Abstract
BACKGROUND: The impact of adjusting intraoperative mean arterial pressure (MAP) management strategies on early detection and prevention of acute kidney injury (AKI) after Type A acute aortic dissection (TA-AAD) repair has not been elucidated. This study sought to investigate the association between different degrees of hypotension exposure and stage 3 AKI, and examine how intraoperative time-series dynamic variables influence the performance of risk stratification models. METHODS: We analyzed intraoperative data and divided 336 adult patients into groups based on MAP below different thresholds (< 65, 60, 55, 50 mmHg). Logistic regression algorithms were used to identify and screen for predictors other than blood pressure (BP) features and develop initial model. Hypotensive exposure indicators, including cumulative time and area under the curve below a certain MAP threshold, were considered for confounding correction. Subsequently all independent predictors were incorporated to develop upgraded models. Predictive performance was assessed by area under the receiver operating characteristic curve (AUROC) and calibration curves. RESULTS: 227 patients (67.6 %) developed postoperative AKI, including 114 (33.9 %) stage 1, 54 (16.1 %) stage 2, and 59 (17.6 %) stage 3. Multivariate logistic regression analysis identified preoperative serum creatinine (odds ratio [OR] = 1.007 [95 % CI 1.002-1.015], P = 0.047), operation duration (OR = 1.007 [95 % CI, 1.002-1.012], P = 0.008) and intraoperative urine output (OR = 0.576 [95 % CI, 0.417-0.768], P < 0.001) as independent predictors of stage 3 AKI. After confounding correction, hypotensive exposure indicators were significant at all four thresholds, and ORs increased with decreasing thresholds. Integrating BP features yielded eight upgraded models with AUROC ranging from 0.797 to 0.805. CONCLUSIONS: With a worsening degree of intraoperative hypotension, i.e., lower absolute MAP thresholds and longer exposure times, the odds of stage 3 AKI risk after TA-AAD repair increased. Incorporating BP time-series variables into models could improve the accuracy of early prediction, while the two presentations of hypotension features yield scarcely any difference in predictive outcomes.