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The triple variable index combines information generated over time from common monitoring variables to identify patients expressing distinct patterns of intraoperative physiology

机译:三重变量指数将随着时间的推移产生的信息与常见的监测变量相结合,以识别表达术中生理学模式的患者

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摘要

Abstract Background Mean arterial pressure (MAP), bispectral index (BIS), and minimum alveolar concentration (MAC) represent valuable, yet dynamic intraoperative monitoring variables. They provide information related to poor outcomes when considered together, however their collective behavior across time has not been characterized. Methods We have developed the Triple Variable Index (TVI), a composite variable representing the sum of z-scores from MAP, BIS, and MAC values that occur together during surgery. We generated a TVI expression profile, defined as the sequential TVI values expressed across time, for each surgery where concurrent MAP, BIS, and MAC monitoring occurred in an adult patient (≥18 years) at the University of Pittsburgh Medical Center between January and July 2014 (n = 5296). Patterns of TVI expression were identified using k-means clustering and compared across numerous patient, procedure, and outcome characteristics. TVI and the triple low state were compared as prediction models for 30-day postoperative mortality. Results The median frequency MAP, BIS, and MAC were recorded was one measurement every 3, 5, and 5 min. Three expression patterns were identified: elevated, mixed, and depressed. The elevated pattern displayed the highest average MAP, BIS, and MAC values (86.5 mmHg, 45.3, and 0.98, respectively), while the depressed pattern displayed the lowest values (76.6 mmHg, 38.0, 0.66). Patterns (elevated, mixed, depressed) were distinct across the following characteristics: average patient age (52, 53, 54 years), American Society of Anesthesiologists Physical Status 4 (6.7, 16.1, 27.3%) and 5 (0.1, 0.6, 1.6%) categories, cardiac (2.2, 6.5, 16.1%) and emergent (5.8, 10.5, 12.8%) surgery, cardiopulmonary bypass use (0.3, 2.6, 9.8%), intraoperative medication administration including etomidate (3.0, 7.3, 12.6%), hydromorphone (47.6, 26.3, 25.2%), ketamine (11.2, 4.6, 3.0%), dexmedetomidine (18.4, 16.6, 13.6%), phenylephrine (74.0, 74.8, 83.0), epinephrine (2.0, 6.0, 18.0%), norepinephrine (2.4, 7.5, 21.2%), vasopressin (3.4, 7.6, 21.0%), succinylcholine (74.0, 69.0, 61.9%), intraoperative hypotension (28.8, 33.0, 52.3%) and the triple low state (9.4, 30.3, 80.0%) exposure, and 30-day postoperative mortality (0.8, 2.7, 5.6%). TVI was a better predictor of patients that died or survived in the 30 days following surgery compared to cumulative triple low state exposure (AUC 0.68 versus 0.62, p < 0.05). Conclusions Surgeries that share similar patterns of TVI expression display distinct patient, procedure, and outcome characteristics.
机译:摘要背景平均动脉压(地图),双光谱指数(BIS)和最小肺泡浓度(MAC)代表有价值但动态的术中监测变量。它们提供与差的结果相关的信息在一起时,但它们跨时间的集体行为尚未表现。方法我们开发了三重变量指数(TVI),该复合变量代表了在手术期间一起发生的MAP,BIS和MAC值的Z分数和。我们生成了一个TVI表达式配置文件,定义为跨国公司在1月至7月至7月之间的成人患者(≥18岁)中发生同时地图,BIS和MAC监测的每个手术的顺序TVI值。 2014(n = 5296)。使用K-means聚类鉴定了TVI表达的模式,并在众多患者,程序和结果特征上进行了比较。 TVI和三重低州被比较为30天术后死亡率的预测模型。结果记录中位频率图,BIS和MAC每3,5和5分钟进行一次测量。鉴定了三种表达模式:升高,混合和抑郁。升高的模式显示了最高的平均图,BIS和MAC值(分别为86.5 mmHg,45.3和0.98),而凹陷模式显示为最低值(76.6 mmHg,38.0,0.66)。模式(升高,混合,抑郁)在以下特征中是明显的:平均患者年龄(52,53,54岁),美国麻醉学家身体状态4(6.7,16.1,27.3%)和5(0.1,0.6,1.6 %)类别,心脏(2.2,6.5,16.1%)和出苗(5.8,10.5,12.8%)手术,心肺旁路使用(0.3,2.6,9.8%),术中药物施用,包括依托噻唑(3.0,7.3,12.6%) ,氢质白酮(47.6,26.3,25.2%),氯胺酮(11.2,4.6,3.0%),右嘌呤(18.4,16.6,13.6%),苯妥(74.0,74.8,83.0),肾上腺素(2.0,6.0,18.0%),上萘啶(2.4,7.5,21.2%),瓦向量(3.4,7.6,21.0%),琥珀胆碱(74.0,69.0,61.9%),术中低血压(28.8,33.0,52.3%)和三倍低状态(9.4,30.3, 80.0%)暴露,30天术后死亡率(0.8,2.7,5.6%)。与累积三重低水平暴露相比,在手术后30天内,TVI是一种更好的预测因素,其在手术后30天内死亡或存活(AUC 0.68对0.62,P <0.05)。结论股票相似模式的手术显示不同的患者,程序和结果特征。

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