Acta Dermato-Venereologica 98-7CompleteContent | Page 15

CLINICAL REPORT 683 A Clinical Prediction Model for Surgical Site Infections in Dermato­ logical Surgery Xiaomeng LIU 1–3 , Nicole W. J. KELLENERS-SMEETS 1,2 , Melissa SPRENGERS 1 , Vishal HIRA 4 , Klara MOSTERD 1,2 and Patty J. NELEMANS 5 Department of Dermatology, 2 GROW, School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, Department of Dermatology, Flevo Hospital, Almere, 4 Department of Medical Microbiology and Infection Prevention, Groene Hart Ziekenhuis, Gouda, and 5 Department of Epidemiology, Maastricht University, Maastricht, The Netherlands 1 3 To adequately identify patients at risk for surgical site infection in dermatological surgery and effectively prescribe antibiotic prophylaxis, a prediction model may be helpful. Such a model was developed using data from 1,407 patients who underwent dermatolo- gical surgery without antibiotic prophylaxis. The mul- tivariable logistic regression model included type of closure, tumour location and defect size as risk fac- tors. Bootstrapping was used for internal validation. The overall performance of the model was good, with an area under the curve of 84.1%. The decision curve analysis showed that the model is potentially useful if one is willing to treat more than 8 patients with anti- biotic prophylaxis to avoid one infection. For those who prefer more restrictive use of antibiotic prophy- laxis, a default strategy of treating no patients at all with prophylaxis would be the best choice. External validation of the model is required before it can be wi- dely applied. Key words: surgical site infection; antibiotic prophylaxis; der- matological surgery; prediction model. Accepted Apr 12, 2018; Epub ahead of print Apr 12, 2018 Acta Derm Venereol 2018; 98: 683–688. Corr: Xiaomeng Liu, Department of Dermatology, Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, The Nether- lands. E-mail: [email protected] S urgical site infection (SSI) is a major concern in dermatological surgery. It impairs wound healing and could worsen cosmetic outcome. Although rare, systemic infection might also result from a SSI and is associated with substantial morbidity. Fortunately, the incidence rate of SSI is generally below 5% (1–8). Despite the low rate of SSI, however, many dermatologica l surgeons prescribe antibiotic prophylaxis on a regular basis (9–11). The over­use of antibiotics could lead to a range of ad- verse events, including allergic reactions. According to a recent study from the USA, adverse events due to systemic antibiotics accounted for 14.1% of visits to the emergency department (12). In addition, over-prescribing of antibiotics will result in increased antimicrobial resis- tance (13). Therefore, antibiotic prophylaxis should be considered only when there is a substantial risk of SSI. In our previous study on SSI after dermatological surgery, specific risk factors that increase the risk of SIGNIFICANCE Surgical site infection is one of the complications of der- matological surgery and could be prevented by antibiotic prophylaxis. To limit the overuse of antibiotics, the correct identification of patients at risk for such an infection is very important. A prediction model was developed in the current study for this purpose. This model adequately predicts the risk of surgical site infection based on the type of wound closure, the anatomical location and the size of the wound. Application of the model can help dermatologists to predict the risk of surgical site infection and effectively prescribe antibiotic prophylaxis prior to surgery. acquiring a SSI have been identified, including the loca- tion of the tumour, size of the defect and the method of closure (14). Other patient-, environment- and procedure- related factors have been studied with conflicting results (1–8). To adequately assess the risk of SSI in a clinical setting, the combination of different risk factors in each patient should be evaluated. Clinical prediction models could serve this purpose by risk estimation for individual patients based on combinations of multiple predictors. Currently, such a prediction model is not available for dermatological surgery. Correctly identifying the patients at risk for SSI could minimize the overuse of antibiotic prophylaxis and reduce the rate of SSI. The aim of this study was to develop a clinical prediction model to facilitate the decision whether to give antibiotic prophylaxis, based on individual risk of SSI in patients undergoing derma- tological surgery. METHODS Patients A retrospective cohort study was conducted at the Department of Dermatology, Maastricht University Medical Centre (14). All patients who received surgery under local anaesthesia from April 2014 to April 2015 were included. A waiver to obtain written informed consent was authorized by the local medical ethics com- mittee because the study protocol did not involve deviations from standard care. Patients with biopsies, curettages, shave-excisions or laser procedures were excluded. Patients who received anti- biotics in the perioperative period (1 month prior to or after the procedure) were also excluded. Data on patient-, operation- and lesion-related characteristics were retrospectively collected from This is an open access article under the CC BY-NC license. www.medicaljournals.se/acta Journal Compilation © 2018 Acta Dermato-Venereologica. doi: 10.2340/00015555-2945 Acta Derm Venereol 2018; 98: 683–688