Impact of Mean Arterial Pressure Fluctuation onMortality in Critically Ill Patients
Ya Gao, MD1; Qinfen Wang, MSc2; Jiamei Li, MD1; Jingjing Zhang, MD1; Ruohan Li, MD1;Lu Sun, MD3; Qi Guo, MD4; Yong Xia, PhD2; Bangjiang Fang, MD, PhD5; Gang Wang, MD, PhD1
Abstract摘要
Objective: The purpose of this study was to investigate the associationbetween mean arterial pressure fluctuations and mortalityin critically ill patients admitted to the ICU.
目的：探讨ICU危重病人平均动脉压波动与死亡率的关系。
Methods
Design: Retrospective cohort.
Setting: All adult ICUs at a tertiary care hospital.
Patients: All adult patients with complete mean arterial pressurerecords were selected for analysis in the Multiparameter IntelligentMonitoring in Intensive Care II database. Patients in theexternal cohort were newly recruited adult patients in the MedicalInformation Mart for Intensive Care III database.Interventions: None.
方法：对所有三级医院成人ICU进行回顾性队列研究。所有具有完整的平均动脉压记录的成年患者均被选入重症监护II的多参数智能监测数据库中进行分析。外部队列中的患者是新招募的成年患者，资料收集为重症监护III数据库。
Main Results: The records of 8,242 patientswere extracted. Mean arterial pressure fluctuation was calculatedas follows: (mean night time mean arterial pressure –mean daytimemean arterial pressure)/mean arterial pressure. Patients weredivided into two groups according to the degree of mean arterialpressure fluctuation: group A (between –5% and 5%) and groupB (<–5% and >5%). The endpoints of this study were ICU andhospital mortality. Patients in group A (n = 4,793) had higher ICUand hospital mortality than those in group B (n = 3,449; 11.1% vs8.1%, p < 0.001 and 13.8% vs 10.1%, p < 0.001, respectively).After adjusting for other covariates, the mean arterial pressurefluctuations between –5% and 5% were significantly correlatedwith ICU mortality (odds ratio, 1.296; 95% CI, 1.103–1.521;p = 0.002) and hospital mortality (odds ratio, 1.323; 95% CI,1.142–1.531; p < 0.001). This relationship remained remarkablein patients with low or high Sequential Organ Failure Assessmentscores in the sensitive analysis. Furthermore, external validationon a total of 4,502 individuals revealed that patients in group Astill had significantly higher ICU (p < 0.001) and hospital mortality(p < 0.001) than those in group B.
结果：对8242例患者进行数据分析。平均动脉压波动计算如下：（平均夜间平均动脉压-平均白天平均动脉压）/平均动脉压。根据平均动脉压波动程度将患者分为两组：A组（-5%和5%之间）和B组（<-5%和>5%）。研究的目的是ICU和住院死亡率。A组(n=4793)患者ICU及住院死亡率明显高于B组(n=3449;11.1%vs 8.1%,p<0.001,13.8%vs 10.1%,p<0.001)。调整其他协变量后，-5%和5%之间的平均动脉压波动与ICU死亡率（优势比，1.296；95%CI，1.103-1.521；p=0.002）和医院死亡率（优势比，1.323；95%CI，1.142-1.531；p<0.001）显著相关。在敏感性分析中，这种关系在低或高SOFA评分的患者中仍然显著。此外，对4502人的外部队列验证显示，A组的ICU（p<0.001）和医院死亡率仍显著高于B组（p<0.001）。
Conclusions: The reduced mean arterial pressure fluctuation(within –5% and 5%) may be associated with ICU and hospitalmortality in critically ill patients.
结论：危重患者平均动脉压波动降低（在-5%和5%以内）可能与ICU和住院死亡率有关。
Key Words:fluctuation; intensive care unit; mean arterial pressure;mortality; Multiparameter Intelligent Monitoring in Intensive CareII; Sequential Organ Failure Assessment scores
关键词：波动；重症监护病房；平均动脉压；死亡率；重症监护多参数智能监测II；序贯性器官功能衰竭评分
Introduction引言
The hypothalamic suprachiasmatic nucleus (SCN) plays a critical role in orchestrating the circadian rhythms of the human body, such as core body temperature (CBT), hormone levels, blood glucose level, sleep cycles, the immune system, and the autonomic nervous system via a self-regulating molecular mechanism . In addition to the desynchronization of critical illness, patients in ICU are exposed to different degrees of artificial light, noise, and various organ supports including ventilation, parenteral nutrition, and medications.Therefore, disrupted circadian rhythms of sleep architecture, CBT, blood glucose, and blood pressure (BP) in ICU patients have been frequently observed, and CBT has been found to be associated with the severity of illness .
下丘脑视交叉上核（SCN）通过自我调节的分子机制在调节人体生理节律方面起着关键作用，如核心体温（CBT），激素水平，血糖，睡眠周期，免疫系统和自主神经系统。ICU患者还暴露于不同程度的人工光、噪音以及各种器官支持，包括机械通气、肠外营养和各种药物。因此，睡眠结构、CBT、血糖和血压(BP)昼夜节律紊乱在ICU患者中很常见。并且已经有研究证实CBT与疾病的严重程度相关。
BP is a physiologic parameter presenting various variations as a result of neuroendocrine variables and exogenousfactors . Several researchers have shown that abnormal BP variation is associated with various organ damage, higher risk for cardiovascular events, and mortality . In addition,based on our previous research, abnormal circadian BP variation is associated with an elevated risk of various cardiovascular and metabolic conditions . A previous investigation revealed the prognostic value of the first 5-minute systolic BP (SBP) variability in patients with severe sepsis or septic shock for 28-day ICU mortality . However, the relationship between the day-night BP variation and mortality in critically ill patients remains currently unclear. Mean arterial pressure (MAP) serves as an important variable for evaluating organ perfusion in ICU . We aimed to explore the associations between MAP fluctuation and ICU and hospital mortality in critically ill patients admitted to the ICU in the Multiparameter Intelligent Monitoring in Intensive CareII (MIMIC-II) database.
血压是在神经内分泌和外源性因素共同作用下，呈现多种变化的一项生理参数。一些研究已经表明，血压异常变化与器官损伤、心血管事件的高风险以及死亡率有关。此外，根据我们以前的研究，血压昼夜节律的异常变化与各种心血管事件高风险和代谢状况相关。先前的一项研究显示，在严重败血症或感染性休克患者中，前5分钟收缩压（SBP）变异度对28天ICU死亡率有预测价值。然而，目前尚不清楚昼夜血压变化与危重患者死亡率之间的关系。平均动脉压(MAP)是评价ICU器官灌注的重要指标。本研究旨在应用重症监护病房多参数智能监测数据库(MIMIC-II)探索MAP波动与ICU及危重病人住院死亡率的关系。
Materials and Methods 材料与方法
Study Design研究方案
We used data from the MIMIC-II and extracted the following parameters for each patient: age at ICU admission, sex, ethnicity, first Sequential Organ Failure Assessment (SOFA) score and first Simplified Acute Physiology Score (SAPS-I) score, vasopressor medications, vasodepressor medications,sedatives, and complete MAP records.
我们使用MIMIC-II的数据库，提取每个患者以下参数：ICU入院年龄、性别、种族、首次序贯性器官衰竭评估（SOFA）评分和简化急性生理学评分（SAPS-I），血管收缩药物，血管舒张药物，镇静剂和完整的MAP记录。
Participants参与者
All adult patients (>15 yr old) with MAP records in the database were selected for analysis. However, individuals were excluded if they 1) were diagnosed as having shock due to any cause; 2) had multiple ICU admissions; 3) stayed in the ICU for less than 1 day; 4) had no SOFA and SAPS-I scores; and 5) had no day MAP records or night MAP records. In addition, patients were not included if greater than 30% of their MAP values less than 50 or greater than 183 mm Hg because extreme records failed to reflect the general characteristics of day-night MAP variation.Invasive MAP values were continuously collected using a bedside monitor during the ICU stay to avoid the inaccuracy of nurse-driven records . The mean value of the MAP measurements obtained from 7 am to11 pm and 11 pm to 7 am was defined as the mean daytime and nighttime MAP, respectively. MAP fluctuation was calculated as follows: (mean nighttime MAP – mean daytime MAP)/mean MAP (all MAP values/the number of MAP examinations).Patients were divided into 2 groups based on the degree of MAP fluctuation: group A (flu ctuation between –5% and 5%) and group B(fluctuation <–5% and >5%). The endpoints of this study were ICU and hospital mortality.
本研究选择数据库中有MAP记录的所有15岁以上的成人患者进行分析。排除标准：1)任何原因引起的休克，2)多次ICU住院，3)在ICU停留不足1天，4)没有SOFA和SAPS-I评分，5)没有白天MAP记录或夜间MAP记录。此外，如果患者的有大于30%deMAP值小于50或大于183mm Hg，亦排除患者，因为极端记录不能反映日夜MAP变化的一般特征。早上7点到晚上11点和晚上11点到早晨7点获得的MAP测量的平均值分别定义为白天和晚上的平均MAP。计算MAP波动。如下所示：（平均夜间MAP—平均白天MAP）/平均MAP(所有MAP值/MAP检查次数)。根据MAP波动分为两组。：A组（波动-5%~5%）和B组(波动<5%和>5%)。研究两组之间ICU和医院死亡率。
Statistical Analysis统计分析
Categorical variables were presented as percentages and compared using a chi-square test. Continuous variables were expressed as mean ± sd and compared using a Student t test.Logistic regression models were used to assess the impact of MAP fluctuation on the outcomes (i.e., ICU mortality/hospital mortality). Model 1 was adjusted for age, sex, and ethnicity.Model 2 was adjusted for the covariates included in model 1 plus mean MAP. Model 3 was adjusted for the covariates included in model 2 as well as the SOFA and SAPS-I scores. Model 4 incorporated model 3 along with some of the major comorbidities that could influence mortality (i.e., congestive heart failure, cardiac arrhythmia, hypertension, complicated diabetes, uncomplicated diabetes, metastatic cancer, renal failure, liver disease,lymphoma, coagulopathy, and delirium) based on the univariate analysis results and clinical experience. Besides covariates included in the model 4, model 5 comprised vasopressor medication, vasodepressor medication, and sedatives.
分类变量以百分比表示，并用卡方检验进行比较。连续变量用平均值±sd表示，并用t检验进行比较。Logistic回归模型用于评估MAP波动对结局（即ICU死亡率/医院死亡率）的影响。模型1根据年龄、性别和种族进行调整，模型2根据模型1加上平均MAP中的协变量进行调整。模型3针对模型2中包括的协变量以及SOFA和SAPS-I评分进行调整。模型4结合了模型3以及可能影响死亡率的一些主要并发症(充血性心力衰竭、心律失常、高血压、糖尿病合并并发症、无并发症的糖尿病、转移癌、肾衰竭、肝病、淋巴瘤、凝血病和谵妄)，基于单变量分析结果和临床经验。除了模型4中包括的协变量外，模型5又增加了血管升压药物、血管抑制药物和镇静剂。
A sensitivity analysis was conducted to determine whether the results persisted even when the severity of the clinical status changed. The SOFA score, a measure of organ dysfunction,has been shown to be associated with patient outcomes . Possible interactions between MAP fluctuation and SOFA scores were evaluated. Another three sensitivity analyses were conducted in the patients without vasodepressor, vasopressor, or sedative exposure, respectively. All data were analyzed using SPSS version 18.0 (SPSS, Chicago, IL). P values less than 0.05 indicated statistical significance.
进行敏感性分析以确定即使临床状况的严重程度发生变化，结果是否仍然存在。SOFA评分是衡量器官功能障碍的一项指标，已被证明与患者的预后有关。我们评估了MAP波动与SOFA评分之间可能的相互作用。另外三项敏感性分析分别为是否应用血管抑制剂、血管加压剂或镇静剂。所有数据都使用SPSS版本18.0进行分析。P<0.05有统计学意义。
Results结果
From the 15,551 adult patients with MAP records a total of 8,242 patients were included in this study . Patients were divided into group A(n = 4,793) and group B (n = 3,449) based on the MAP fluctuation.The main characteristics of the study participants are shown in Table 1. There were no significant differences in age,sex, or ethnicity between the two groups. Patients in group A had lower MAP fluctuations and higher SOFA (p < 0.001) and SAPS-I (p = 0.002) scores than those in group B. Furthermore, group A had a relatively higher prevalence of congestive heart failure, hypertension, uncomplicated diabetes, renal failure, liver disease, and coagulopathy than group B. Additionally,patients in group A had a higher exposure rate for vasodepressor, vasopressor, and sedatives than those in group B. The mean MAP was not significantly different between these two groups (81.61 vs 81.38 mm Hg; p = 0.333).
Surprisingly, we found that patients in group A had higher ICU and hospital mortality than those in group B (11.1% vs8.1%, p < 0.001 and 13.8% vs 10.1%, p < 0.001, respectively)(Table 1). Logistic regression was performed to verify the association between MAP fluctuation and ICU and hospital mortality.After adjusting for a series of covariates, such as age, sex, ethnicity, mean all-day MAP, SOFA score, SAPS-I score, major comorbidities in regression models, and medications, MAP fluctuations between –5% and 5% were significantly correlated with ICU (odds ratio [OR], 1.296; 95% CI, 1.103–1.521;p = 0.002) and hospital (OR, 1.323; 95% CI, 1.142–1.531; p <0.001) mortality (Table 2).
在15551例有MAP记录的成人患者中，共有8242例被纳入本研究。根据MAP的波动将患者分为A组(n=4793)和B组(n=3449)。研究参与者的主要特征如表1所示。两组在年龄、性别、种族上均无显著差异。与B组相比，A组MAP波动小，SOFA和SAPS-I评分高（p<0.001），且A组充血性心力衰竭、高血压、无并发症糖尿病、肾功能衰竭、肝病、凝血病的患病率相对较高。血管舒张剂、血管收缩剂和镇静剂的暴露率高于B组。两组平均MAP无显著差异（81.61与81.38mm Hg，p=0.333）。
令人惊讶的是，我们发现A组的病人ICU及住院死亡率高于B组（11.1%vs.1%）。8.1%，p<0.001和13.8%，vs 10.1%，p<0.001（表1）。我们采用Logistic回归分析MAP波动与ICU及住院死亡率的关系。通过调整回归分析模型中一系列协变量如年龄、性别、种族、平均全天MAP、SOFA评分、SAPS-I评分、主要合并症和药物治疗后，-5%和5%之间的MAP波动与ICU（OR，1.296；95%CI，1.103-1.521；p=0.002）和住院（OR，1.323；95%CI，1.142–1.531；p<0.001）死亡率显著相关（表2）。
表1
表2
To diminish the influence of patient severity on mortality, all individuals were divided into two subgroups for further sensitivity analysis: 0 ≤ SOFA score ≤ 7 (n = 4,230) and 8 ≤ SOFAscore ≤ 24 (n = 4,012). In the 0 ≤ SOFA score ≤ 7 subgroup,group A had a higher ICU (9.2% vs 6.5%; p = 0.001) and hospital(12.6% vs 8.7%; p < 0.001) mortality than those in group B.This result was also observed in patients who had SOFA scores between 8 and 24. Additionally, based on the logistic regression analysis conducted for both subgroups, MAP fluctuations between–5% and 5% were a statistically significant factor in both models with or without adjusting for any covariates (Table 3).Furthermore, three sensitivity analyses in the patients without receiving vasodepressor, vasopressor, or sedatives showed that the patients with lower MAP fluctuations were still associated with both ICU and hospital mortality after adjusting a series of covariates.
为了减少患者病情严重性对死亡率的影响，所有个体分为0≤SOFA评分≤7（n=4230）和8≤SOFA评分≤24（n=4012）两个亚组进行进一步的敏感性分析。在0≤SOFA评分≤7分组中，A组的ICU死亡率（9.2%vs 6.5%，p=0.001）和住院死亡率（12.6%vs 8.7%，p<0.001）明显高于B组。这个结果在SOFA评分在8到24之间的患者中也观察到。此外，基于对两个亚组进行的logistic回归分析，MAP波动在-5%和5%之间在两个模型中都有统计学差异，不论是否调整任何协变量（表3）。此外，对未接受血管舒张剂、血管收缩剂或镇静剂的患者的三项敏感性分析表明，MAP波动较低组的患者在调整一系列协变量后，仍然与ICU和医院死亡率相关。
In the external cohort,a total of 4,502 patients were included into the analysis and divided into group A (n = 2,376) and group B (n = 2,126).The results demonstrated that patients in group A had a significantly higher ICU and hospital mortality than those in group B (9.8% vs 6.0%, p < 0.001 and 17.0% vs 11.4%, p < 0.001,respectively).
在外部队列中，共有4502例患者被纳入分析，并分为A组（n=2376）和B组（n=2126）。结果表明，A组ICU和住院死亡率明显高于B组（分别为9.8%和6.0%，p<0.001，17.0%和11.4%，p<0.001）。
表3
Discussion讨论
MAP is associated with organ perfusion and mortality. Although the MAP at admission has been identified.as a risk factor for ICU mortality , MAP fluctuation, especially day-night variation, has not yet been investigated in any predicting models for ICU mortality. we found that lower MAP fluctuations were significantly correlated with ICU mortality (OR, 1.296; 95% CI,1.103–1.521; p = 0.002) and hospital mortality (OR, 1.323;95% CI, 1.142–1.531; p < 0.001) after adjusting for a series of covariates. To the best of our knowledge, this was the first study in which the relationship between MAP fluctuation and ICU and hospital mortality has been evaluated using data from the MIMIC-II database.
MAP与器官灌注和死亡率相关。虽然研究前我们已确认MAP是ICU死亡率的一个危险因素，但还没有任何关于MAP波动，尤其是昼夜变化，对ICU死亡率的影响。我们发现较低的MAP波动与ICU死亡率（OR，1.296；95%CI，1.103-1.521；p=0.002）和住院死亡率（OR，1.323；调整一系列协变量后，95%CI为1.142-1.531，p<0.001）显著相关。据我们所知，这是首次使用MIMIC-II数据库的数据来评估MAP波动与ICU和住院死亡率之间的关系。
In this study, we found that patients with lower MAP fluctuations had higher ICU and hospital mortality than other patients. Furthermore,we also evaluated the difference in the mean MAP and found that it was not different between the two groups. After adjusting for the mean MAP as a covariate variable in the logistic regression model, the associations of MAP fluctuation with ICU and hospital mortality in critically ill patients remained statistically significant.
在本研究中，我们发现低MAP波动的患者比其他患者具有更高的ICU和医院死亡率。此外，我们还评估了平均MAP的差异，发现两组之间没有差异。将平均MAP作为logistic回归模型中的协变量进行调整后，MAP波动与ICU和危重患者医院死亡率的相关性在统计学上仍然显著。
The SOFA score is a well-known measure that is robustly correlated with patient outcomes in the ICU setting. Therefore, we conducted a sensitivity analysis in which the patients were divided into two subgroups according to SOFA scores (i.e., ≤7 or >7) according to previous interaction analysis.Surprisingly, the association between MAP fluctuations and mortality persisted in the subgroups. Furthermore, as vasoactive medications and sedatives may affect BP regulation, we performed three sensitivity analyses in patients who were not exposed to vasodepressor, vasopressor, or sedatives,respectively. The logistic regression verified the association of MAP fluctuations with mortality again. Therefore, a lower MAP fluctuation (between –5% and 5%) may serve as an independent risk factor for both ICU and hospital mortality in critically ill patients. Based on this conclusion, further management, such as reducing the number of operations or lowering light intensity level at night, may be taken into account to improve circadian BP rhythm of ICU patient to improve their prognosis.
SOFA评分是一个众所周知的ICU患者预后预测指标。因此，我们进行了敏感性分析，根据SOFA评分（即≤7或>7）将患者分为两个亚组，令人惊讶的是，MAP波动与死亡率之间的关系在亚组中仍然存在。此外，由于血管活性药物和镇静剂可能影响血压调节，我们对未接触血管舒张剂、血管收缩剂或镇静剂的患者分别进行了三种敏感性分析。Logistic回归再次验证了MAP波动与死亡率的关系。因此，较低的MAP波动（在-5%至5%之间）可以作为ICU和危重患者医院死亡率的独立危险因素。根据这一结论，可以考虑进一步的处理，如减少操作次数，降低夜间光强度水平，以改善ICU患者的血压昼夜节律，以改善其预后。
In normal conditions, the circadian decline rate of SBP mostly determined by endogenous neuroendocrine rhythm. Critically ill patients suffer from the circumstance alterations in light-dark cycles, auditory disruption, iatrogenic treatment, and psychologic reactions when they are admitted to the ICU. These external changes disturb the endogenous neuroendocrine rhythm and sleep-wake cycle, which may contribute to the abnormal BP variation. Changes in the level of growth hormone, adrenal steroids, thyrotropin, norepinephrine, gonadotropin, and melatonin had been verified existed in ICU patients . Among them, abnormal melatonin might associate with a series of pathologic processes such as inflammation, endotoxemia, and CNS diseases . These altered endogenous substances may contribute to higher mortality in ICU patients with lower MAP fluctuation.
正常情况下，SBP的昼夜下降率主要由内源性神经内分泌节律决定。危重病人在入住ICU时，会受到明暗周期变化、听力障碍、医源性治疗和心理反应的影响。这些外部变化扰乱了内源性神经内分泌节律和睡眠-觉醒周期，这可能是导致血压异常变化的原因。ICU患者存在生长激素、肾上腺皮质激素、促甲状腺素、去甲肾上腺素、促性腺激素和褪黑激素水平的变化。其中，褪黑素异常可能与一系列病理过程有关，如炎症、内毒素血症和中枢神经系统疾病。这些改变的内源性物质可能导致ICU患者MAP波动下降。
Our study has some limitations. First, although we conducted an external validation and successfully verified our finding, there were no SOFA and SAPS-I scores available in the MIMIC-III database for further logistic regression. Second,the MIMIC-II database reflects the real-world clinical setting;therefore, different intervals between BP monitoring measurements may exist . We calculated the MAP fluctuation using the average of night MAP, day MAP, and all-day MAP, furthermore,adjusted for a series of covariates in the regression models to diminish the potential influence of mortality. This could be addressed by conducting a well-designed prospective study to evaluate the relationship with predefined frequency of BP measurements in the future. Finally, as limitations of retrospective study, potential biases (i.e., selection bias) are inevitable. Although we have adjusted for as many covariate variables as possible to diminish the possible influences, residual confounding may exit and need to be investigated in the future.
我们的研究有一定的局限性。首先，虽然我们进行了一次外部验证并成功地验证了我们的发现，但是在MIMIC-III数据库中没有SOFA和SAPS-I评分可用于进一步的逻辑回归。第二，MIMIC-II数据库反映了真实世界的临床环境，因此可能存在BP监测测量之间的不同间隔。我们利用夜间MAP、白天MAP和全天MAP的平均值来计算MAP的波动，并且调整回归模型中的一系列协变量，以减小死亡率的潜在影响。这可以通过进行精心设计的前瞻性研究来解决，以评估未来血压测量与预定频率的关系。最后，由于回顾性研究的局限性，潜在的偏倚（即选择偏倚）是不可避免的。尽管我们已经调整了尽可能多的协变量以减小可能的影响，但是仍然可能存在残余混淆，并且需要在将来进行研究。
Conclusions 结论
In this study, we investigated the relationship between MAPand mortality in critically ill patients and found that patientswith lower MAP (between –5% and 5%) fluctuations may beassociated with both ICU and hospital mortality. The sensitivityanalysis further confirmed this association in patients witheither low or high SOFA scores.
在本研究中，我们调查了MAP与危重患者死亡率之间的关系，发现MAP波动较低的患者（在-5%和5%之间）可能与ICU和医院死亡率有关。敏感性分析进一步证实了SOFA评分低或高的患者存在这种关联。
翻译
丁瑞琪 博士
山东省立医院重症医学科主治医师，兼任山东省医师协会重症基层委员会委员兼秘书，山东省卫生与健康物联网专业委员会委员兼秘书。
在线速递
翻译：丁瑞琪
审校：张继承/王春亭
编辑：宋 璇
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