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ORIGINAL RESEARCH article

Front. Med.
Sec. Intensive Care Medicine and Anesthesiology
Volume 11 - 2024 | doi: 10.3389/fmed.2024.1474311
This article is part of the Research Topic Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume V View all 6 articles

Development and Validation of a Web-Based Nomogram for Acute Kidney Injury in Acute Non-Variceal Upper Gastrointestinal Bleeding Patients

Provisionally accepted
Chaolian Wei Chaolian Wei 1Cao Honghua Cao Honghua 2Lina Huang Lina Huang 1Lu-Huai Feng Lu-Huai Feng 1*
  • 1 Guangxi Medical University Cancer Hospital, Nanning, China
  • 2 Guigang City People's Hospital, Guigang, China

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

    Background: Acute kidney injury (AKI) is a common and serious complication in patients with acute non-variceal upper gastrointestinal bleeding (NVUGIB). Early prediction and intervention are crucial for improving patient outcomes.: Data for patients presenting with acute NVUGIB in this retrospective study were sourced from the MIMC-IV database. Patients were randomly allocated into training and validation cohorts for further analysis. Independent predictors for AKI were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses in the training cohort. Based on the logistic regression results, a nomogram was developed to predict early AKI onset in acute NVUGIB patients, and implemented as a web-based calculator for clinical application. The nomogram's performance was evaluated through discrimination, using the C-index, calibration curves, and decision curve analysis (DCA) to assess its clinical value. Results: The study involved 1082 acute NVUGIB patients, with 406 developing AKI. A multivariable logistic regression identified five key AKI predictors: CKD, use of human albumin, chronic liver disease, glucose, and blood urea nitrogen. The nomogram was constructed based on independent predictors. The nomogram exhibited robust accuracy, evidenced by a C-index of 0.73 in the training cohort and 0.72 in the validation cohort. Calibration curves demonstrated satisfactory concordance between predicted and observed AKI occurrences. DCA revealed that the nomogram offered considerable clinical benefit within a threshold probability range of 7% to 54%. Conclusion: Our nomogram is a valuable tool for predicting AKI risk in patients with acute NVUGIB, offering potential for early intervention and improved clinical outcomes.

    Keywords: Acute Kidney Injury, prediction, nomogram, Intensive Care Unit, Upper gastrointestinal hemorrhage

    Received: 01 Aug 2024; Accepted: 23 Sep 2024.

    Copyright: © 2024 Wei, Honghua, Huang and Feng. 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: Lu-Huai Feng, Guangxi Medical University Cancer Hospital, Nanning, 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.