Zhang B, Zhu Q, Ji ZP. Nomogram for predicting early complications after distal gastrectomy. World J Gastrointest Surg 2023; 15(11): 2500-2512 [PMID: 38111768 DOI: 10.4240/wjgs.v15.i11.2500]
Corresponding Author of This Article
Zhi-Peng Ji, MD, Associate Chief Physician, Department of Gastrointestinal Surgery, Second Hospital of Shandong University, No. 247 Beiyuan Street, Tianqiao District, Jinan 250033, Shandong Province, China. 17660081217@163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastrointest Surg. Nov 27, 2023; 15(11): 2500-2512 Published online Nov 27, 2023. doi: 10.4240/wjgs.v15.i11.2500
Nomogram for predicting early complications after distal gastrectomy
Biao Zhang, Qing Zhu, Zhi-Peng Ji
Biao Zhang, Qing Zhu, Zhi-Peng Ji, Department of Gastrointestinal Surgery, Second Hospital of Shandong University, Jinan 250033, Shandong Province, China
Author contributions: Zhang B and Ji ZP designed the research study and performed the research; Zhang B and Zhu Q analyzed the data and wrote the manuscript; all authors have read and approve the final manuscript.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of Second Hospital of Shandong University.
Informed consent statement: All study participants or their legal guardian provided informed written consent about personal and medical data collection prior to study enrolment.
Conflict-of-interest statement: We have no financial relationships to disclose.
Data sharing statement: No additional data are available.
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: Zhi-Peng Ji, MD, Associate Chief Physician, Department of Gastrointestinal Surgery, Second Hospital of Shandong University, No. 247 Beiyuan Street, Tianqiao District, Jinan 250033, Shandong Province, China. 17660081217@163.com
Received: September 12, 2023 Peer-review started: September 12, 2023 First decision: September 25, 2023 Revised: October 4, 2023 Accepted: October 30, 2023 Article in press: October 30, 2023 Published online: November 27, 2023 Processing time: 76 Days and 0.7 Hours
ARTICLE HIGHLIGHTS
Research background
Gastric cancer (GC) remains one of the most prevalent malignant tumors globally, contributing to the mortality due to malignant tumors.
Research motivation
Identifying methods to reduce or prevent postoperative morbidity in patients with GC has become a key focus point.
Research objectives
To establish a nomogram prediction model.
Research methods
We included 131 patients who underwent surgery under standard general anesthesia, followed by distal gastrectomy with D2 lymph node dissection.
Research results
The calibration curve (Hosmer Lemeshow test: χ2 = 7.33) showed that the model had good consistency. The results of the decision curve analysis indicated that this model offered good clinical benefits.
Research conclusions
This prediction model can be used to guide the detection of early postoperative complications and has clinical reference value.
Research perspectives
To evaluate the performance of the model more accurately, external validation of big data from other centers is required.
