1097 17 Years of Treating Deep Sternal Wound Infections at A Single Institution: Outcomes and Lessons Learned. (12th October 2021)

• Record Type: Journal Article
• Authors: Argyriou, A; Hasan, R; Abunasra, H; McLaughlin, K; Bilal, H; Sogliani, F; Datta, S
• Is Part Of: British journal of surgery. Volume 108:Supplement 6(2021)
• Publication Date: 2021-10-12
• Subjects: Surgery -- Periodicals; 617.005
• DOI: 10.1093/bjs/znab259.253
• Languages: English
• ISSNs: 0007-1323

Abstract

Abstract: Introduction: Deep sternal wound infections (DSWI) are a serious complication following cardiac surgery that comprise of any infection penetrating the subcutaneous tissue of the sternum. DSWI have been found to increase mortality and worsen prognostic outcomes following surgery. Method: We conducted a retrospective cohort study using hospital e-records from 2000 to 2017 of all adult patients operated on with a median sternotomy at our institution. Univariate and multivariate analysis along with mortality and Kaplan-Meier survival curves compared the DSWI population against the remaining study population, using SPSS-25 software. Results: Of 15521 total patients in the study, 145 (0.9%) suffered a DSWI. Variables that were associated with DSWI included age at operation (p = 0.019), gender (p = 0.007), BMI (p = 0.001), diabetes (p < 0.0001), renal disease (p = 0.008), operative urgency (p = 0.007), type of operation (p = 0.02), Euroscore (p = <0.0001), bypass-time (p = 0.038) and crossclamp-time (p = 0.008). A logistic regression encompassing significant variables revealed that gender (p = 0.031 CI 1.45-1.96), BMI (p < 0.0001 CI 1.03-1.10), diabetes (p = 0.007 CI 1.20-3.67) and type of operation (p = 0.018 CI 1.23-1.87) remained significant when covariate contribution was eliminated. DSWI subgroup mortality was insignificant at 30 days (3.4%vs2.9%, p = 0.68) but significantly worse at 90 days (8.3%vs3.7%, p = 0.004) and at 1 year (17.2%vs5.4%, p < 0.0001). Kaplan-Meier analysis depicted a significantly worse survival distribution for the DSWI population compared to rest of study (Log-Rank<0.05). Conclusions: At our centre, DSWI are attributable to certain modifiable and set demographics and contribute heavily to medium-term mortality. A better understanding of DSWI risk factors may pinpoint those at risk and benefit the multidisciplinary team to ultimately reduce the rate of DSWI.