Nomogram construction and validation for predicting infection recurrence after necrotic tissue debridement in severe acute pancreatitis

doi:10.4240/wjgs.122812

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Publication Name

World Journal of Gastrointestinal Surgery

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1948-9366

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastrointest Surg. Oct 27, 2026; 18(10): 122812
Published online Oct 27, 2026. doi: 10.4240/wjgs.122812

Nomogram construction and validation for predicting infection recurrence after necrotic tissue debridement in severe acute pancreatitis

Zi-Yun Yang, Shu-Yao Wang, Fei Wang, Yuan-Yuan Yu, Shi-Ying Wan, Yang Shao, Zhuo-Jun Lu, Yan-Cui Zhu

Zi-Yun Yang, Fei Wang, Yan-Cui Zhu, Intensive Care Unit, The First Affiliated Hospital of Kunming Medical University, Kunming 650000, Yunnan Province, China

Shu-Yao Wang, Yuan-Yuan Yu, Shi-Ying Wan, Yang Shao, Department of Anesthesiology, The First Affiliated Hospital of Kunming Medical University, Kunming 650000, Yunnan Province, China

Zhuo-Jun Lu, Department of Rehabilitation, The First Affiliated Hospital of Kunming Medical University, Kunming 650000, Yunnan Province, China

Co-first authors: Zi-Yun Yang and Shu-Yao Wang.

Author contributions: Yang ZY, Wang SY, Wang F, Yu YY, Wan SY, Shao Y, and Lu ZJ contributed to data collection and paper writing; Yang ZY and Wang SY contributed equally to this manuscript as co-first authors; Yang ZY, Wang SY, Wang F, Yu YY, Wan SY, Shao Y, Lu ZJ, and Zhu YC contributed to research design and data analysis; Zhu YC was responsible for funding application, reviewing and editing, communication coordination, ethical review, copyright and licensing, and follow-up. All authors have read and approved the final manuscript.

AI contribution statement: During the preparation of this manuscript, DeepL was used for English translation and language polishing, while no other AI tools including ChatGPT and Grammarly were utilized; none of the main text of the manuscript (Abstract, Introduction, Materials and Methods, Results, Discussion, and Conclusion) was AI-generated, and no AI tools were applied for data analysis, writing assistance, study design or result interpretation, nor were any images in the manuscript generated by AI.

Supported by Kunming Medical University Undergraduate Innovative Research Program.

Institutional review board statement: The research was reviewed and approved by The First Affiliated Hospital of Kunming Medical University.

Clinical trial registration statement: This study is a single-center, small-sample, prospective observational study, not falling within the scope of interventional clinical trials. The study only conducted the observation and analysis of clinical data and did not involve the intervention of new drugs, new devices, or treatment plans. During the design and implementation of the study, in accordance with the nature of the study and relevant management requirements, no clinical trial registration was conducted. This study has been reviewed by the ethics committee of the affiliated institution, and the entire process adhered to medical research norms. Subsequent related studies will strictly follow the relevant requirements for clinical trial registration.

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.

CONSORT 2010 statement: The authors have read the CONSORT 2010 Statement, and the manuscript was prepared and revised according to the CONSORT 2010 Statement.

Data sharing statement: No other data available.

Corresponding author: Yan-Cui Zhu, Associate Chief Physician, Intensive Care Unit, The First Affiliated Hospital of Kunming Medical University, No. 295 Xichang Road, Wuhua District, Kunming 650000, Yunnan Province, China. 18787710531@163.com

Received: May 29, 2026
Revised: June 26, 2026
Accepted: July 16, 2026
Published online: October 27, 2026
Processing time: 144 Days and 6.9 Hours

Abstract

BACKGROUND

Postoperative infection recurrence remains a major challenge following necrotic tissue debridement in severe acute pancreatitis (SAP), yet reliable tools for early risk stratification are lacking. Although several clinical and laboratory parameters have been associated with infection outcomes, no simple, practical model exists to predict individualized recurrence risk. This study hypothesized that a nomogram incorporating preoperative clinical scores and inflammatory markers could effectively stratify patients by recurrence risk.

AIM

To construct and validate a nomogram for predicting infection recurrence after necrotic tissue debridement in patients with SAP.

METHODS

This study included 312 SAP patients who underwent necrotic tissue debridement at a single center (2023-2025), divided 7:3 into a modeling cohort (n = 218) and a validation cohort (n = 94). Infection recurrence within 30 days post-surgery was the primary outcome. Multivariate logistic regression identified independent risk factors, which were incorporated into a nomogram. Model performance was evaluated by receiver operating characteristic curves, calibration plots, and decision curve analysis.

RESULTS

Multivariate logistic regression identified Acute Physiology and Chronic Health Evaluation II score [odds ratio (OR) = 1.384, 95% confidence interval (CI): 1.147-1.670], computed tomography severity index score (OR = 4.231, 95%CI: 2.336-7.663), and C-reactive protein (OR = 1.051, 95%CI: 1.023-1.079) as independent risk factors for infection recurrence (all P < 0.05). The nomogram showed good discrimination in both the modeling cohort (area under the curve = 0.863, 95%CI: 0.798-0.927) and the validation cohort (area under the curve = 0.809, 95%CI: 0.751-0.867). Calibration was satisfactory (Hosmer-Lemeshow test: P = 0.849 and P = 0.715, respectively). Decision curve analysis confirmed clinical net benefit across risk thresholds of 0.10-0.75 and 0.10-0.85.

CONCLUSION

The nomogram incorporating Acute Physiology and Chronic Health Evaluation II, computed tomography severity index, and C-reactive protein demonstrates good predictive performance for postoperative infection recurrence in SAP patients and may serve as a practical tool for individualized risk stratification.

Keywords: Severe acute pancreatitis; Necrotic tissue debridement; Infection recurrence; Nomogram; Predictive model

Core Tip: This study developed and validated a nomogram to predict infection recurrence after necrotic tissue debridement in patients with severe acute pancreatitis. The model incorporates three independent risk factors: Acute Physiology and Chronic Health Evaluation II score, computed tomography severity index score, and C-reactive protein level. It demonstrated robust predictive performance and clinical utility, offering a practical tool for the individualized risk assessment of postoperative infection recurrence in severe acute pancreatitis patients.