Han WW, Fang JJ. Analysis of risk factors and predictive value of a nomogram model for sepsis in patients with diabetic foot. World J Diabetes 2025; 16(4): 104088 [DOI: 10.4239/wjd.v16.i4.104088]
Corresponding Author of This Article
Jian-Jiang Fang, MD, Department of Emergency, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, No. 57 Xingning Road, Yinzhou District, Ningbo 315100, Zhejiang Province, China. jianjiangfan6299@yeah.net
Research Domain of This Article
Endocrinology & Metabolism
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 Diabetes. Apr 15, 2025; 16(4): 104088 Published online Apr 15, 2025. doi: 10.4239/wjd.v16.i4.104088
Analysis of risk factors and predictive value of a nomogram model for sepsis in patients with diabetic foot
Wen-Wen Han, Jian-Jiang Fang
Wen-Wen Han, Jian-Jiang Fang, Department of Emergency, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, Ningbo 315100, Zhejiang Province, China
Author contributions: Han WW designed the research, performed data curation, formal analysis, and methodology development, as well as managed resources and utilized software; Han WW also wrote the original draft of the manuscript; Fang JJ reviewed and edited the manuscript to ensure its scientific rigor and clarity, contributing critical input in refining the final draft.
Institutional review board statement: This study was approved by the Ethics Committee of Ningbo Medical Center, Lihuili Hospital.
Informed consent statement: Written informed consent for publication was obtained from all patients and/or their families included in this retrospective analysis.
Conflict-of-interest statement: The authors declare that they have no competing interests.
Data sharing statement: The data sets generated and analyzed during this study are not public, but under reasonable requirements, the correspondence author can provide.
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: Jian-Jiang Fang, MD, Department of Emergency, Ningbo Medical Center Lihuili Hospital, The Affiliated Lihuili Hospital of Ningbo University, No. 57 Xingning Road, Yinzhou District, Ningbo 315100, Zhejiang Province, China. jianjiangfan6299@yeah.net
Received: December 10, 2024 Revised: January 2, 2025 Accepted: February 7, 2025 Published online: April 15, 2025 Processing time: 81 Days and 2.8 Hours
Abstract
BACKGROUND
Sepsis is a severe complication in hospitalized patients with diabetic foot (DF), often associated with high morbidity and mortality. Despite its clinical significance, limited tools exist for early risk prediction.
AIM
To identify key risk factors and evaluate the predictive value of a nomogram model for sepsis in this population.
METHODS
This retrospective study included 216 patients with DF admitted from January 2022 to June 2024. Patients were classified into sepsis (n = 31) and non-sepsis (n = 185) groups. Baseline characteristics, clinical parameters, and laboratory data were analyzed. Independent risk factors were identified through multivariable logistic regression, and a nomogram model was developed and validated. The model's performance was assessed by its discrimination (AUC), calibration (Hosmer-Lemeshow test, calibration plots), and clinical utility [decision curve analysis (DCA)].
RESULTS
The multivariable analysis identified six independent predictors of sepsis: Diabetes duration, DF Texas grade, white blood cell count, glycated hemoglobin, C-reactive protein, and albumin. A nomogram integrating these factors achieved excellent diagnostic performance, with an AUC of 0.908 (95%CI: 0.865-0.956) and robust internal validation (AUC: 0.906). Calibration results showed strong agreement between predicted and observed probabilities (Hosmer-Lemeshow P = 0.926). DCA demonstrated superior net benefit compared to extreme intervention scenarios, highlighting its clinical utility.
CONCLUSION
The nomogram prediction model, based on six key risk factors, demonstrates strong predictive value, calibration, and clinical utility for sepsis in patients with DF. This tool offers a practical approach for early risk stratification, enabling timely interventions and improved clinical management in this high-risk population.
Core Tip: Sepsis remains a significant complication in diabetic foot (DF) patients, often associated with poor outcomes and high mortality. However, early identification of at-risk individuals remains a clinical challenge. In our study, we identified six independent risk factors-diabetes duration, DF Texas grade, white blood cell count, glycated hemoglobin, C-reactive protein, and albumin-that contribute significantly to the risk of sepsis. We developed a nomogram incorporating these factors, demonstrating excellent diagnostic performance and clinical utility.
