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Objective <p>To explore the independent risk factors for acute kidney injury (AKI) and continuous renal replacement therapy (CRRT) after surgery for acute Stanford type A aortic dissection (ATAAD).</p> Methods <p>A single-center retrospective observational cohort study was performed on the clinical data of 420 patients who underwent ATAAD surgery at our hospital from January 2018 to December 2024. Patients were grouped according to the occurrence of postoperative AKI and the use of CRRT. Univariate and multivariate analyses were used to identify independent risk factors, and predictive models were constructed accordingly.</p> Results <p>A total of 420 patients with acute type A aortic dissection were enrolled, of whom 128 (30.48%) developed postoperative acute kidney injury (AKI) and 76 (18.10%) required continuous renal replacement therapy (CRRT). Elevated AIP and RAR were independently associated with an increased risk of postoperative AKI (OR = 9.36, 95% CI 3.28–26.70, <i>P</i> &lt; 0.001; OR = 3.05, 95% CI 1.59–5.85, <i>P</i> &lt; 0.001). Furthermore, elevated AIP was also an independent risk factor for CRRT (OR = 19.89, 95% CI 4.79–82.65, <i>P</i> &lt; 0.001). Subgroup analysis confirmed that the predictive effects of AIP and RAR for AKI were stable and not modified by cardiopulmonary bypass time (all <i>P</i> for interaction &gt; 0.05). The prediction model for AKI (AUC = 0.93) and CRRT (AUC = 0.94) showed excellent discrimination, calibration, and clinical net benefit. Adding AIP and RAR to conventional risk factors significantly improved incremental predictive value for AKI (ΔAUC = 0.0204, <i>P</i> &lt; 0.001; continuous NRI = 0.5689, <i>P</i> &lt; 0.001; IDI = 0.0466, <i>P</i> &lt; 0.001), and adding AIP significantly improved predictive performance for CRRT (ΔAUC = 0.0164, <i>P</i> &lt; 0.001; continuous NRI = 0.5979, <i>P</i> &lt; 0.001; IDI = 0.0357, <i>P</i> &lt; 0.001).</p> Conclusion <p>Preoperative elevation of AIP and RAR are independent risk factors for postoperative AKI in patients with ATAAD, among which AIP has higher predictive value for postoperative CRRT, which serves as a clinically driven secondary management outcome rather than a purely physiological endpoint. We present these predictive models as an exploratory derivation study. While they show promising apparent performance, they require independent external validation before being considered as actionable tools for clinical management.</p>

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Association between preoperative atherogenic index of plasma, ratio of red blood cell distribution width to serum albumin, and postoperative acute kidney injury, and construction of predictive models in patients with acute Stanford type A aortic dissection: a single-center retrospective observational cohort study

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  • 发表日期：

    2026年5月25日

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  • Xiangtao Ma,
  • Qin Zhao,
  • Hansong Liu,
  • Wei Feng,
  • Jia Liu

摘要

Objective

To explore the independent risk factors for acute kidney injury (AKI) and continuous renal replacement therapy (CRRT) after surgery for acute Stanford type A aortic dissection (ATAAD).

Methods

A single-center retrospective observational cohort study was performed on the clinical data of 420 patients who underwent ATAAD surgery at our hospital from January 2018 to December 2024. Patients were grouped according to the occurrence of postoperative AKI and the use of CRRT. Univariate and multivariate analyses were used to identify independent risk factors, and predictive models were constructed accordingly.

Results

A total of 420 patients with acute type A aortic dissection were enrolled, of whom 128 (30.48%) developed postoperative acute kidney injury (AKI) and 76 (18.10%) required continuous renal replacement therapy (CRRT). Elevated AIP and RAR were independently associated with an increased risk of postoperative AKI (OR = 9.36, 95% CI 3.28–26.70, P < 0.001; OR = 3.05, 95% CI 1.59–5.85, P < 0.001). Furthermore, elevated AIP was also an independent risk factor for CRRT (OR = 19.89, 95% CI 4.79–82.65, P < 0.001). Subgroup analysis confirmed that the predictive effects of AIP and RAR for AKI were stable and not modified by cardiopulmonary bypass time (all P for interaction > 0.05). The prediction model for AKI (AUC = 0.93) and CRRT (AUC = 0.94) showed excellent discrimination, calibration, and clinical net benefit. Adding AIP and RAR to conventional risk factors significantly improved incremental predictive value for AKI (ΔAUC = 0.0204, P < 0.001; continuous NRI = 0.5689, P < 0.001; IDI = 0.0466, P < 0.001), and adding AIP significantly improved predictive performance for CRRT (ΔAUC = 0.0164, P < 0.001; continuous NRI = 0.5979, P < 0.001; IDI = 0.0357, P < 0.001).

Conclusion

Preoperative elevation of AIP and RAR are independent risk factors for postoperative AKI in patients with ATAAD, among which AIP has higher predictive value for postoperative CRRT, which serves as a clinically driven secondary management outcome rather than a purely physiological endpoint. We present these predictive models as an exploratory derivation study. While they show promising apparent performance, they require independent external validation before being considered as actionable tools for clinical management.