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©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Mar 27, 2023; 15(3): 387-397
Published online Mar 27, 2023. doi: 10.4240/wjgs.v15.i3.387
Risk factors and prediction model for inpatient surgical site infection after elective abdominal surgery
Jin Zhang, Fei Xue, Si-Da Liu, Dong Liu, Yun-Hua Wu, Dan Zhao, Zhou-Ming Liu, Wen-Xing Ma, Ruo-Lin Han, Liang Shan, Xiang-Long Duan
Jin Zhang, Fei Xue, Si-Da Liu, Dong Liu, Yun-Hua Wu, Zhou-Ming Liu, Wen-Xing Ma, Ruo-Lin Han, Xiang-Long Duan, Second Department of General Surgery, Shaanxi Provincial People's Hospital, Xi’an 710068, Shaanxi Province, China
Fei Xue, Xiang-Long Duan, Institute of Medical Research, Northwestern Polytechnical University, Xi’an 710072, Shaanxi Province, China
Fei Xue, Xiang-Long Duan, Second Department of General Surgery, Third Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710068, Shaanxi Province, China
Dan Zhao, Computer Science School, Universiti Sains Malaysia, Penang 11800, Malaysia
Liang Shan, Medical Service, Shaanxi Provincial People's Hospital, Xi’an 710068, Shaanxi Province, China
Author contributions: All the authors solely contributed to this paper; Zhang J, Xue F, Liu SD, Liu D and Wu YH designed the research study; Zhao D, Liu ZM, Ma WX and Han RL performed the research; Zhang J, Zhao D and Xue F analyzed the data and wrote the manuscript; Shan L and Duan XL were responsible for revising the manuscript for important intellectual content; and all authors read and approved the final version.
Supported by Key Research and Development Program of Shaanxi, No. 2020GXLH-Y-019 and 2022KXJ-141; Innovation Capability Support Program of Shaanxi, No. 2019GHJD-14 and 2021TD-40; Science and Technology Talent Support Program of Shaanxi Provincial People's Hospital, No. 2021LJ-05; 2023 Natural Science Basic Research Foundation of Shaanxi Province, No. 2023-JC-YB-739.
Institutional review board statement: The study was reviewed and approved by the ethics committee of the Shaanxi Provincial People's Hospital, No. 2021-315.
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Dataset available from the corresponding author at 584710525@qq.com. Participants gave informed consent for data sharing.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
https://creativecommons.org/Licenses/by-nc/4.0/ Corresponding author: Liang Shan, MD, Attending Doctor, Medical Service, Shaanxi Provincial People's Hospital, No. 256 West Youyi Road, Beilin District, Xi’an 710068, Shaanxi Province, China. 584710525@qq.com
Received: October 31, 2022
Peer-review started: October 31, 2022
First decision: January 3, 2023
Revised: January 11, 2023
Accepted: February 15, 2023
Article in press: February 15, 2023
Published online: March 27, 2023
Processing time: 147 Days and 6.3 Hours
ARTICLE HIGHLIGHTS
Research background
Surgical site infections (SSIs) can increase mortality and prolong the length of hospital stay, thereby increasing healthcare costs. Therefore, it is much necessary to develop a prediction model after elective abdominal surgeries in order to identify risk factors of SSI.
Research motivation
To establish a predictive model for SSI which is more easily assess the risk of it. And provide timely interventions for high-risk patients to improve the quality of care so as to reduce medical costs and ease the burden on patients.
Research objectives
The present study aimed to develop a realistic, feasible, valid and unique model for predicting the risk of elective abdominal SSI.
Research methods
This observational study was conducted from January 1, 2018 to January 1, 2021 using patient demographic data and haematological test results. Inpatient SSI risk factors were evaluated using univariate analysis and multivariate logistic regression. Nomograms were used in the predictive models. The receiver operating characteristic and area under the curve values were used to measure the specificity and accuracy of the model.
Research results
The key findings indicated that the surgical sites included the uterus (42.2%), the liver (27.6%), the gastrointestinal tract (19.1%), the appendix (5.9%), the kidney (3.7%), and the groin area (1.4%). SSI occurred in 5% of the patients (n = 150). Multivariate logistic regression revealed the following independent risk factors: A history of diabetes, antibiotic use, a Nutritional Risk Screening 2002 score of ≥ 3, general anaesthesia, a National Nosocomial Infections Surveillance (NNIS) score of ≥ 2, procalcitonin ≥ 0.05 μg/L, low-density lipoprotein cholesterol < 3.37 mmol/L, intraoperative blood loss ≥ 200 mL, surgical season, surgical site, and incision grade (all P < 0.05. The overall area under the receiver operating characteristic curve of the predictive model was 0.926, which was significantly higher than that of the NNIS (0.662).
Research conclusions
The patient’s condition and haematological test indicators formed the bases of our prediction model. It is a novel, efficient, and highly accurate predictive model for preventing postoperative SSI, thereby improving the prognosis in patients undergoing abdominal surgery.
Research perspectives
This study developed the accurate model for predicting the risk of elective abdominal SSI. We plan to make larger multi-centre and large sample studies in order to obtain more realistic and valid data results.
