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Model-based PEEP selection in mechanically ventilated patients — First clinical trial results

机译:机械通气患者基于模型的PEEP选择-首次临床试验结果

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Background: Current methods to treat acute respiratory distress syndrome (ARDS) and acute lung injury (ALI) do not provide standardised approaches to optimise positive end expiratory pressure (PEEP). Mathematical models provide a means to optimise PEEP selection. A clinical trial is conducted to validate mathematical models that enable PEEP selection based on alveolar recruitability. Methods: Patients diagnosed with ARDS and ALI were enrolled in a single centre study. A specialised recruitment manoeuvre was performed starting from zero PEEP (ZEEP) in increments of 5 cmH2O, finishing with PEEP that produced a peak airway pressure = 45 cmH2O. The trial used volume controlled ventilation using low tidal volumes of 6 ml per kilogram (max 500 mls). Raw pressure volume (PV) data measured by a pneumatachometer were used in a mathematical model to estimate alveolar recruitment, alveolar recruitability, and to then determine an optimal PEEP. Data from 3 patients recruited to date are used to provide initial validation and define a novel means of selecting PEEP based on current and predicted alveolar recruitment. This study was approved by the New Zealand Upper South Island A Regional Ethics Committee. Results: Optimal PEEP levels for Patients 1 and 3 ranged from 15 to 20 cmH2O. Optimal PEEP for Patient 2 ranged more broadly from 10 to 20 cmH2O. Clinically selected values were 10, 12 and 10 cmH2O respectively. The model also allowed the clinician to detect some mechanical failures. Conclusions: The choice of optimal PEEP for ARDS/ALI patients is highly debated, clinician-specific, and variable, resulting in variable care, length of stay and outcome. This paper provides a model-based method to protocolise the optimization of PEEP based on accepted clinical goals and patient-specific physiological response. Further validation on more patients will be required to support these initial, promising results.
机译:背景:目前治疗急性呼吸窘迫综合征(ARDS)和急性肺损伤(ALI)的方法尚未提供标准化方法来优化呼气末正压(PEEP)。数学模型提供了一种优化PEEP选择的方法。进行了一项临床试验,以验证能够基于肺泡可募集性选择PEEP的数学模型。方法:将诊断为ARDS和ALI的患者纳入一项单中心研究。从零PEEP(ZEEP)开始以5 cmH2O的增量进行专门的招募策略,最后以PEEP产生气道峰值压力= 45 cmH2O。该试验使用风量控制通风,潮气量低至每公斤6毫升(最大500毫升)。由气压计测量的原始压力体积(PV)数据用于数学模型中,以估算肺泡补充,肺泡补充能力,然后确定最佳PEEP。迄今已招募的3名患者的数据用于提供初始验证,并定义了一种基于当前和预测的肺泡招募选择PEEP的新颖方法。这项研究已得到新西兰上南岛A地区道德委员会的批准。结果:患者1和3的最佳PEEP水平为15至20 cmH2O。患者2的最佳PEEP范围从10到20 cmH2O。临床选择的值分别为10、12和10 cmH2O。该模型还允许临床医生检测到一些机械故障。结论:ARDS / ALI患者最佳PEEP的选择一直存在争议,临床医生具有针对性,而且存在差异,从而导致护理,住院时间和结局均存在差异。本文提供了一种基于模型的方法,以基于公认的临床目标和患者特定的生理反应来优化PEEP。为了支持这些初步的,有希望的结果,将需要对更多患者进行进一步验证。

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