Association between preoperative serum myoglobin and acute kidney injury after Stanford Type A aortic dissection surgery

Prediction of acute kidney injury incidence following acute type A aortic dissection surgery with novel biomarkers: a prospective observational study

BACKGROUND

Acute kidney injury (AKI) is a prevalent complication following acute type A aortic dissection (ATAAD) surgery and is closely associated with unfavorable prognostic outcomes. Hence, the development of a robust and efficient diagnostic approach to identify high-risk patients is of paramount importance.

METHODS

We conducted a prospective study involving 328 patients who underwent ATAAD surgery at our institution, comprising three distinct cohorts. In addition, 52 patients undergoing alternative cardiopulmonary surgeries and 37 healthy individuals were enrolled as control groups. Employing proteomic analysis, we initially identified plasma proteins potentially linked to AKI occurrence within the plasma proteomic cohort. Subsequent validation was performed in an independent cohort. Utilizing predictors derived from multivariate logistic regression analysis, a nomogram was meticulously formulated and its efficacy was validated in the model construction cohort.

RESULTS

Proteomics revealed significant elevation of plasma levels of S100A8/A9, pentraxin 3 (PTX3), and chitinase 3-like 1 (CHI3L1) immediately post-surgery in patients who developed ATAAD surgery-associated AKI (ASA-AKI). Receiver operating characteristic (ROC) curves demonstrated impressive predictive performance of S100A8/A9, PTX3, and CHI3L1 at 0 h post-surgery, yielding area under the curve (AUC) values of 0.823, 0.786, and 0.803, respectively, for ASA-AKI prediction. Furthermore, our findings exhibited positive correlations between plasma levels of S100A8/A9, PTX3, CHI3L1, and urinary neutrophil gelatinase-associated lipocalin (NGAL) at 0 h post-surgery, along with correlations between plasma S100A8/A9, CHI3L1 levels, and the Cleveland Clinic score. A logistic regression model incorporating plasma S100A8/A9, PTX3, CHI3L1 levels, urinary NGAL levels, and the Cleveland Clinic score facilitated the construction of a predictive nomogram for ASA-AKI. This nomogram demonstrated robust discriminative ability, achieving an AUC of 0.963 in the model construction cohort.

CONCLUSIONS

Our study underscored the augmentation of plasma S100A8/A9, PTX3, and CHI3L1 levels immediately post-surgery in patients developing ASA-AKI. The incorporation of these three biomarkers, in conjunction with the Cleveland Clinic score and NGAL, into a nomogram demonstrated commendable predictive efficacy. This presents a practical tool for identifying patients at an elevated risk of AKI following ATAAD surgery.

The predictive values of monocyte-lymphocyte ratio in postoperative acute kidney injury and prognosis of patients with Stanford type A aortic dissection

Objectives

Postoperative acute kidney injury (pAKI) is a serious complication of Stanford type A aortic dissection (TAAD) surgery, which is significantly associated with the inflammatory response. This study aimed to explore the relationship between blood count-derived inflammatory markers (BCDIMs) and pAKI and to construct a predictive model for pAKI.

Methods

Patients who underwent TAAD surgery were obtained from our center and the Medical Information Mart for Intensive Care (MIMIC)-IV database. The differences in preoperative BCDIMs and clinical outcomes of patients with and without pAKI were analyzed. Logistic regression was used to construct predictive models based on preoperative BCDIMs or white cell counts (WCCs). The performance of the BCDIMs and WCCs models was evaluated and compared using the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), Hosmer-Lemeshow test, calibration plot, net reclassification index (NRI), integrated discrimination improvement index (IDI), and decision curve analysis (DCA). The Kaplan-Meier curves were applied to compare the survival rate between different groups.

Results

The overall incidence of pAKI in patients who underwent TAAD surgery from our center was 48.63% (124/255). The presence of pAKI was associated with longer ventilation time, higher incidence of cerebral complications and postoperative hepatic dysfunction, and higher in-hospital mortality. The results of the logistic regression indicated that the monocyte-lymphocyte ratio (MLR) was an independent risk factor for pAKI. The BCDIMs model had good discriminating ability, predictive ability, and clinical utility. In addition, the performance of the BCDIMs model was significantly better than that of the WCCs model. Analysis of data from the MIMIC-IV database validated that MLR was an independent risk factor for pAKI and had predictive value for pAKI. Finally, data from the MIMIC-IV database demonstrated that patients with a high MLR had a significantly poor 28-day survival rate when compared to patients with a low MLR.

Conclusion

Our study suggested that the MLR is an independent risk factor for pAKI. A predictive model based on BCDIMs had good discriminating ability, predictive ability, and clinical utility. Moreover, the performance of the BCDIMs model was significantly better than that of the WCCs model. Finally, a high MLR was significantly associated with poor short-term survival of patients who underwent TAAD surgery.