Nie Jing, Qi Shengyao
School of Medicine, Tongji University, Shanghai, China.
School of Life Sciences and Technology, Tongji University, Shanghai, China.
J Investig Med. 2025 Jun 3:10815589251348930. doi: 10.1177/10815589251348930.
Acute kidney injury (AKI) represents a major cause of death among patients with sepsis. While recent evidence suggests that albumin-corrected anion gap (ACAG) might serve as an early indicator of AKI, its prognostic capabilities require further investigation. We conducted a retrospective analysis of critical care data from the Medical Information Mart for Intensive Care IV electronic health record repository. Restricted cubic splines (RCSs) and Cox proportional hazards models were employed to quantify ACAG's association with AKI occurrence and in-hospital mortality. Kaplan-Meier survival analyses were performed to compare outcomes across ACAG-based groups, and subgroup analyses were carried out to evaluate the robustness of these associations and potential interactions between variables. Among 19,445 included patients, elevated ACAG emerged as a strong predictor of AKI (hazard ratio, HR (95% confidence interval, CI): 16.75 (14.50, 19.75), p < 0.001) and in-hospital mortality (HR (95% CI): 16.75 (14.50, 19.75), p < 0.001). RCS analysis showed a predominantly linear relationship between ACAG and clinical outcomes (AKI: p for nonlinear = 0.059; mortality: p for nonlinear = 0.794), with 17 emerging as a critical ACAG threshold value. Significant interactions were identified between ACAG and factors such as sex, age, and chronic kidney disease status. Our findings demonstrate ACAG's robust ability to predict adverse outcomes in sepsis, particularly regarding kidney function deterioration and survival. These findings highlight the potential clinical utility of ACAG as a prognostic marker to guide early therapeutic interventions.
急性肾损伤(AKI)是脓毒症患者死亡的主要原因。虽然最近的证据表明,白蛋白校正阴离子间隙(ACAG)可能是AKI的早期指标,但其预后能力仍需进一步研究。我们对重症监护医学信息集市IV电子健康记录库中的重症监护数据进行了回顾性分析。采用限制性立方样条(RCS)和Cox比例风险模型来量化ACAG与AKI发生及住院死亡率之间的关联。进行Kaplan-Meier生存分析以比较基于ACAG分组的结果,并进行亚组分析以评估这些关联的稳健性以及变量之间的潜在相互作用。在纳入的19445例患者中,ACAG升高是AKI(风险比,HR(95%置信区间,CI):16.75(14.50,19.75),p<0.001)和住院死亡率(HR(95%CI):16.75(14.50,19.75),p<0.001)的有力预测指标。RCS分析显示ACAG与临床结局之间主要呈线性关系(AKI:非线性p=0.059;死亡率:非线性p=0.794),17被确定为关键的ACAG阈值。ACAG与性别、年龄和慢性肾脏病状态等因素之间存在显著的相互作用。我们的研究结果表明ACAG在预测脓毒症不良结局方面具有强大能力,尤其是在肾功能恶化和生存方面。这些发现凸显了ACAG作为预后标志物指导早期治疗干预的潜在临床应用价值。