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ORIGINAL RESEARCH article

Front. Med.

Sec. Nephrology

Volume 12 - 2025 | doi: 10.3389/fmed.2025.1563425

Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury

Provisionally accepted
Hui Lin Hui Lin 1Yilin Ren Yilin Ren 1Jing Cui Jing Cui 2Junnan Guo Junnan Guo 1Mengzhu Wang Mengzhu Wang 1Lihua Wang Lihua Wang 1Xiaole Su Xiaole Su 1Xi Qiao Xi Qiao 1*
  • 1 Second Hospital of Shanxi Medical University, Taiyuan, China
  • 2 Department of Endocrinology, Air force Medical Center, Beijing, China

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

    Background: Acute respiratory distress syndrome (ARDS), a severe form of respiratory failure, can be precipitated by acute kidney injury (AKI), leading to a significant increase in mortality among affected patients. This study aimed to identify the risk factors for ARDS and construct a predictive nomogram.Methods: We conducted a retrospective analysis of 1241 AKI patients admitted to the Second Hospital of Shanxi Medical University from August 25, 2016, to December 31, 2023. The patients were divided into a study cohort (1012 cases, including 108 with ARDS) and a validation cohort (229 cases, including 23 with ARDS). Logistic regression analysis was employed to identify the risk factors for ARDS, which were subsequently incorporated into the development of a nomogram. The predictive performance of the nomogram was assessed by AUC, calibration plots, and decision curve analyses, with external validation also performed.Results: Six risk factors were identified and included in the nomogram: older age (OR=1.020; 95%CI=1.005-1.036), smoking history (OR=1.416; 95%CI=1.213-1.811), history of diabetes mellitus (OR=1.449; 95%CI=1.202-1.797), mean arterial pressure (MAP; OR=1.165; 95%CI=1.132-1.199), higher serum uric acid levels (OR=1.002; 95%CI=1.001-1.004), and higher AKI stage [(stage 1: reference), (stage 2: OR=11.863; 95%CI=4.850-29.014), (stage 3: OR=41.398; 95%CI=30.840-52.731)]. The AUC values were 0.951 in the study cohort and 0.959 in the validation cohort. Calibration and decision curve analyses confirmed the accuracy and clinical utility of the nomogram. Conclusions: The nomogram, which integrates age, smoking history, diabetes mellitus history, MAP, and AKI stage, predicts the risk of ARDS in patients with AKI. This tool may aid in early detection and facilitate clinical decision-making.Introduction

    Keywords: Acute respiratory distress syndrome (ARDS), acute kidney injury (AKI), risk factor, Early prediction, nomogram

    Received: 20 Jan 2025; Accepted: 28 Mar 2025.

    Copyright: © 2025 Lin, Ren, Cui, Guo, Wang, Wang, Su and Qiao. 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: Xi Qiao, Second Hospital of Shanxi Medical University, Taiyuan, 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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