Early postoperative acute kidney injury prediction in patients with acute type A aortic dissection

Acute kidney injury (AKI) is a frequent and serious complication following surgery for acute type A aortic dissection (AAD), often leading to delayed treatment and poor outcomes. This multicenter study developed and validated a predictive nomogram for early postoperative AKI in 1,211 AAD patients. Using logistic regression, independent risk factors were identified: age, hypertension, preoperative shock, and cardiopulmonary bypass time. The model demonstrated robust performance, with area under the curve values of 0.749 and 0.753 in internal and external validation cohorts, respectively. Decision curve analysis confirmed the nomogram's clinical utility, providing superior net benefit over postoperative creatinine levels when the predicted AKI risk exceeds 50%. This tool enables early identification of high-risk patients, facilitating timely interventions to improve perioperative management and outcomes in this critical surgical population.

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Publication Details

Journal
iScience
Published
2025-11-27
DOI
https://doi.org/10.1016/j.isci.2025.114222
Citations
1
Primary Topic
Aortic Disease and Treatment Approaches
Type
article
Field-Weighted Citation Impact
1.52
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article

Early postoperative acute kidney injury prediction in patients with acute type A aortic dissection

Huihui Xue, Ling Chen, Huaijian Zhang, Liangwan Chen et al.
1 citations
iScience
Aortic Disease and Treatment Approaches
1.52
article

Early postoperative acute kidney injury prediction in patients with acute type A aortic dissection

Huihui Xue, Ling Chen, Huaijian Zhang, Liangwan Chen, Zhihuang Qiu, Yichao Pan
article en
1 citations

Abstract

Acute kidney injury (AKI) is a frequent and serious complication following surgery for acute type A aortic dissection (AAD), often leading to delayed treatment and poor outcomes. This multicenter study developed and validated a predictive nomogram for early postoperative AKI in 1,211 AAD patients. Using logistic regression, independent risk factors were identified: age, hypertension, preoperative shock, and cardiopulmonary bypass time. The model demonstrated robust performance, with area under the curve values of 0.749 and 0.753 in internal and external validation cohorts, respectively. Decision curve analysis confirmed the nomogram's clinical utility, providing superior net benefit over postoperative creatinine levels when the predicted AKI risk exceeds 50%. This tool enables early identification of high-risk patients, facilitating timely interventions to improve perioperative management and outcomes in this critical surgical population.

iScienceVol. 29(1)
Fujian Medical University (CN), First Affiliated Hospital of Xiamen University (CN), Zhangzhou Municipal Hospital of Fujian Province (CN), Education Department of Fujian Province (CN), Union Hospital (CN)
Openalex Percentile: Top 12%
Aortic Disease and Treatment Approaches
1.52
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