Risk factors and early outcomes of acute renal injury after thoracic aortic endograft repair for type B aortic dissection

Postoperative acute kidney injury after thoracic endovascular aortic repair for acute type B aortic dissection

BACKGROUND

Thoracic endovascular aortic repair (TEVAR) has evolved as the standard for treating complicated acute type B aortic dissection (ATBAD). Acute kidney injury (AKI) is a common complication in critically ill patients and is commonly observed in patients with ATBAD. The purpose of the study was to characterize AKI after TEVAR.

METHODS

All patients who underwent TEVAR for ATBAD from 2011 through 2021 were identified using the International Registry of Acute Aortic Dissection. The primary end point was AKI. A generalized linear model analysis was performed to identify a factor associated with postoperative AKI.

RESULTS

A total of 630 patients presented with ATBAD and underwent TEVAR. The indication for TEVAR was complicated ATBAD in 64.3%, high-risk uncomplicated ATBAD in 27.6%, and uncomplicated ATBAD in 8.1%. Of 630 patients, 102 (16.2%) developed postoperative AKI (AKI group) and 528 patients (83.8%) did not (non-AKI group). The most common indication for TEVAR was malperfusion (37.5%). In-hospital mortality was significantly higher in the AKI group (18.6% vs 4%; P < .001). Postoperatively, cerebrovascular accident, spinal cord ischemia, limb ischemia, and prolonged ventilation were more commonly observed in the AKI group. The expected mortality was similar at 2 years between the two groups (P = .51). Overall, the preoperative AKI was observed in 95 (15.7%) in the entire cohort consisting of 60 (64.5%) in the AKI group and 35 (6.8%) in the non-AKI group. A history of CKD (odds ratio, 4.6; 95% confidence interval, 1.5-14.1; P = .01) and preoperative AKI (odds ratio, 24.1; 95% confidence interval, 10.6-55.0; P < .001) were independently associated with postoperative AKI.

CONCLUSIONS

The incidence of postoperative AKI was 16.2% in patients undergoing TEVAR for ATBAD. Patients with postoperative AKI had a higher rate of in-hospital morbidities and mortality than those without. A history of CKD and preoperative AKI were independently associated with postoperative AKI.

Acute Kidney Injury in Patients with Acute Type B Aortic Dissection

OBJECTIVE

Acute kidney injury (AKI) is common in patients with aortic diseases; however, it has not been extensively studied in acute type B aortic dissection (TBAD). AKI is known to be associated with adverse kidney outcomes and premature death. This study investigated the incidence and impact of AKI in patients with acute TBAD.

METHODS

This was a retrospective study including data from two tertiary vascular centres in the UK. Case notes and electronic records were reviewed for consecutive patients presenting with acute symptomatic TBAD. Patients were managed according to a uniform clinical protocol; both patients who underwent surgery and those managed conservatively were included in this analysis. Serum creatinine values were used to calculate the number of patients who developed AKI, based on validated Kidney Disease Improving Global Outcomes definitions. Associations between incidence of AKI, death, and Major Adverse Kidney Events (MAKE; defined as death, dialysis and/or drop in estimated glomerular filtration rate > 25%) were explored.

RESULTS

Overall, 66 (42.6%) of 155 patients developed AKI within one week of presenting with TBAD. Of these, 23 patients (34.8%) had stage 1, 26 patients (39.4%) stage 2, and 17 patients (25.8%) stage 3 AKI. MAKE at 30 and 90 days occurred in 17 (11.0%) and 12 patients (7.7%), respectively. AKI was associated with significantly worse outcomes, with a 24.2% mortality rate in the AKI group compared with 7.8% among those with no AKI (p <.001); this association was also significant in adjusted analyses, both in patients who did and did not undergo surgery.

CONCLUSION

AKI is very common among patients presenting with acute TBAD, even in clinically uncomplicated disease. There was a significant association with mortality and MAKE, whether patients underwent surgery or not. This warrants further investigation to better understand the underlying causes of the AKI and investigate management strategies which may improve outcomes.

Develop ment and validation of a prognostic dynamic nomogram for in-hospital mortality in patients with Stanford type B aortic dissection

Background

This study aimed to identify the risk factors for in-hospital mortality in patients with Stanford type B aortic dissection (TBAD) and develop and validate a prognostic dynamic nomogram for in-hospital mortality in these patients.

Methods

This retrospective study involved patients with TBAD treated from April 2002 to December 2020 at the General Hospital of Northern Theater Command. The patients with TBAD were divided into survival and non-survival groups. The data were analyzed by univariate and multivariate logistic regression analyses. To identify independent risk factors for in-hospital mortality, multivariate logistic regression analysis, least absolute shrinkage, and selection operator regression were used. A prediction model was constructed using a nomogram based on these factors and validated using the original data set. To assess its discriminative ability, the area under the receiver operating characteristic curve (AUC) was calculated, and the calibration ability was tested using a calibration curve and the Hosmer-Lemeshow test. Clinical utility was evaluated using decision curve analysis (DCA) and clinical impact curves (CIC).

Results

Of the 978 included patients, 52 (5.3%) died in hospital. The following variables helped predict in-hospital mortality: pleural effusion, systolic blood pressure ≥160 mmHg, heart rate >100 bpm, anemia, ischemic cerebrovascular disease, abnormal cTnT level, and estimated glomerular filtration rate <60 ml/min. The prediction model demonstrated good discrimination [AUC = 0.894; 95% confidence interval (CI), 0.850-0.938]. The predicted probabilities of in-hospital death corresponded well to the actual prevalence rate [calibration curve: via 1,000 bootstrap resamples, a bootstrap-corrected Harrell's concordance index of 0.905 (95% CI, 0.865-0.945), and the Hosmer-Lemeshow test (χ² = 8.3334, P = 0.4016)]. DCA indicated that when the risk threshold was set between 0.04 and 0.88, the predictive model could achieve larger clinical net benefits than "no intervention" or "intervention for all" options. Moreover, CIC showed good predictive ability and clinical utility for the model.

Conclusion

We developed and validated prediction nomograms, including a simple bed nomogram and online dynamic nomogram, that could be used to identify patients with TBAD at higher risk of in-hospital mortality, thereby better enabling clinicians to provide individualized patient management and timely and effective interventions.

Prediction model of acute kidney injury after different types of acute aortic dissection based on machine learning

Objective

A clinical prediction model for postoperative combined Acute kidney injury (AKI) in patients with Type A acute aortic dissection (TAAAD) and Type B acute aortic dissection (TBAAD) was constructed by using Machine Learning (ML).

Methods

Baseline data was collected from Acute aortic division (AAD) patients admitted to First Affiliated Hospital of Xinjiang Medical University between January 1, 2019 and December 31, 2021. (1) We identified baseline Serum creatinine (SCR) estimation methods and used them as a basis for diagnosis of AKI. (2) Divide their total datasets randomly into Training set (70%) and Test set (30%), Bootstrap modeling and validation of features using multiple ML methods in the training set, and select models corresponding to the largest Area Under Curve (AUC) for follow-up studies. (3) Screening of the best ML model variables through the model visualization tools Shapley Addictive Explanations (SHAP) and Recursive feature reduction (REF). (4) Finally, the pre-screened prediction models were evaluated using test set data from three aspects: discrimination, Calibration, and clinical benefit.

Results

The final incidence of AKI was 69.4% (120/173) in 173 patients with TAAAD and 28.6% (81/283) in 283 patients with TBAAD. For TAAAD-AKI, the Random Forest (RF) model showed the best prediction performance in the training set (AUC = 0.760, 95% CI:0.630–0.881); while for TBAAD-AKI, the Light Gradient Boosting Machine (LightGBM) model worked best (AUC = 0.734, 95% CI:0.623–0.847). Screening of the characteristic variables revealed that the common predictors among the two final prediction models for postoperative AKI due to AAD were baseline SCR, Blood urea nitrogen (BUN) and Uric acid (UA) at admission, Mechanical ventilation time (MVT). The specific predictors in the TAAAD-AKI model are: White blood cell (WBC), Platelet (PLT) and D dimer at admission, Plasma The specific predictors in the TBAAD-AKI model were N-terminal pro B-type natriuretic peptide (BNP), Serum kalium, Activated partial thromboplastin time (APTT) and Systolic blood pressure (SBP) at admission, Combined renal arteriography in surgery. Finally, we used in terms of Discrimination, the ROC value of the RF model for TAAAD was 0.81 and the ROC value of the LightGBM model for TBAAD was 0.74, both with good accuracy. In terms of calibration, the calibration curve of TAAAD-AKI's RF fits the ideal curve the best and has the lowest and smallest Brier score (0.16). Similarly, the calibration curve of TBAAD-AKI's LightGBM model fits the ideal curve the best and has the smallest Brier score (0.15). In terms of Clinical benefit, the best ML models for both types of AAD have good Net benefit as shown by Decision Curve Analysis (DCA).

Conclusion

We successfully constructed and validated clinical prediction models for the occurrence of AKI after surgery in TAAAD and TBAAD patients using different ML algorithms. The main predictors of the two types of AAD-AKI are somewhat different, and the strategies for early prevention and control of AKI are also different and need more external data for validation.

Risk factors of acute kidney injury in patients with Stanford type B aortic dissection involving the renal artery who underwent thoracic endovascular aortic repair

Background

Acute kidney injury (AKI) is one of the most common and serious complications in patients with type B aortic dissection (TBAD). This study aimed at investigating the incidence and risk factors of in-hospital AKI in TBAD patients involving the renal artery who underwent thoracic endovascular aortic repair (TEVAR) only.

Methods

A total of 256 patients who were diagnosed as TBAD combined with renal artery involvement were included in this retrospective study. All patients were divided into the AKI group and the non-AKI group according to the KDIGO criteria. The risk factors for AKI were identified using a multivariate logistic regression model.

Results

A total of 256 patients were included in this study, and the incidence of AKI was 18% (46/256). Patients in the AKI group were more likely to have a higher proportion of the youth, a higher level of body mass index, and a shorter time from onset to admission. Multivariate logistic regression analysis revealed that the youth (age ≤40 years) (OR: 2.853, 95%CI: 1.061–7.668, p = .038) were prone to AKI, and lower estimated glomerular filtration rate (eGFR) (OR: 1.526, per 15-ml/min/1.73 m² decrease, 95%CI: 1.114–2.092; p = .009), higher diastolic blood pressure (DBP) (OR: 1.418, per 10-mmHg increase; 95%CI: 1.070–1.879; p = .015), and fasting blood glucose (FBG) ≥7 mmol/L on admission (OR: 2.592; 95%CI: 1.299–5.174; p = .007) were independent risk factors for AKI.

Conclusions

Higher incidence of AKI had been perceived in this study, most of them were young and middle-aged patients. Renopreventive measures should be considered in those high-risk patients with younger age, lower eGFR, higher DBP, and higher FBG on admission.

Outcomes and risk management in type B aortic dissection patients with acute kidney injury: a concise review

Purpose

Type B aortic dissection is a rare but life-threatening disease. Thoracic endovascular aortic repair (TEVAR) was widely used for Type B aortic dissection patients in the last decade due to the lower mortality and morbidity compared with open chest surgical repair (OCSR). AKI in type B aortic dissection is a well-recognized complication and indicates poor short-term and long-term outcome. The objective of this concise review was to identify the risk factors and the impact of AKI on type B aortic dissection patients.

Methods and results

A literature search was performed using PubMed, Embase, MEDLINE, and Cochrane Library with the search terms ‘type B aortic dissection’ and ‘acute kidney injury’ (AKI), and all English-language literatures published in print or available online from inception through August 2020 were thoroughly reviewed. Studies that reported relative AKI risks and outcomes in type B aortic dissection patient were included. Major mechanisms of AKI in type B aortic dissection included renal hypoperfusion, inflammation response, and the use of contrast medium. Type B aortic dissection patients with AKI significantly had increased hospital stay duration, need of renal replacement therapy, and 30-d and 1-year mortality.

Conclusions

AKI in type B aortic dissection is a well-recognized complication and associated with poor short-term and long-term outcome. Early identification of high-risk patients, early diagnosis of AKI, stabilization of the hemodynamic parameters, avoidance of nephrotoxic drugs, and optimization of the use of contrast agents are the major strategies for the reduction of AKI in type B aortic dissection patients.

Acute Kidney Injury in Asia: Disease Burden

Acute kidney injury (AKI) is a common and critical clinical disorder with non-negligible morbidity and mortality and remains a large public health problem. Asia, as the world's largest and most populous continent, is crucial in eliminating unsatisfactory outcomes of AKI. The diversities in climate, customs, and economic status lead to various clinical features of AKI across Asia. In this review, we focus on the epidemiologic data and clinical features of AKI in different Asian countries and clinical settings, and we show the huge medical and economic burden of AKI in Asian countries. Drugs and sepsis are the most common etiologies for AKI, however, an adequate surveillance system has not been well established. There is significant undertreatment of AKI in many regions, and medical resources for renal replacement therapy are not universally available. Although substantial improvement has been achieved, health care for AKI still needs improvement, especially in developing regions.

Contrast-Induced Kidney Nephropathy in Thoracic Endovascular Aortic Repair: A 2-Year Retrospective Study in 470 Patients

We identified changes in renal function in patients who underwent thoracic endovascular aortic repair (TEVAR) and the factors that may influence renal function. Information on 470 consecutive patients was collected. Kidney function and contrast volume were recorded. Unpaired t test, Spearman correlation, and logistic regression were used for statistical analysis. A Kaplan-Meier curve helped clarify our follow-up findings. Mean contrast volume was 90.5 ± 21.2 mL. The change in serum creatinine was significantly correlated with (1) preexisting renal pathology (P = .033) and (2) aortic dissection (AD) involving the renal arteries (P = .019). The change in serum urea nitrogen (ΔBUN) was only significantly correlated with AD involving the renal arteries (P = .0348). Contrast volume (P = .036, odds ratio = 1.010, 95% confidence interval: 1.001-1.019) was a risk factor for contrast-induced nephropathy (CIN) after TEVAR. Survival rates and renal failure rates among no CIN, CIN, and CIN-acute kidney injury groups at longest 27 months follow-up were significantly different. Creatinine and BUN were generally elevated post-TEVAR. Contrast-induced nephropathy post-TEVAR may correlate with renal comorbidities and renal artery involvement. Contrast volume is risk factor for CIN after TEVAR. More attention needs to be paid to patient renal function during follow-up.