Dynamics in perioperative neutrophil-to-lymphocyte*platelet ratio as a predictor of early acute kidney injury following cardiovascular surgery.
Dynamics in perioperative neutrophil-to-lymphocyte*platelet ratio as a predictor of early acute kidney injury following cardiovascular surgery.
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围手术期中性粒细胞与淋巴细胞血小板比率的动态作为心血管手术后早期急性肾损伤的预测因子
DOI：
10.1080/0886022x.2021.1937220
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发表时间：
2021-12
期刊：
影响因子：
3
通讯作者：
Ding X
中科院分区：
文献类型：
--
作者：
Li Y;Zou Z;Zhang Y;Zhu B;Ning Y;Shen B;Wang C;Luo Z;Xu J;Ding X
本研究应用嗜中性粒细胞-淋巴细胞 * 血小板比值（NLPR）复合指标，探讨围手术期NLPR动态变化对预测心脏手术相关急性肾损伤（CSA-AKI）的意义。2019年7月1日至12月31日期间，参与者前瞻性地来自“中山心血管外科队列”。使用两个时间点的中性粒细胞计数、淋巴细胞和血小板计数确定NLPR。应用剂量-反应关系分析来描述不同NLPR水平下CSA-AKI的非线性比值比（OR）。然后将NLPR积分到广义估计方程（GEE）中，预测阿基的风险。在接受心血管手术的2449例患者中，838例（34.2%）发生CSA-AKI，1期（n = 658，26.9%），2-3期（n = 180，7.3%）。与非AKI患者相比，阿基患者的术前和术后NLPR均较高（1.1[0.8，1.8] vs. 0.9[0.7，1.4]，p < 0.001; 12.4[7.5，20.0] vs. 10.1[6.4，16.7]，p < 0.001）。这种效应是一种“J”形关系：CSA-AKI的风险在术前NLPR 1.0之前相对平稳，之后迅速增加，比值比为1.13（1.06-1.19）/1单位。同样，术后NLPR值>11.0的患者更有可能发生阿基，OR为1.02。将动态NLPR整合到GEE模型中，我们发现AUC为0.806（95% CI 0.793-0.819），显著高于无NLPR的AUC（0.799，p < 0.001）。围手术期NPLR动态变化是预测急性肾损伤的一个有前景的指标。它将促进阿基风险管理，并允许临床医生早期干预，以逆转肾损伤。
In this study, we applied a composite index of neutrophil-lymphocyte * platelet ratio (NLPR), and explore the significance of the dynamics of perioperative NLPR in predicting cardiac surgery-associated acute kidney injury (CSA-AKI). During July 1st and December 31th 2019, participants were prospectively derived from the ‘Zhongshan Cardiovascular Surgery Cohort’. NLPR was determined using neutrophil counts, lymphocyte and platelet count at the two-time points. Dose-response relationship analyses were applied to delineate the non-linear odds ratio (OR) of CSA-AKI in different NLPR levels. Then NLPRs were integrated into the generalized estimating equation (GEE) to predict the risk of AKI. Of 2449 patients receiving cardiovascular surgery, 838 (34.2%) cases developed CSA-AKI with stage 1 (n = 658, 26.9%), stage 2–3 (n = 180, 7.3%). Compared with non-AKI patients, both preoperative and postoperative NLPR were higher in AKI patients (1.1[0.8, 1.8] vs. 0.9[0.7,1.4], p < 0.001; 12.4[7.5, 20.0] vs. 10.1[6.4,16.7], p < 0.001). Such an effect was a ‘J’-shaped relationship: CSA-AKI’s risk was relatively flat until 1.0 of preoperative NLPR and increased rapidly afterward, with an odds ratio of 1.13 (1.06–1.19) per 1 unit. Similarly, patients whose postoperative NLPR value >11.0 were more likely to develop AKI with an OR of 1.02. Integrating the dynamic NLPRs into the GEE model, we found that the AUC was 0.806(95% CI 0.793–0.819), which was significantly higher than the AUC without NLPR (0.799, p < 0.001). Dynamics of perioperative NPLR is a promising marker for predicting acute kidney injury. It will facilitate AKI risk management and allow clinicians to intervene early so as to reverse renal damage.