Gaining consensus on expert rule statements for acute respiratory failure digital twin patient model in intensive care unit using a Delphi method.
Gaining consensus on expert rule statements for acute respiratory failure digital twin patient model in intensive care unit using a Delphi method.
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DOI：
10.17305/bb.2023.9344
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发表时间：
2023-11-03
期刊：
影响因子：
--
通讯作者：
Lal, Amos
中科院分区：
文献类型：
--
作者：
Montgomery, Amy J.;Litell, John;Dang, Johnny;Flurin, Laure;Gajic, Ognjen;Lal, Amos
数字孪生技术是对物理产品的虚拟描绘，已在许多领域得到应用。医疗保健中的数字孪生患者模型是一个虚拟患者，它提供了虚拟测试各种干预措施结果的机会，而不会让实际患者受到可能的伤害。这可以在重症监护病房 (ICU) 的复杂环境中作为决策辅助。我们的目标是在多学科专家小组中就导致内科 ICU 呼吸衰竭的呼吸病理生理学声明达成共识。我们召集了一个由 34 名国际重症监护专家组成的小组。我们的小组使用有向无环图（DAG）对呼吸衰竭病理生理学的要素进行建模，并得出描述相关 ICU 临床实践的专家陈述。专家们参与了三轮修改后的德尔菲法，以使用李克特量表评估对 78 个最终问题（13 个陈述，每个陈述 6 个子陈述）的一致性。经过修改的 Delphi 流程就 62 条最终专家规则声明达成了一致。一致程度最高的陈述包括生理学、气道阻塞管理、肺泡通气减少和通气-灌注匹配。最低的一致陈述涉及休克和由于耗氧量增加和死腔导致的低氧性呼吸衰竭之间的关系。我们的研究证明了改进的德尔菲法在达成共识以创建专家规则声明以进一步开发急性呼吸衰竭数字双胞胎患者模型方面的实用性。数字孪生设计中使用的绝大多数专家规则语句与危重患者呼吸衰竭的专家知识相一致。
Digital twin technology is a virtual depiction of a physical product and has been utilized in many fields. Digital twin patient model in healthcare is a virtual patient that provides opportunities to test the outcomes of various interventions virtually without subjecting an actual patient to possible harm. This can serve as a decision aid in the complex environment of the intensive care unit (ICU). Our objective is to develop consensus among a multidisciplinary expert panel on statements regarding respiratory pathophysiology contributing to respiratory failure in the medical ICU. We convened a panel of 34 international critical care experts. Our group modeled elements of respiratory failure pathophysiology using directed acyclic graphs (DAGs) and derived expert statements describing associated ICU clinical practices. The experts participated in three rounds of modified Delphi to gauge agreement on 78 final questions (13 statements with 6 substatements for each) using a Likert scale. A modified Delphi process achieved agreement for 62 of the final expert rule statements. Statements with the highest degree of agreement included the physiology, and management of airway obstruction decreasing alveolar ventilation and ventilation-perfusion matching. The lowest agreement statements involved the relationship between shock and hypoxemic respiratory failure due to heightened oxygen consumption and dead space. Our study proves the utility of a modified Delphi method to generate consensus to create expert rule statements for further development of a digital twin-patient model with acute respiratory failure. A substantial majority of expert rule statements used in the digital twin design align with expert knowledge of respiratory failure in critically ill patients.
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影响因子：
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作者：
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通讯作者：
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作者：
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期刊：
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影响因子：
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