Association Between Glycemic Variability and Persistent Acute Kidney Injury After Noncardiac Major Surgery: A Multicenter Retrospective Cohort Study.

Siyu Kong,Ke Ding,Huili Jiang,Fan Yang,Chen Zhang,Liu Han,Yali Ge,Lihai Chen,Hongwei Shi,Jifang Zhou
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Abstract

BACKGROUND While the relationship between glycemic variability (GV) and acute kidney injury (AKI) has been a subject of interest, the specific association of GV with persistent AKI beyond 48 hours postoperative after noncardiac surgery is not well-established. METHODS This retrospective cohort study aimed to describe the patterns of different GV metrics in the immediate 48 hours after noncardiac surgery, evaluate the association between GV indices and persistent AKI within the 7-day postoperative window, and compare the risk identification capabilities of various GV for persistent AKI. A total of 10,937 patients who underwent major noncardiac surgery across 3 medical centers in eastern China between January 2015 and September 2023 were enrolled. GV was characterized using the coefficient of variations (CV), mean amplitude of glycemic excursions (MAGE), and the blood glucose risk index (BGRI). Multivariable logistic regression was used to examine the relationship between GV and AKI. Optimal cutoff values for GV metrics were calculated through the risk identification models, and an independent cohort from the INformative Surgical Patient dataset for Innovative Research Environment (INSPIRE) database with 7714 eligible cases served to externally validate the risk identification capability. RESULTS Overall, 274 (2.5%) of the 10,937 patients undergoing major noncardiac surgery met the criteria of persistent AKI. Higher GV was associated with an increased risk of persistent AKI (CV: odds ratio [OR] = 1.26, 95% confidence interval [CI], 1.08-1.46; MAGE: OR = 1.31, 95% CI, 1.15-1.49; BGRI: OR = 1.18, 95% CI, 1.08-1.29). Compared to models that did not consider glycemic factors, MAGE and BGRI independently contributed to predicting persistent AKI (MAGE: areas under the curve [AUC] = 0.768, P = .011; BGRI: AUC = 0.764, P = .014), with cutoff points of 3.78 for MAGE, and 3.02 for BGRI. The classification of both the internal and external validation cohorts using cutoffs demonstrated good performance, achieving the best AUC values of 0.768 for MAGE in the internal cohort and 0.777 for MAGE in the external cohort. CONCLUSIONS GV measured within 48 hours postoperative period is an independent risk factor for persistent AKI in patients undergoing noncardiac surgery. Specific cutoff points can be used to stratify at-risk patients. These findings indicate that stabilizing GV may potentially mitigate adverse kidney outcomes after noncardiac surgery, highlighting the importance of glycemic control in the perioperative period.
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非心脏大手术后血糖变化与持续急性肾损伤之间的关系:一项多中心回顾性队列研究。
背景虽然血糖变异性(GV)与急性肾损伤(AKI)之间的关系一直备受关注,但 GV 与非心脏手术后 48 小时后的持续性 AKI 的具体关系尚未得到充分证实。方法这项回顾性队列研究旨在描述非心脏手术后 48 小时内不同 GV 指标的模式,评估 GV 指数与术后 7 天内持续性 AKI 之间的关联,并比较各种 GV 对持续性 AKI 的风险识别能力。2015年1月至2023年9月期间,华东地区3家医疗中心共纳入了10937名接受非心脏大手术的患者。使用变异系数(CV)、血糖偏移平均幅度(MAGE)和血糖风险指数(BGRI)对血糖风险进行表征。多变量逻辑回归用于研究 GV 与 AKI 之间的关系。通过风险识别模型计算出了 GV 指标的最佳临界值,并从创新研究环境手术患者信息数据集 (INSPIRE) 数据库的 7714 个合格病例中挑选出一个独立队列,对风险识别能力进行外部验证。结果在 10937 名接受重大非心脏手术的患者中,有 274 人(2.5%)符合持续性 AKI 的标准。较高的 GV 与持续性 AKI 风险增加有关(CV:几率比 [OR] = 1.26,95% 置信区间 [CI],1.08-1.46;MAGE:OR=1.31,95% CI,1.15-1.49;BGRI:OR=1.18,95% CI,1.08-1.29)。与不考虑血糖因素的模型相比,MAGE 和 BGRI 可独立预测持续性 AKI(MAGE:曲线下面积 [AUC] = 0.768,P = .011;BGRI:AUC = 0.764,P = .014),MAGE 临界点为 3.78,BGRI 临界点为 3.02。使用截断点对内部和外部验证队列进行分类显示出良好的性能,内部队列中 MAGE 的最佳 AUC 值为 0.768,外部队列中 MAGE 的最佳 AUC 值为 0.777。特定的临界点可用于对高危患者进行分层。这些研究结果表明,稳定 GV 有可能减轻非心脏手术后肾脏的不良预后,突出了围手术期血糖控制的重要性。
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