2021 Fiscal Year Final Research Report

Investigation of blood data and advanced intensive cares among out-of-hospital cardiac arrest patients for contributing to the revised cardiopulmonary resuscitation guidelines

Research Project

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Project/Area Number	19K09393
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Review Section	Basic Section 55060:Emergency medicine-related
Research Institution	Osaka University
Principal Investigator	Kitamura Tetsuhisa 大阪大学, 医学系研究科, 准教授 (30639810)
Project Period (FY)	2019-04-01 – 2022-03-31
Keywords	蘇生科学 / 臨床疫学 / 救急医学 / レジストリ研究
Outline of Final Research Achievements	This study assessed the effects of blood data and advanced intensive cares among patients with out-of-hospital cardiac arrest (OHCA) for contributing to the revised cardiopulmonary resuscitation guidelines, and has enrolled 12,594 OHCA patients from critical care medical centers in Osaka Prefecture. In a total of 1,169 adult OHCA patients with initial shockable rhythm, three sub-phenotypes (Groups 1, 2, and 3) were identified, mainly characterized by the distribution of partial pressure of O2 and CO2 values of blood gas assessment, cardiac rhythm on hospital arrival, and estimated glomerular filtration rate. The 30-day survival outcomes were varied across the groups: 15.7% in Group 1; 30.7% in Group 2; and 85.9% in Group 3, by using a machine learning-based unsupervised cluster analysis. These results were validated using the validation dataset. This concept of sub-phenotypes might be valuable when considering the appropriate target population of advanced intensive cares.
Free Research Field	臨床疫学
Academic Significance and Societal Importance of the Research Achievements	機械学習クラスタ分析によって、危険因子や臨床的特徴、治療に対する反応が異なる表現型を持つ院外心停止患者の臨床的サブフェノタイプを特定することは、病院搬送後高度集中治療の効果の異質性を探ることに関連し、その死亡を下げる臨床応用につながる可能性がある。潜在性クラスタ分析はサブフェノタイプを特定するために多次元的な臨床因子を考慮できる点で優れている。本多施設共同研究は、病院到着前の初期心電図波形が心室細動である院外心停止患者のサブフェノタイプを評価した最初の研究であり、その臨床的特徴の同定は、院外心停止患者の予後改善のための高度集中治療の適切な対象者を検討する上で有用な可能性がある。