Impact of SARS-CoV-2 infection on postoperative complications of patients undergoing surgery after general outbreak in China: a protocol for multicentre prospective cohort study

Introduction There is currently limited evidence addressing perioperative prognosis of surgical patients during COVID-19 pandemic; especially targeting on the Chinese population since the wave in 2022. Considering a distinct feature from the rest of the world demonstrated and the fast mutation and s...

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Bibliographic Details
Main Authors: Ziyu Zheng, Gang Luo, Baobao Gao, Lini Wang, Chong Lei
Format: Article
Language:English
Published: BMJ Publishing Group 2023-08-01
Series:BMJ Open
Online Access:https://bmjopen.bmj.com/content/13/8/e072608.full
Description
Summary:Introduction There is currently limited evidence addressing perioperative prognosis of surgical patients during COVID-19 pandemic; especially targeting on the Chinese population since the wave in 2022. Considering a distinct feature from the rest of the world demonstrated and the fast mutation and spread of the virus, evidence most relevant to China is urgently in need. The objective of this study is to seek for supporting evidence via evidence-based risk evaluations for postoperative complications to accumulate experience for coming infection waves.Methods and analysis This protocol proposes a multicentral, prospective, observational cohort study aiming to explore the link between SARS-CoV-2 infection and postoperative complications among surgical patients under general or regional anaesthesia between 16 January 2023 and 31 December 2023. A retrospective cohort covering the same period in 2019 is extracted for historic reference. Data are extracted from the health information system and anaesthesia information management system. The COVID-19 information is collected via an online survey. Missing values in weight or height will be imputed by each other with age and gender via multiple imputation. Other missing values will not be handled specially. Standard descriptive statistics will be reported followed by statistical modelling. Binomial regression with logit link is used for binary outcome. The time-to-event outcome is analysed using Cox regression with discharge from hospital further treated as a competing state. Hierarchical models will be assessed to account for temporal or central random effects. Temporal trends will be displayed with future expectations.Ethics and dissemination Ethical approval is obtained from the ethical committee in Xijing Hospital (No. KY20232002-C-1); approvals are expected for each participating institute. Verbal consent will be informed and obtained prior to online survey collection. Personal information remains confidential, and publications will be deidentified.Trial registration number NCT05677815.
ISSN:2044-6055