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[平均灌注压对脓毒症相关性急性肾损伤风险的影响]

[Impact of mean perfusion pressure on the risk of sepsis-associated acute kidney injury].

作者信息

Yang Linshan, Zhou Wei, Sheng Shuyue, Fan Guoliang, Ma Shaolin, Zhu Feng

机构信息

Department of Critical Care Medicine, Shanghai East Hospital, Tongji University, Shanghai 200120, China. Corresponding author: Zhu Feng, Email:

出版信息

Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2025 Apr;37(4):367-373. doi: 10.3760/cma.j.cn121430-20240823-00722.

DOI:10.3760/cma.j.cn121430-20240823-00722
PMID:40814710
Abstract

OBJECTIVE

To investigate the relationship between mean perfusion pressure (MPP) and the risk of sepsis-associated acute kidney injury (SA-AKI) and its prognosis, and to determine the optimal cut-off value of MPP for predicting SA-AKI.

METHODS

A retrospective cohort study was conducted. The clinical data of adult patients with sepsis were collected from the Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2) database. The patients were divided into two groups based on the occurrence of SA-AKI. Baseline characteristics, vital signs, comorbidities, laboratory indicators within 24 hours of intensive care unit (ICU) admission, and clinical outcome indicators were collected. Mean MPP was calculated using the average values of mean arterial pressure (MAP) and central venous pressure (CVP), MPP = MAP-CVP. Cox regression models were constructed, relevant confounding factors were adjusted, and multivariate Logistic regression analysis was used to investigate the associations between MPP and the risk of SA-AKI as well as ICU death. The predictive value of MPP for SA-AKI was evaluated using receiver operator characteristic curve (ROC curve) analysis, and the optimal cut-off value was determined.

RESULTS

A total of 6 009 patients were ultimately enrolled in the analysis. Among them, SA-AKI occurred in 4 755 patients (79.13%), while 1 254 patients (20.87%) did not develop SA-AKI. Compared with the non-SA-AKI group, the MPP in the SA-AKI group was significantly lowered [mmHg (1 mmHg≈0.133 kPa): 62.00 (57.00, 68.00) vs. 65.00 (60.00, 70.00), P < 0.01], and the ICU mortality was significantly increased [11.82% (562/4 755) vs. 1.59% (20/1 254), P < 0.01]. Three Cox regression models were constructed: model 1 was unadjusted; model 2 was adjusted for gender, age, height, weight and race; model 3 was adjusted for gender, age, height, weight, race, heart rate, respiratory rate, body temperature, hemoglobin, platelet count, white blood cell count, anion gap, HCO, blood urea nitrogen, serum creatinine, Cl, Na, K, fibrinogen, international normalized ratio, blood lactic acid, pH value, arterial partial pressure of oxygen, arterial partial pressure of carbon dioxide, sequential organ failure assessment score, Charlson comorbidity index score, use of vasopressors, mechanical ventilation, and urine output. Multivariate Logistic regression analysis showed that when MPP was treated as a continuous variable, there was a negative correlation between MPP and the risk of SA-AKI in model 1 and model 2 [model 1: odds ratio (OR) = 0.967, 95% confidence interval (95%CI) was 0.961-0.974, P < 0.001; model 2: OR = 0.981, 95%CI was 0.974-0.988, P < 0.001], and also a negative correlation between MPP and the risk of ICU death (model 1: OR = 0.955, 95%CI was 0.945-0.965, P < 0.001; model 2: OR = 0.956, 95%CI was 0.946-0.966, P < 0.001). However, in model 3, there was no significant correlation between MPP and either SA-AKI risk or ICU death risk. when MPP was used as a multi-categorical variable, in model 1 and model 2, referring to MPP ≤ 58 mmHg, when 59 mmHg ≤ MPP ≤ 68 mmHg, as MPP increased, the risk of SA-AKI progressively decreased (OR value was 0.411-0.638, all P < 0.001), and the risk of ICU death also gradually decreased (OR value was 0.334-0.477, all P < 0.001). ROC curve showed that MPP had a certain predictive value for SA-AKI occurrence [area under the ROC curve (AUC) = 0.598, 95%CI was 0.404-0.746], and the optimal cut-off value was 60.5 mmHg.

CONCLUSION

MPP was significantly associated with the risk of SA-AKI, with an optimal cut-off value of 60.5 mmHg, and also demonstrated a significant correlation with the risk of ICU death.

摘要

目的

探讨平均灌注压(MPP)与脓毒症相关急性肾损伤(SA-AKI)风险及其预后之间的关系,并确定预测SA-AKI的MPP最佳截断值。

方法

进行一项回顾性队列研究。从重症监护医学信息数据库-IV 2.2(MIMIC-IV 2.2)中收集成年脓毒症患者的临床资料。根据SA-AKI的发生情况将患者分为两组。收集基线特征、生命体征、合并症、重症监护病房(ICU)入院24小时内的实验室指标以及临床结局指标。使用平均动脉压(MAP)和中心静脉压(CVP)的平均值计算平均MPP,MPP = MAP - CVP。构建Cox回归模型,调整相关混杂因素,并采用多变量Logistic回归分析来研究MPP与SA-AKI风险以及ICU死亡之间的关联。使用受试者工作特征曲线(ROC曲线)分析评估MPP对SA-AKI的预测价值,并确定最佳截断值。

结果

最终共有6009例患者纳入分析。其中,4755例患者(79.13%)发生SA-AKI,而1254例患者(20.87%)未发生SA-AKI。与非SA-AKI组相比,SA-AKI组的MPP显著降低[mmHg(1 mmHg≈0.133 kPa):62.00(57.00,68.00) vs. 65.00(60.00,70.00),P < 0.01],且ICU死亡率显著升高[11.82%(562/4755) vs. 1.59%(20/1254),P < 0.01]。构建了三个Cox回归模型:模型1未调整;模型2调整了性别、年龄、身高、体重和种族;模型3调整了性别、年龄、身高、体重、种族、心率、呼吸频率、体温、血红蛋白、血小板计数、白细胞计数、阴离子间隙、HCO、血尿素氮、血清肌酐、Cl、Na、K、纤维蛋白原、国际标准化比值、血乳酸、pH值、动脉血氧分压、动脉血二氧化碳分压、序贯器官衰竭评估评分、Charlson合并症指数评分、血管升压药的使用、机械通气和尿量。多变量Logistic回归分析显示,当将MPP作为连续变量时,模型1和模型2中MPP与SA-AKI风险呈负相关[模型1:比值比(OR) = 0.967,95%置信区间(95%CI)为0.961 - 0.974,P < 0.001;模型2:OR = 0.981,95%CI为0.974 - 0.988,P < 0.001],MPP与ICU死亡风险也呈负相关(模型1:OR = 0.955,95%CI为0.945 - 0.965,P < 0.001;模型2:OR = 0.956,95%CI为0.946 - 0.966,P < 0.001)。然而,在模型3中,MPP与SA-AKI风险或ICU死亡风险均无显著相关性。当将MPP作为多分类变量时,在模型1和模型2中,以MPP≤58 mmHg为参照,当59 mmHg≤MPP≤68 mmHg时,随着MPP升高,SA-AKI风险逐渐降低(OR值为0.411 - 0.638,均P < 0.001),ICU死亡风险也逐渐降低(OR值为0.334 - 0.477,均P < 0.001)。ROC曲线显示,MPP对SA-AKI的发生具有一定预测价值[ROC曲线下面积(AUC) = 0.598,95%CI为0.404 - 0.746],最佳截断值为60.5 mmHg。

结论

MPP与SA-AKI风险显著相关,最佳截断值为60.5 mmHg,且与ICU死亡风险也显著相关。

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