Personalized Mechanical Ventilation for the Injured Lung
针对受损肺部的个性化机械通气
基本信息
- 批准号:9232202
- 负责人:
- 金额:$ 58.72万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-08-01 至 2019-03-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdult Respiratory Distress SyndromeAlgorithmsBiologicalBlood gasBody WeightCharacteristicsClinicalComputer SimulationDataDevelopmentDiagnosisDiseaseEnvironmental air flowEpithelialFeedbackGoalsIndividualInfectionInjuryLeadLiquid substanceLungMeasuresMechanical ventilationMechanicsModalityModelingNaturePatientsPharmacologic SubstancePharmacy (field)ProcessProne PositionProteinsRandomized Clinical TrialsRecruitment ActivityRegimenRespiratory FailureRunningSeminalSeveritiesStressStructure of parenchyma of lungSupportive careTestingTidal VolumeTimeTissuesTraumaVentilator-induced lung injuryVolutraumaWeightatelectraumabasedesigneffective therapyelectric impedanceexpirationhuman subjectimprovedimproved outcomeindividual patientinjuredlung injurymechanical behaviormechanical propertiesmortalitymouse modelnovelnovel therapeuticspatient populationpersonalized approachpersonalized strategiespressurepreventpublic health relevanceresponsestandard of caretranslation to humans
项目摘要
DESCRIPTION (provided by applicant): Acute respiratory distress syndrome (ARDS) is a common and often fatal condition for which there is no effective treatment other than supportive care centered on mechanical ventilation. Mechanical ventilation itself, however, can easily cause damage to already injured lung tissues, leading to ventilator-induced lung injury (VILI). The principle goal in managing ARDS is thus to administer mechanical ventilation in a manner that avoids, or at least minimizes, VILI. The standard of care in ARDS involves use of small tidal volumes (Vt), the current ideal being 6 ml/kg ideal body weight, together with positive end-expiration pressure (PEEP) to prevent lung collapse and improve oxygenation. These strategies have led to improved outcomes, but ARDS mortality remains high, so better approaches to mechanically ventilating the injured lung are desperately needed. Unfortunately, continuing to search for one-size-fits-all approaches to mechanical ventilation of the very heterogeneous ARDS patient population is rapidly becoming futile because of the huge number of patients that would be needed to obtain statistically significant improvements over current strategies. For this reason, the search for improved approaches to mechanical ventilation in ARDS must focus on strategies that can be tailored to suit the pathophysiological characteristics of individual patiens. Furthermore, such strategies must be adaptable to the evolving nature and severity of ARDS as it runs its course. These considerations lead us to propose that personalized mechanical ventilation of the ARDS patient must take place within an ongoing feedback loop involving three interdependent processes: 1) assessing the injury status of a given lung, 2) predicting how much VILI will be caused in that lung by a given regimen of mechanical ventilation, and 3) optimizing ventilation to be minimally injurious based on the information provided in steps 1 and 2. This will allow the imposed regimen of mechanical ventilation to be responsive to the ventilatory needs of the patient, while at the same time minimizing the amount of VILI that is produced so that the patient's own reparative processes have the best chances of prevailing. We have undertaken extensive prior studies that show we can assess the current state of injury of the lung most effectively by measuring how its mechanical properties change over time as a result of ongoing recruitment and derecruitment. We have also developed computational models showing how it is, in principle, possible to predict the amount of VILI that will be produced by a given regimen of mechanical ventilation. Our overarching goal in this proposal is to leverage these findings to optimize the personalized design of mechanical ventilation strategies for the injured lung. This goal will be pursued experimentally in mouse models of ARDS and VILI, and computationally by fitting the data obtained to computational models of lung mechanics and VILI development.
描述(申请人提供):急性呼吸窘迫综合征(ARDS)是一种常见的、通常是致命的疾病,除了以机械通气为中心的支持性护理外,没有有效的治疗方法。然而,机械通气本身很容易对已经受损的肺组织造成损害,导致呼吸机诱导的肺损伤(VILI)。因此,管理ARDS的主要目标是以一种避免或至少最小化VILI的方式实施机械通风。ARDS的护理标准包括使用小潮气量(Vt),目前的理想情况是6ml/kg理想体重,加上正末呼气压力(PEEP)以防止肺衰竭和改善氧合。这些策略已经改善了预后,但ARDS的死亡率仍然很高,因此迫切需要更好的方法来机械通风受伤的肺。不幸的是,继续为非常不同的ARDS患者群体寻找一刀切的机械通气方法正迅速变得徒劳,因为需要大量的患者才能在统计上比目前的策略有显著的改善。因此,在ARDS中寻找更好的机械通气方法必须集中在可以量身定制的策略上,以适应个别患者的病理生理特征。此外,这种战略必须适应急性呼吸窘迫综合征的演变性质和严重性。考虑到这些因素,我们建议ARDS患者的个性化机械通气必须在持续的反馈循环中进行,涉及三个相互依赖的过程:1)评估给定肺的损伤状态,2)预测给定的机械通气方案将对该肺造成多少VILI,以及3)根据步骤1和2中提供的信息将机械通气优化为最小损伤。这将使实施的机械通气方案对患者的呼吸需求做出反应,同时最大限度地减少VILI的产生,从而使患者自己的修复过程具有最好的机会。我们已经进行了大量的前期研究,这些研究表明,我们可以通过测量肺的机械性能随时间的变化来最有效地评估当前肺损伤的状态,这是持续招募和解除肺损伤的结果。我们还开发了计算模型,展示了如何在原则上预测给定的机械通风方案所产生的VILI量。我们在这项建议中的首要目标是利用这些发现来优化受伤肺的机械通气策略的个性化设计。这一目标将在ARDS和VILI的小鼠模型上进行实验,并通过将获得的数据与肺力学和VILI发育的计算模型进行匹配来进行计算。
项目成果
期刊论文数量(9)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Dynamic Mechanical Interactions Between Neighboring Airspaces Determine Cyclic Opening and Closure in Injured Lung.
- DOI:10.1097/ccm.0000000000002234
- 发表时间:2017-04
- 期刊:
- 影响因子:8.8
- 作者:Broche L;Perchiazzi G;Porra L;Tannoia A;Pellegrini M;Derosa S;Sindaco A;Batista Borges J;Degrugilliers L;Larsson A;Hedenstierna G;Wexler AS;Bravin A;Verbanck S;Smith BJ;Bates JH;Bayat S
- 通讯作者:Bayat S
Entropy Production and the Pressure-Volume Curve of the Lung.
- DOI:10.3389/fphys.2016.00073
- 发表时间:2016
- 期刊:
- 影响因子:4
- 作者:Oliveira CL;Araújo AD;Bates JH;Andrade JS Jr;Suki B
- 通讯作者:Suki B
Modeling Lung Derecruitment in VILI Due to Fluid-Occlusion: The Role of Emergent Behavior.
- DOI:10.3389/fphys.2020.542744
- 发表时间:2020
- 期刊:
- 影响因子:4
- 作者:Mori V;Smith BJ;Suki B;Bates JHT
- 通讯作者:Bates JHT
Design and nonlinear modeling of a sensitive sensor for the measurement of flow in mice.
用于测量小鼠流量的灵敏传感器的设计和非线性建模。
- DOI:10.1088/1361-6579/aacb1b
- 发表时间:2018-07-03
- 期刊:
- 影响因子:3.2
- 作者:Jawde SB;Smith BJ;Sonnenberg A;Bates JHT;Suki B
- 通讯作者:Suki B
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Jason HT Bates其他文献
Jason HT Bates的其他文献
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{{ truncateString('Jason HT Bates', 18)}}的其他基金
Mathematical and Computational Predictive Modeling Core
数学和计算预测建模核心
- 批准号:
10021010 - 财政年份:2018
- 资助金额:
$ 58.72万 - 项目类别:
Preserving Epithelial Barrier Integrity in Ventilator-Induced Lung Injury
在呼吸机引起的肺损伤中保持上皮屏障的完整性
- 批准号:
10186793 - 财政年份:2018
- 资助金额:
$ 58.72万 - 项目类别:
Mathematical and Computational Predictive Modeling Core
数学和计算预测建模核心
- 批准号:
10256815 - 财政年份:2018
- 资助金额:
$ 58.72万 - 项目类别:
Non-Allergic Late-Onset Asthma of Obesity: Pathophysiology and Therapy
肥胖引起的非过敏性迟发型哮喘:病理生理学和治疗
- 批准号:
9243305 - 财政年份:2016
- 资助金额:
$ 58.72万 - 项目类别:
Personalized Mechanical Ventilation for the Injured Lung
针对受损肺部的个性化机械通气
- 批准号:
9026498 - 财政年份:2014
- 资助金额:
$ 58.72万 - 项目类别:
Personalized Mechanical Ventilation for the Injured Lung
针对受损肺部的个性化机械通气
- 批准号:
8766263 - 财政年份:2014
- 资助金额:
$ 58.72万 - 项目类别:
A multi-scale approach to airway hyperresponsiveness: from molecule to organ
气道高反应性的多尺度方法:从分子到器官
- 批准号:
8502325 - 财政年份:2010
- 资助金额:
$ 58.72万 - 项目类别:
A multi-scale approach to airway hyperresponsiveness: from molecule to organ
气道高反应性的多尺度方法:从分子到器官
- 批准号:
8135440 - 财政年份:2010
- 资助金额:
$ 58.72万 - 项目类别:
A multi-scale approach to airway hyperresponsiveness: from molecule to organ
气道高反应性的多尺度方法:从分子到器官
- 批准号:
8322649 - 财政年份:2010
- 资助金额:
$ 58.72万 - 项目类别:
A multi-scale approach to airway hyperresponsiveness: from molecule to organ
气道高反应性的多尺度方法:从分子到器官
- 批准号:
7932703 - 财政年份:2010
- 资助金额:
$ 58.72万 - 项目类别:
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