Предиктивна вредност цистатина Ц за постоперативну акутну повреду бубрега акутне дисекције аорте типа А
Sažetak
Objective
The research aimed to provide an initial prediction of postoperative acute kidney injury in patients with acute type A aortic dissection undergoing total aortic arch replacement combined with frozen elephant trunk stent implantation by investigating the association between preoperative cystatin C levels and postoperative AKI, while incorporating relevant risk factors into the analysis.
Methods
This study employed a case-control design, involving 202 patients from a single center between January 2018 and December 2019. The participants were categorized into case group (n=73) and control group (n=129).
Results
The univariate analysis indicated preoperative history of hypertension (P=0.013), white blood cell count (P<0.001), and serum creatinine (P<0.001), blood urea nitrogen (P<0.001), cystatin C (P<0.001) were significant statistically. Duration of mechanical ventilation (P<0.001), Duration of ICU admission (P<0.001), postoperative acute respiratory failure (P=0.018), acute cerebrovascular events (P=0.042), death within 30 days after operation (P<0.001) were different statistically between groups. The preoperative variables above were enrolled into the multivariate analysis. The result indicated cystatin C (95%CI, 3.811-34.953, P=0.001), white blood cell count (95%CI, 1.013-1.242, P=0.028) and history of hypertension (95%CI, 1.188-7.990, P=0.021) might be independent risk factors. Survival analyses indicated cystatin C level was related to postoperative AKI statistically both in crude and subgroup analyses. The clinical prediction model was developed based on the multivariate analysis. The internal validation demonstrated that the concordance statistics were 0.804 (training set) and 0.609 (validation set).
Conclusions
The preoperative cystatin C level was identified as a predictor of postoperative acute kidney injury. Moreover, integrating preoperative cystatin C with other clinical risk factors could improve the prediction of postoperative acute kidney injury.
Sva prava zadržana (c) 2025 Shouming Li, Xin Zhao, Zhenhua Wang, Han Song, Yongmin Liu
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