A Novel Predictive Model for Acute Kidney Injury Following Surgery of the Aorta
Background: Acute kidney injury (AKI) frequently occurs after aortic surgery and has a significant impact on patient outcomes. Early detection or prediction of AKI is crucial for timely interventions. This study aims to develop and validate a novel model for predicting AKI following aortic surgery....
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IMR Press
2024-02-01
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| Series: | Reviews in Cardiovascular Medicine |
| Subjects: | |
| Online Access: | https://www.imrpress.com/journal/RCM/25/2/10.31083/j.rcm2502054 |
| _version_ | 1827338768251617280 |
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| author | Mingjian Chen Sheng Zhao Pengfei Chen Diming Zhao Liqing Wang Zhaoyang Chen |
| author_facet | Mingjian Chen Sheng Zhao Pengfei Chen Diming Zhao Liqing Wang Zhaoyang Chen |
| author_sort | Mingjian Chen |
| collection | DOAJ |
| description | Background: Acute kidney injury (AKI) frequently occurs after aortic surgery and has a significant impact on patient outcomes. Early detection or prediction of AKI is crucial for timely interventions. This study aims to develop and validate a novel model for predicting AKI following aortic surgery. Methods: We enrolled 156 patients who underwent on-pump aortic surgery in our hospital from February 2023 to April 2023. Postoperative levels of eight cytokines related to macrophage polarization analyzed using a multiplex cytokine assay. All-subset regression was used to select the optimal cytokines to predict AKI. A logistic regression model incorporating the selected cytokines was used for internal validation in combination with a bootstrapping technique. The model’s ability to discriminate between cases of AKI and non-AKI was assessed using receiver operating characteristic (ROC) curve analysis. Results: Of the 156 patients, 109 (69.87%) developed postoperative AKI. Interferon-gamma (IFN-γ) and interleukin-4 (IL-4) were identified as candidate AKI predictors. The cytokine-based model including IFN-γ and IL-4 demonstrated excellent discrimination (C-statistic: 0.90) and good calibration (Brier score: 0.11). A clinical nomogram was generated, and decision curve analysis revealed that the cytokine-based model outperformed the clinical factor-based model in terms of net benefit. Moreover, both IFN-γ and IL-4 emerged as independent risk factors for AKI. Patients in the second and third tertiles of IFN-γ and IL-4 concentrations had a significantly higher risk of severe AKI, a higher likelihood of requiring renal replacement therapy, or experiencing in-hospital death. These patients also had extended durations of mechanical ventilation and intensive care unit stays, compared with those in the first tertile (all p for group trend <0.001). Conclusions: We successfully established a novel and powerful predictive model for AKI, and demonstrating the significance of IFN-γ and IL-4 as valuable clinical markers. These cytokines not only predict the risk of AKI following aortic surgery but are also linked to adverse in-hospital outcomes. This model offers a promising avenue for the early identification of high-risk patients, potentially improving clinical decision-making and patient care. |
| first_indexed | 2024-03-07T19:39:20Z |
| format | Article |
| id | doaj.art-22f114d238174154b441c56400a52298 |
| institution | Directory Open Access Journal |
| issn | 1530-6550 |
| language | English |
| last_indexed | 2024-03-07T19:39:20Z |
| publishDate | 2024-02-01 |
| publisher | IMR Press |
| record_format | Article |
| series | Reviews in Cardiovascular Medicine |
| spelling | doaj.art-22f114d238174154b441c56400a522982024-02-29T06:14:30ZengIMR PressReviews in Cardiovascular Medicine1530-65502024-02-012525410.31083/j.rcm2502054S1530-6550(23)01154-7A Novel Predictive Model for Acute Kidney Injury Following Surgery of the AortaMingjian Chen0Sheng Zhao1Pengfei Chen2Diming Zhao3Liqing Wang4Zhaoyang Chen5Department of Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 100037 Beijing, ChinaDepartment of Cardiology, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, 100037 Beijing, ChinaDepartment of Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 100037 Beijing, ChinaDepartment of Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 100037 Beijing, ChinaDepartment of Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, 100037 Beijing, ChinaCardiology Department, Heart Center of Fujian Province, Union Hospital, Fujian Medical University, 350000 Fuzhou, Fujian, ChinaBackground: Acute kidney injury (AKI) frequently occurs after aortic surgery and has a significant impact on patient outcomes. Early detection or prediction of AKI is crucial for timely interventions. This study aims to develop and validate a novel model for predicting AKI following aortic surgery. Methods: We enrolled 156 patients who underwent on-pump aortic surgery in our hospital from February 2023 to April 2023. Postoperative levels of eight cytokines related to macrophage polarization analyzed using a multiplex cytokine assay. All-subset regression was used to select the optimal cytokines to predict AKI. A logistic regression model incorporating the selected cytokines was used for internal validation in combination with a bootstrapping technique. The model’s ability to discriminate between cases of AKI and non-AKI was assessed using receiver operating characteristic (ROC) curve analysis. Results: Of the 156 patients, 109 (69.87%) developed postoperative AKI. Interferon-gamma (IFN-γ) and interleukin-4 (IL-4) were identified as candidate AKI predictors. The cytokine-based model including IFN-γ and IL-4 demonstrated excellent discrimination (C-statistic: 0.90) and good calibration (Brier score: 0.11). A clinical nomogram was generated, and decision curve analysis revealed that the cytokine-based model outperformed the clinical factor-based model in terms of net benefit. Moreover, both IFN-γ and IL-4 emerged as independent risk factors for AKI. Patients in the second and third tertiles of IFN-γ and IL-4 concentrations had a significantly higher risk of severe AKI, a higher likelihood of requiring renal replacement therapy, or experiencing in-hospital death. These patients also had extended durations of mechanical ventilation and intensive care unit stays, compared with those in the first tertile (all p for group trend <0.001). Conclusions: We successfully established a novel and powerful predictive model for AKI, and demonstrating the significance of IFN-γ and IL-4 as valuable clinical markers. These cytokines not only predict the risk of AKI following aortic surgery but are also linked to adverse in-hospital outcomes. This model offers a promising avenue for the early identification of high-risk patients, potentially improving clinical decision-making and patient care.https://www.imrpress.com/journal/RCM/25/2/10.31083/j.rcm2502054acute kidney injurymacrophage polarizationcytokinepredictive modelaortic surgery |
| spellingShingle | Mingjian Chen Sheng Zhao Pengfei Chen Diming Zhao Liqing Wang Zhaoyang Chen A Novel Predictive Model for Acute Kidney Injury Following Surgery of the Aorta Reviews in Cardiovascular Medicine acute kidney injury macrophage polarization cytokine predictive model aortic surgery |
| title | A Novel Predictive Model for Acute Kidney Injury Following Surgery of the Aorta |
| title_full | A Novel Predictive Model for Acute Kidney Injury Following Surgery of the Aorta |
| title_fullStr | A Novel Predictive Model for Acute Kidney Injury Following Surgery of the Aorta |
| title_full_unstemmed | A Novel Predictive Model for Acute Kidney Injury Following Surgery of the Aorta |
| title_short | A Novel Predictive Model for Acute Kidney Injury Following Surgery of the Aorta |
| title_sort | novel predictive model for acute kidney injury following surgery of the aorta |
| topic | acute kidney injury macrophage polarization cytokine predictive model aortic surgery |
| url | https://www.imrpress.com/journal/RCM/25/2/10.31083/j.rcm2502054 |
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