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ORIGINAL RESEARCH article

Front. Oncol.

Sec. Surgical Oncology

Volume 15 - 2025 | doi: 10.3389/fonc.2025.1528036

A Dynamic Nomogram Predicting Nosocomial Infections in Patients after Colon Cancer Surgery

Provisionally accepted
Xue Yao Xue Yao 1Shuhui Wang Shuhui Wang 2Anning Lu Anning Lu 3Na Li Na Li 1Yun Xu Yun Xu 1*
  • 1 Weifang People's Hospital, Weifang, China
  • 2 Qilu Hospital, Shandong University, Jinan, Shandong Province, China
  • 3 Shandong Second Medical University, Weifang, Shandong Province, China

The final, formatted version of the article will be published soon.

    Objective: Nosocomial infections are one of the severe postoperative complications that compromise perioperative safety in patients with colon cancer. However, there are limited studies on constructing visual risk prediction screening tools for nosocomial infections in these patients. The objective of this study is to construct a nomogram for predicting the risk of nosocomial infections among patients after colon cancer surgery.: Total 1146 patients after colon cancer surgery were selected and divided into a training set and a validation set. After identifying the most significant predictors through LASSO regression and logistic regression, the model was presented as static and dynamic nomogram. AUC was used to evaluate the discrimination of model. Calibration was evaluated by means of calibration curves. Decision and impact curves were applied to evaluate the clinical validity. Results: 110 patients (9.60%) suffered nosocomial infections following colon cancer surgery. Peak temperature on the second postoperative day, Braden score on the first postoperative day, duration of retention of abdominal drains, ASA class, surgical type and postoperative complications were correlated with nosocomial infections. The nomogram composed of these predictors demonstrated good discrimination, calibration and clinical benefit in both the training and validation sets.Risk predictors are important breakthroughs for healthcare workers in nosocomial infections prevention and control initiatives. The dynamic nomogram built in this study may be helpful for healthcare personnel to identify the risk of nosocomial infections among patients after colon cancer surgery.

    Keywords: Colon Cancer, nosocomial infections, prediction, nomogram, Model

    Received: 14 Nov 2024; Accepted: 10 Feb 2025.

    Copyright: © 2025 Yao, Wang, Lu, Li and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yun Xu, Weifang People's Hospital, Weifang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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