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Model-based prediction of the patient-specific response to adrenaline

机译:基于模型的对肾上腺素的患者特异性反应的预测

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摘要

A model for the cardiovascular and circulatory systems has previously been validated in simulated cardiac andcirculatory disease states. It has also been shown to accurately capture the main hemodynamic trends in porcine models of pulmonary embolism and PEEP (positive end-expiratory pressure) titrations at different volemic levels. In this research, the existing model and parameter identification process are used to study the effect of different adrenaline doses in healthyand critically ill patient populations, and to develop a means of predicting the hemodynamic response to adrenaline. The hemodynamic effects on arterial blood pressures and stroke volume (cardiac index) are simulated in the model and adrenaline-specific parameters are identified. The dose dependent changes in these parameters are then related to adrenaline dose using data from studies published in the literature. These relationships are then used to predict the future,patient-specific response to a change in dose or over time periods from 1-12 hours. The results are compared to data from 3 published adrenaline dosing studies comprising a total of 37 data sets. Absolute percentage errors for the identified model are within 10% when re-simulated and compared to clinical data for all cases. All identified parameter trends matchclinically expected changes. Absolute percentage errors for the predicted hemodynamic responses (N=15) are also within 10% when re-simulated and compared to clinical data. Clinically accurate prediction of the effect of inotropic circulatory support drugs, such as adrenaline, offers significant potential for this type of model-based application. Overall, this work represents a further clinical, proof of concept, of the underlying fundamental mathematical model, methods and approach,as well as providing a template for using the model in clinical titration of adrenaline in a decision support role in critical care. They are thus a further justification in support of upcoming human clinical trials to validate this model.
机译:先前已经在模拟的心脏和循环系统疾病状态下验证了心血管和循环系统的模型。在不同的血栓水平,在肺栓塞和PEEP(正呼气末正压)滴定的猪模型中,它也能准确捕获主要的血流动力学趋势。在这项研究中,使用现有的模型和参数识别过程来研究不同剂量的肾上腺素在健康和危重患者群体中的作用,并开发一种预测对肾上腺素的血液动力学反应的方法。在模型中模拟对动脉血压和中风量(心脏指数)的血流动力学影响,并识别肾上腺素特异性参数。然后,使用文献中发表的研究数据,将这些参数的剂量依赖性变化与肾上腺素剂量相关。然后将这些关系用于预测未来患者对剂量变化或1-12小时内特定时间变化的反应。将结果与来自3个已发布的肾上腺素剂量研究的数据进行比较,该研究包括总共37个数据集。重新模拟并与所有病例的临床数据进行比较后,所识别模型的绝对百分比误差在10%以内。所有识别出的参数趋势均符合临床预期变化。重新模拟并与临床数据比较,预测的血液动力学反应的绝对百分比误差(N = 15)也在10%以内。临床上对正性肌循环支持药物(例如肾上腺素)效果的准确预测为这种基于模型的应用提供了巨大的潜力。总体而言,这项工作代表了基础数学模型,方法和方法的进一步临床概念验证,并提供了在肾上腺素临床滴定中使用该模型以在重症监护中起决策支持作用的模板。因此,它们是支持即将进行的人类临床试验以验证该模型的进一步理由。

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