1. Introduction

Acute kidney injury (AKI) is a common complication after cardiac surgery [1, 2]. Previous studies have reported that the risk of AKI after aortic arch surgery is significantly higher than that of other types of cardiac surgery [3]. Acute type A aortic dissection (AAAD) is a cardiovascular emergency with acute onset and difficult rescue. Once aortic rupture occurs, the mortality rate is extremely high [4]. At present, the only effective treatment for AAAD is surgery, but because of the complexity and difficulty of surgical operation, there are many complications after operation and the prognosis is poor [5]. It has been reported that the probability of AKI after AAAD surgery is as high as 42% [3], and severe AKI may increase hospital mortality by 3–8 times [6]. Ascending aortic replacement is widely regarded as the first choice for the treatment of AAAD [7]. For the treatment of aortic arch disease, Sun et al. invented a surgical method according to the characteristics of aortic dissection and named it Sun’s procedure, in which the most critical procedure is four-branched artificial vascular total arch replacement and descending aortic frozen trunk stent implantation [8]. At present, there have been many studies on the independent risk factors of AKI after this kind of operation [9]. In order to simplify the steps of aortic arch reconstruction, our center has improved the surgical procedure of aortic arch treatment and invented a modified triple-branched stent graft (MTBSG) to replace four-branch artificial blood vessels. This new stent is implanted during the operation to repair the aortic arch, and it has been proved to be a safe and effective procedure after a long period of clinical practice [10–12]. Unfortunately, there is no research on the risk factors of AKI after MTBSG implantation in the treatment of AAAD, let alone quantitative risk assessment of postoperative AKI, which makes the AKI unpredictable and the intervention lagging behind. Therefore, finding the predictors of AKI after MTBSG implantation is helpful for us to carry out early intervention so as to improve the prognosis of the operation. The purpose of this study is to explore the risk factors of AKI after MTBSG implantation and to establish a competitive risk nomogram model based on the results of the above analysis to predict the degree of risk in order to guide clinical treatment.

2. Materials and Methods

2.1. Patients

The perioperative clinical data of AAAD patients who underwent emergency surgery in our center from January 2018 to December 2020 were collected retrospectively. In this study, the inclusion criteria were (1) acute type A aortic dissection confirmed by thoracic aortic angiography or color Doppler echocardiography; (2) emergency operation within 12 hours after admission; and (3) ascending aortic replacement combined with modified triple-branched stent graft implantation. The exclusion criteria were (1) severe renal insufficiency or chronic kidney disease before operation and (2) death within 24 hours after operation. This study strictly abides by the Helsinki Declaration (Figure 1).

3. Results

3.2. The Selection of Risk Factors and Model Performance Test of Nomograms

Univariate analysis showed that there were significant differences in age, preoperative shock, malperfusion syndrome, D-dimer, CR, CPB time, and amount of RBC transfusion (Table 3). These variables were included in multivariate logistic analysis, and the results showed that age (OR: 1.053; 95% CI: 1.015,1.092; P = 0.006), malperfusion syndrome (OR: 11.224, 95% CI: 2.474, 50.920; P = 0.002), CR (OR: 1.016, 95% CI: 1.005, 1.027; P = 0.004), CPB time (OR: 1.009, 95% CI: 1.001, 1.016; P = 0.022), and amount of RBC transfusion (OR: 1.676, 95% CI: 1.403, 2.000; P = 0.000) were independent risk factors for AKI after MTBSG implantation (Table 4).

Table 3. Univariate analysis of risk factors for AKI.

Index	OR	95% CI	P value
Age (years)	1.047	1.018, 1.078	0.002
Shock (n, %)	2.738	1.202, 6.233	0.016
Malperfusion syndrome (n, %)	16.276	4.579, 57.856	0.000
D-dimer (μg/mL)	1.048	1.011, 1.087	0.010
CR (μmol/L)	1.013	1.004, 1.022	0.006
Cardiopulmonary bypass time (min)	1.010	1.005, 1.016	0.000
Amount of RBC transfusion (U)	1.654	1.410, 1.940	0.000

Table 4. Multivariate analysis of risk factors for AKI.

Item	OR	95% CI	P value
Age (years)	1.053	1.015, 1.092	0.006
Malperfusion syndrome (n, %)	11.224	2.474, 50.920	0.002
CR (μmol/L)	1.016	1.005, 1.027	0.004
Cardiopulmonary bypass time (min)	1.009	1.001, 1.016	0.022
Amount of RBC transfusion (U)	1.676	1.403, 2.000	0.000

We set up a nomogram prediction model based on the factors of AKI obtained by multivariate logistic regression analysis and the contribution weight of each variable. The risk of AKI after MTBSG implantation is determined by the total score of the risk factors at the top of the nomogram (Figure 2). The ROC curve is drawn according to the risk score and clinical characteristics. The results show that the AUC is 0.854 (95% CI = 0.8041∼0.9039) (Figure 3). We also used the DCA curve and CIC curve to evaluate the net benefit of intervention based on the nomogram model on patients with AKI. The results show that the nomogram model in this study has a good benefit in predicting the occurrence of AKI after MTBSG implantation (Figures 4 and 5). We also use the calibration curve to evaluate the difference between the predicted results of the nomogram model and the actual results. The results show that the calibration curve of the model is close to the diagonal, so it is considered that the predicted results of the nomogram model in this study are in satisfactory consistency with the actual results (Figure 6). The nomogram model of AKI after MTBSG implantation was verified by bootstrap resampling which indicated that the model had good discrimination.

3.3. Kaplan–Meier Survival Curves and Cumulative Hazard Curves

Kaplan–Meier estimates of the impact of postoperative AKI on patients survival. Our results show that the long-term survival rate of patients in AKI group is significantly different from that in non-AKI group. With the increase of time, the survival rate and survival time of patients in AKI group decreased significantly, and the survival risk increased significantly (Figures 7 and 8).

4. Discussion

With the progress of medical treatment, the surgical treatment of AAAD is also more diversified. It has been proved to be a safe and effective surgical method to repair the aortic arch by MTBSG implantation [10–12, 15, 16]. However, there is no research on the risk factors of AKI after MTBSG implantation. AKI after AAAD is a common and fatal complication [1, 2], which significantly increases the risk of death in hospital and the prognosis is poor [5]. Therefore, we believe that early identification of risk factors for AKI after MTBSG implantation is of great significance to reduce the incidence of AKI and improve the prognosis of patients.

In this study, the incidence of AKI after MTBSG implantation was 29.13%, which was roughly the same as previous studies [3]. Through multivariate analysis, we determined the independent risk factors of AKI after MTBSG implantation and, combined with clinical practice, developed a practical and novel nomogram model to predict the risk of AKI after MTBSG implantation. The nomogram model was verified by ROC curve, DCA curve, CIC curve calibration curve, and bootstrap verification.

Age, malperfusion syndrome, serum CR, CPB time, and the amount of RBC transfusion were identified as independent risk factors for AKI after MTBSG implantation. Previous studies have shown that elderly patients have a higher risk of developing AKI after surgery, which is consistent with our findings [17]. With the increase of age, the renal blood perfusion of elderly patients decreased, and the regulatory response of renal vessels to vasodilation factor also decreased [18], so the ability of kidney to adapt to hemodynamic changes became worse and the tolerance to ischemic injury decreased [19]. At the same time, due to the deterioration of renal function, elderly patients are more likely to be exposed to renal damage drugs such as diuretics or contrast media due to certain complications or examinations. Therefore, in some elderly patients with AAAD, we should pay more attention to the protection of renal function before and during operation and try to avoid the use of drugs that may cause renal function damage.

Previous studies have found that the increase of preoperative CR level is an independent risk factor for postoperative AKI. The increase of preoperative CR level is closely related to preoperative kidney injury [20], and any preoperative kidney injury will affect the recovery of postoperative renal function and increase the risk of AKI. In our study, the baseline level of CR in patients with AKI increased significantly before operation, which made the kidney less tolerant to surgery. In addition, the hemodynamic instability, hypoxic injury, and inflammation of the kidney after operation would further promote the occurrence of AKI [21]. Most preoperative kidney injuries are caused by malperfusion syndrome [22], which is a serious complication of AAAD. Poor renal perfusion is considered to be the most important risk factor for AKI [21], which is confirmed by our study. Therefore, we should be more alert to the patient with preoperative imaging suggested the dissection involving the renal artery, and early reperfusion treatment is helpful to improve the prognosis.

Cardiopulmonary bypass support is a necessary condition for cardiovascular surgery, but its nonpulsatile advective blood flow is a nonphysiological state. Long-term cardiopulmonary bypass will aggravate the destruction of blood components and promote the release of inflammatory factors into the blood [23]. Roh et al. reported that the risk of postoperative AKI in patients with CPB time >180 min was 4 times higher than that in patients with CPB time <120 min [24]. Compared with conventional cardiac surgery, AAAD surgery needs to undergo DHCA, and a large change in temperature will further damage renal function. CPB time in our nomogram is a risk factor for postoperative AKI, which is consistent with previous literature reports.

In recent years, the risk of blood transfusion and the incidence of AKI have been the focus of research, but the relationship between them has not been clarified. Some studies have shown that the volume of blood transfusion is related to the high incidence of AKI [25–27], which is similar to our research results. The results of a nonrandomized trial by Koch et al. showed that the increase of RBC transfusion significantly increased the incidence of complications and mortality in patients undergoing simple coronary artery bypass grafting surgery, which may be related to T cell-related immune function damage [28]. However, some studies have also reported that there is no direct relationship between AKI and blood transfusion, which may be due to the heterogeneity and insufficient number of samples in the study. In cardiovascular surgery, acute bleeding is a common intraoperative emergency, so transfusion of RBC to supplement hemoglobin is a common procedure in surgery. With the loss of blood, the content of hemoglobin will be significantly reduced, which will affect the oxygen carrying capacity of blood and then affect the oxygen supply of kidney tissue, resulting in hypoxic injury. At the same time, the stored red blood cells may be deformed and hemolyzed during storage, and the infusion of RBC may increase the accumulation of free hemoglobin and iron, which have nephrotoxicity and will further aggravate kidney dysfunction [29–31]. Therefore, by reducing the amount of RBC transfusion, the incidence of AKI and related transfusion complications may decrease.

Hypothermic circulatory arrest (HCA) is a necessary step in repairing the aortic arch, which is often considered as one of the factors that can affect renal function after surgery [32]. There is still controversy regarding the direct relationship between intraoperative HCA and postoperative AKI. In a study by Vekstein et al. [33], it was found that the degree of systemic hypothermia was not associated with the incidence or severity of AKI in patients undergoing proximal aortic surgery, including arch replacement requiring cardiopulmonary bypass. However, further prospective research is needed to validate this conclusion. In the study conducted by Arnaoutakis et al. [34], the results also indicated that, compared to DHCA, moderate hypothermic circulatory arrest (MHCA) does not result in worse renal function. Therefore, most studies currently suggest that the potential risk factor affecting postoperative AKI is the duration of HCA, rather than the degree of hypothermia. In our center, the application of modified triple-branched stent grafts has greatly simplified the complex arch reconstruction procedure, which has significantly reduced the duration of DHCA during surgery for patients undergoing total arch repair for AAAD. This is beneficial in minimizing the impact of HCA on overall organ function.

Our results also found that the occurrence of AKI after operation will not only prolong the length of stay and increase the cost of hospitalization but also affect the prognosis of patients and increase the risk of hospital death. Therefore, it is very important to establish a visual risk prediction model. The nomogram established in this study can be used to individually predict the risk of AKI after MTBSG implantation and quantify the risk factors of AKI. The higher the score of each item in the nomogram model, the greater the risk of AKI. The ability to predict the risk of AKI can help identify high-risk patients and make appropriate clinical decisions, effectively grasp the timing of continuous renal replacement therapy, avoid invasive treatment operations as far as possible, and maximize the benefits of treatment.

There are several limitations to our study. Firstly, as a single-center retrospective study, there may be inherent selection bias associated with retrospective research. Secondly, due to the excellent efficacy and favorable clinical outcomes of the modified triple-branched stent graft, the majority of AAAD patients in our center have undergone the placement of a modified triple-branched stent graft implantation during total arch replacement. The sample size of cases using other arch surgical methods was too small and therefore not included in this study; this may have an impact on the applicability of the model. Finally, because of the limited sample size from a single center, lack of multicenter data hinders further external validation of the model and its clinical applicability needs further exploration. Therefore, before final application in clinical practice, large-scale multicenter prospective randomized controlled trials should be conducted, and reliable external verification of the model should be carried out to evaluate its usefulness.

Ethical Approval

This study was approved by the Ethics Committee of the affiliated Union Hospital of Fujian Medical University.

Consent

Since this is a retrospective analysis of medical records, the need for informed consent was abandoned.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

The design concept was put forward by FX, LX, JH, QW, YH, and LC. FX and LX were responsible for data collection and input. YH and LC were responsible for data processing and icon drawing. JH, QW, and XL were responsible for typesetting and language censorship. All the co-authors were involved in the preparation of the manuscript. All co-authors reviewed and approved the final version of the manuscript. LC and YH contributed equally to this work.