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院内心脏骤停前动脉血气分析结果的时间变化及预测价值

Temporal variations in and predictive values of ABG results prior to in-hospital cardiac arrest.

作者信息

Attin Mina, Ren Jie, Cross Chad, Kapukotuwa Sidath, Shao Ryan, Kaufmann Peter G, Lin C D Joey, Arcoleo Kim

机构信息

School of Nursing, University of Nevada, Las Vegas, 4505 S Maryland Pkwy, Las Vegas, NV 89154, USA.

Kirk Kerkorian School of Medicine, University of Nevada, Las Vegas, 625 Shadow Ln, Las Vegas, NV 89106, USA.

出版信息

J Med Surg Public Health. 2024 Dec;4. doi: 10.1016/j.glmedi.2024.100143. Epub 2024 Oct 20.

Abstract

In-hospital cardiac arrest (IHCA) has been understudied relative to out-of-hospital cardiac arrest. Further, studies of IHCA have mainly focused on a limited number of pre-arrest patient characteristics (e.g., demographics, number and types of comorbidities). Arterial blood gas (ABG) analysis, one of the most common diagnostic tests for assessing and managing critically or acutely ill hospitalized patients, reflects pathophysiological changes associated with adverse events or complications, including IHCA. Yet the predictive and prognostic values of patterns of pre-arrest ABG parameters for IHCA have not been fully studied. The purpose of this retrospective pilot cohort study was to investigate temporal variations in and predictive values of pre-IHCA ABG values among patients with a history of cardiopulmonary diseases. Eligible patients had a history of structural heart disease, heart failure, or pulmonary diseases. Patients were excluded if their IHCA was due to trauma, drug overdose, hypothermia, drowning, chronic terminal illness such as cancer or human immunodeficiency virus, or bleeding not caused by hemorrhage in the brain or heart. Also collected were dates, times, and causes of mechanical intubation prior to IHCA and causes of mortality. Co-primary outcomes were initial rhythms of IHCA and return of spontaneous circulation (ROSC). We conducted a pilot study and the ABG results (pH, partial pressure of carbon dioxide [PaCO], partial pressure of oxygen [PaO], bicarbonate [ ], and lactate) from each of the 3 days prior to IHCA were extracted from the electronic health records (EHRs) of patients (N = 44) who had experienced IHCA at a single medical center. To characterize differences in ABG parameters among study days, coefficients of variation (CVs) were compared using the modified likelihood ratio test (MLRT) using the worst ABG values. Linear regression models were run for the continuous ABG parameters and logistic regression models for the dichotomous ABG variables. Overall model effect and least squares means, SDs, mean differences within and between days (with 95 % confidence intervals), -values and effect sizes were reported for continuous variables. For categorical variables, estimates and standard errors, 95 % confidence intervals, Wald X2 variables and -values were presented. The CVs for pH, PaCO, and differed significant between study days ( <.05). The least squares means with 95 % confidence intervals for pH and lactate differed significantly in days ( <.01). Moderate to large effect sizes were obtained for all ABG parameters. Arterial lactate predicted initial rhythm (shockable versus non-shockable) and ROSC, while pH and predicted ROSC. Results demonstrate, for the first time, the presence of significant variability in ABG parameters across 72 h prior to IHCA and the predictive potential of these parameters for initial rhythms of IHCA and ROSC. While validation in a larger sample is necessary, this study confirms the feasibility and potential value of exploring temporal patterns of pre-arrest ABG values from the EHRs. Findings of future larger studies on pre-arrest patterns of ABG parameters and other laboratory values may be used to design models that better predict risk for IHCA and guide patient care in the pre and intra-arrest periods.

摘要

相对于院外心脏骤停,院内心脏骤停(IHCA)的研究较少。此外,关于IHCA的研究主要集中在有限的一些心脏骤停前患者特征(如人口统计学特征、合并症的数量和类型)上。动脉血气(ABG)分析是评估和管理重症或急性病住院患者最常用的诊断测试之一,它反映了与不良事件或并发症(包括IHCA)相关的病理生理变化。然而,心脏骤停前ABG参数模式对IHCA的预测和预后价值尚未得到充分研究。这项回顾性试点队列研究的目的是调查心肺疾病史患者心脏骤停前ABG值的时间变化及其预测价值。符合条件的患者有结构性心脏病、心力衰竭或肺部疾病史。如果患者的IHCA是由创伤、药物过量、体温过低、溺水、慢性终末期疾病(如癌症或人类免疫缺陷病毒)或非脑或心脏出血引起的出血导致的,则将其排除。还收集了心脏骤停前机械通气的日期、时间和原因以及死亡原因。共同主要结局是心脏骤停的初始心律和自主循环恢复(ROSC)。我们进行了一项试点研究,从一家医疗中心经历过心脏骤停的患者(N = 44)的电子健康记录(EHR)中提取了心脏骤停前3天中每一天的ABG结果(pH值、二氧化碳分压[PaCO]、氧分压[PaO]、碳酸氢盐[]和乳酸)。为了描述研究日之间ABG参数的差异,使用修正似然比检验(MLRT),以最差的ABG值比较变异系数(CV)。对连续ABG参数进行线性回归模型分析,对二分ABG变量进行逻辑回归模型分析。报告了连续变量的总体模型效应、最小二乘均值、标准差、日内和日间均值差异(95%置信区间)、P值和效应大小。对于分类变量,给出了估计值和标准误差、95%置信区间、Wald X2变量和P值。pH值、PaCO和[]的CV在研究日之间有显著差异(P <.05)。pH值和乳酸的95%置信区间的最小二乘均值在不同日期有显著差异(P <.01)。所有ABG参数均获得了中等到大的效应大小。动脉乳酸预测初始心律(可电击与不可电击)和ROSC,而pH值和[]预测ROSC。结果首次证明,在心脏骤停前72小时内ABG参数存在显著变异性,且这些参数对心脏骤停的初始心律和ROSC具有预测潜力。虽然需要在更大样本中进行验证,但本研究证实了从EHR中探索心脏骤停前ABG值时间模式的可行性和潜在价值。未来关于心脏骤停前ABG参数和其他实验室值模式的更大规模研究结果可用于设计更好地预测心脏骤停风险并指导心脏骤停前和心脏骤停期间患者护理的模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a5c/11760193/64307f5e3c47/nihms-2042819-f0001.jpg

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