryln Carville, Nick Santamaria, Richard Parsons and Gavin D Leslie
Journal of wound care, Vol.28(6), pp.332-344
2019
PMID: 31166854

Abstract

Adult Age Factors Aged Aged, 80 and over Australia - epidemiology Cardiovascular Diseases - epidemiology Case-Control Studies Diabetes Mellitus - epidemiology Female Humans Male Middle Aged Obesity - epidemiology Peripheral Arterial Disease - epidemiology Preoperative Care Prospective Studies Retrospective Studies Risk Assessment - methods Smoking - epidemiology Surgical Procedures, Operative - statistics & numerical data Surgical Wound Dehiscence - epidemiology Young Adult
The worldwide volume of surgery today is considerable and postoperative wound healing plays a significant part in facilitating a patient's recovery and rehabilitation. While contemporary surgical procedures are relatively safe, complications such as surgical wound dehiscence (SWD) or breakdown of the incision site may occur despite advances in surgical techniques, infection control practices and wound care. SWD impacts on patient mortality and morbidity and significantly contributes to prolonged hospital stay. Preoperative identification of patients at risk of SWD may be valuable in reducing the risk of postoperative wound complications. A three-phase study was undertaken to determine risk factors associated with SWD, develop a preoperative patient risk assessment tool and to prospectively validate the tool in a clinical setting. Phases 1 and 2 were retrospective case control studies. Phase 1 determined variables associated with SWD and these informed the development of a risk assessment tool. Univariate analysis and multiple logistic regression were applied to identify predictors of surgical risk. Phase 2 used the receiver operator curve statistic to determine the predictive power of the tool. Phase 3 involved a prospective consecutive case series validation to test the inter-rater reliability and predictive power of the tool. In addition to those already identified in the literature, one independent risk predictor for SWD was identified: previous surgery in the same anatomical location (p<0.001, odds ratio [OR] 4). Multiple combined factors were integrated into the tool and included: age (p<0.019, OR 3), diabetes (p<0.624, OR 2), obesity (p<0.94, OR 1.4), smoking (p<0.387, OR 2), cardiovascular disease (p<0.381 OR 3) and peripheral arterial disease (p<0.501, OR 3). The predictive power of the tool yielded 71% in a combined data sample. Patients with previous surgery in the same anatomical location were four times more likely to incur a dehiscence. Identification of at-risk patients for complications postoperatively is integral to reducing SWD occurrence and improving health-related outcomes following surgery.

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Collaboration types
Domestic collaboration
Citation topics
1 Clinical & Life Sciences
1.23 Antibiotics & Antimicrobials
1.23.1036 Surgical Site Infection
Web Of Science research areas
Dermatology
ESI research areas
Clinical Medicine
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