Surgical site infections in patients undergoing breast oncological surgery during the lockdown An unexpected lesson from the COVID-19 pandemic

GIORNALE DI CHIRURGIA(2022)

引用 2|浏览15
暂无评分
摘要
Background: The present study aims to evaluate how the measures to contain the SARS-CoV-2 spreading affected the surgical site infections (SSIs) rate in patients who underwent nondeferrable breast cancer surgery (BCS). Methods: This study is a retrospective analysis of prospectively collected data from a consecutive series of patients underwent nondeferrable BCS in a regional Italian Covid-free hub during two different period: March to April 2020 (pandemic cohort [PC]) and March till April 2019 (control cohort [CC]). SSIs were defined according to the criteria established by the Center for disease control and prevention (CDC) and additional treatment, serous discharge, erythema, purulent exudate, separation of deep tissues, isolation of bacteria, and stay (ASEPSIS) scoring systems. Results: One hundred ninety-nine patients were included in the present study: 100 and 99 patients who underwent nondeferrable BCS from March to April 2020 (PC) and from March to April 2019 (CC), respectively. The overall SSIs rate in this series was 9.1% according to CDC criteria and 6.5% according to ASEPSIS criteria. The SSIs incidence decreased during the pandemic period. Moreover, the SS's rate according to ASEPSIS criteria was statistically lower in the PC than in the CC. We observed significant evidence of higher SSIs, both in terms of CDC and ASEPSIS score, in patients having undergone breast reconstruction compared with patients not undergoing immediate reconstruction. Conclusions: The restrictive measures issued during the lockdown period seemed to lower the SSIs rates in patients undergoing nondeferrable BCS.
更多
查看译文
关键词
Covid-19 pandemic, Breast cancer, Surgical site infections, Center for Disease Control and Prevention (CDC), Additional treatment, Serous discharge, Erythema, Purulent exudate, Separation of deep tissues, Isolation of bacteria, Stay (ASEPSIS)
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要