Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury
BackgroundAcute 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 nomo...
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2025.1563425/full |
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| author | Hui Lin Hui Lin Hui Lin Yilin Ren Yilin Ren Yilin Ren Jing Cui Junnan Guo Junnan Guo Junnan Guo Mengzhu Wang Mengzhu Wang Mengzhu Wang Lihua Wang Lihua Wang Lihua Wang Xiaole Su Xiaole Su Xiaole Su Xi Qiao Xi Qiao Xi Qiao |
| author_facet | Hui Lin Hui Lin Hui Lin Yilin Ren Yilin Ren Yilin Ren Jing Cui Junnan Guo Junnan Guo Junnan Guo Mengzhu Wang Mengzhu Wang Mengzhu Wang Lihua Wang Lihua Wang Lihua Wang Xiaole Su Xiaole Su Xiaole Su Xi Qiao Xi Qiao Xi Qiao |
| author_sort | Hui Lin |
| collection | DOAJ |
| description | BackgroundAcute 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.MethodsWe conducted a retrospective analysis of 1,241 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 (1,012 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.ResultsSix 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.ConclusionThe 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. |
| format | Article |
| id | doaj-art-497ba62e67ad4410bb6c1c3ce0bcf862 |
| institution | OA Journals |
| issn | 2296-858X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Medicine |
| spelling | doaj-art-497ba62e67ad4410bb6c1c3ce0bcf8622025-08-20T02:08:35ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2025-04-011210.3389/fmed.2025.15634251563425Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injuryHui Lin0Hui Lin1Hui Lin2Yilin Ren3Yilin Ren4Yilin Ren5Jing Cui6Junnan Guo7Junnan Guo8Junnan Guo9Mengzhu Wang10Mengzhu Wang11Mengzhu Wang12Lihua Wang13Lihua Wang14Lihua Wang15Xiaole Su16Xiaole Su17Xiaole Su18Xi Qiao19Xi Qiao20Xi Qiao21Department of Nephrology, Second Hospital of Shanxi Medical University, Taiyuan, ChinaShanxi Kidney Disease Institute, Taiyuan, ChinaKidney Research Center of Shanxi Medical University, Taiyuan, ChinaDepartment of Nephrology, Second Hospital of Shanxi Medical University, Taiyuan, ChinaShanxi Kidney Disease Institute, Taiyuan, ChinaKidney Research Center of Shanxi Medical University, Taiyuan, ChinaDepartment of Endocrinology, Air Force Medical Center, Beijing, ChinaDepartment of Nephrology, Second Hospital of Shanxi Medical University, Taiyuan, ChinaShanxi Kidney Disease Institute, Taiyuan, ChinaKidney Research Center of Shanxi Medical University, Taiyuan, ChinaDepartment of Nephrology, Second Hospital of Shanxi Medical University, Taiyuan, ChinaShanxi Kidney Disease Institute, Taiyuan, ChinaKidney Research Center of Shanxi Medical University, Taiyuan, ChinaDepartment of Nephrology, Second Hospital of Shanxi Medical University, Taiyuan, ChinaShanxi Kidney Disease Institute, Taiyuan, ChinaKidney Research Center of Shanxi Medical University, Taiyuan, ChinaDepartment of Nephrology, Second Hospital of Shanxi Medical University, Taiyuan, ChinaShanxi Kidney Disease Institute, Taiyuan, ChinaKidney Research Center of Shanxi Medical University, Taiyuan, ChinaDepartment of Nephrology, Second Hospital of Shanxi Medical University, Taiyuan, ChinaShanxi Kidney Disease Institute, Taiyuan, ChinaKidney Research Center of Shanxi Medical University, Taiyuan, ChinaBackgroundAcute 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.MethodsWe conducted a retrospective analysis of 1,241 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 (1,012 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.ResultsSix 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.ConclusionThe 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.https://www.frontiersin.org/articles/10.3389/fmed.2025.1563425/fullacute respiratory distress syndrome (ARDS)acute kidney injury (AKI)risk factorearly predictionnomogram |
| spellingShingle | Hui Lin Hui Lin Hui Lin Yilin Ren Yilin Ren Yilin Ren Jing Cui Junnan Guo Junnan Guo Junnan Guo Mengzhu Wang Mengzhu Wang Mengzhu Wang Lihua Wang Lihua Wang Lihua Wang Xiaole Su Xiaole Su Xiaole Su Xi Qiao Xi Qiao Xi Qiao Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury Frontiers in Medicine acute respiratory distress syndrome (ARDS) acute kidney injury (AKI) risk factor early prediction nomogram |
| title | Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury |
| title_full | Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury |
| title_fullStr | Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury |
| title_full_unstemmed | Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury |
| title_short | Nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury |
| title_sort | nomogram risk prediction model for acute respiratory distress syndrome following acute kidney injury |
| topic | acute respiratory distress syndrome (ARDS) acute kidney injury (AKI) risk factor early prediction nomogram |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2025.1563425/full |
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