Diagnosis of infection after cardiovascular surgery (DICS): a study protocol for developing and validating a prediction model in prospective observational study

心血管手术后感染诊断(DICS):一项前瞻性观察研究中预测模型开发与验证的研究方案

阅读:1

Abstract

INTRODUCTION: Postoperative infection (PI) is one of the main severe complications after cardiovascular surgery. Therefore, antibiotics are routinely used during the first 48 hours after cardiovascular surgery. However, there is no effective method for early diagnosis of infection after cardiovascular surgery, particularly, to determine whether postoperative patients need to prolong the use of antibiotics after the first 48 hours. In this study, we aim to develop and validate a diagnostic model to help identify whether a patient has been infected after surgery and guide the appropriate use of antibiotics. METHODS AND ANALYSIS: In this prospective study, we will develop and validate a diagnostic model to determine whether the patient has a bacterial infection within 48 hours after cardiovascular surgery. Baseline data will be collected through the electronic medical record system. A total of 2700 participants will be recruited (n=2000 for development, n=700 for validation). The primary outcome of the study is the newly PI during the first 48 hours after cardiovascular surgery. Logistic regression penalised with elastic net regularisation will be used for model development and bootstrap and k-fold cross-validation aggregation will be performed for internal validation. The derived model will be also externally validated in patients who are continuously included in another time period (N=700). We will evaluate the calibration and differentiation performance of the model by Hosmer-Lemeshow good of fit test and the area under the curve, respectively. We will report sensitivity, specificity, positive predictive value and negative predictive value in the validation data-set, with a target of 80% sensitivity. ETHICS AND DISSEMINATION: Ethical approval was obtained from Medical Ethics Committee of Affiliated Nanjing Drum Tower Hospital, Nanjing University Medical College (2020-249-01). TRIAL REGISTRATION NUMBER: Chinese Clinical Trial Register (www.chictr.org.cn, ChiCTR2000038762); Pre-results.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。