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. 2023 Jun 9;13(1):49.
doi: 10.1186/s13613-023-01143-8.

Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis

Yannick Binois  1   2 , Marie Renaudier  1   2 , Florence Dumas  1   2   3 , Younès Youssfi  2   4 , Frankie Beganton  1   2 , Daniel Jost  1   2   5 , Lionel Lamhaut  1   2   6 , Eloi Marijon  1   2   7 , Xavier Jouven  1   2   7 , Alain Cariou  1   8   2   9 , Wulfran Bougouin  10   11   12   13 ; Sudden-Death-Expertise-Center investigators
Collaborators, Affiliations

Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis

Yannick Binois et al. Ann Intensive Care. .

Abstract

Background: Out-of-hospital cardiac arrest (OHCA) is a common cause of death. Early circulatory failure is the most common reason for death within the first 48 h. This study in intensive care unit (ICU) patients with OHCA was designed to identify and characterize clusters based on clinical features and to determine the frequency of death from refractory postresuscitation shock (RPRS) in each cluster.

Methods: We retrospectively identified adults admitted alive to ICUs after OHCA in 2011-2018 and recorded in a prospective registry for the Paris region (France). We identified patient clusters by performing an unsupervised hierarchical cluster analysis (without mode of death among the variables) based on Utstein clinical and laboratory variables. For each cluster, we estimated the hazard ratio (HRs) for RPRS.

Results: Of the 4445 included patients, 1468 (33%) were discharged alive from the ICU and 2977 (67%) died in the ICU. We identified four clusters: initial shockable rhythm with short low-flow time (cluster 1), initial non-shockable rhythm with usual absence of ST-segment elevation (cluster 2), initial non-shockable rhythm with long no-flow time (cluster 3), and long low-flow time with high epinephrine dose (cluster 4). RPRS was significantly associated with this last cluster (HR, 5.51; 95% confidence interval 4.51-6.74).

Conclusions: We identified patient clusters based on Utstein criteria, and one cluster was strongly associated with RPRS. This result may help to make decisions about using specific treatments after OHCA.

Keywords: Mode of death; Personalized medicine; Post-resuscitation; Shock; Sudden death.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Patient flowchart
Fig. 2
Fig. 2
Heatmap (v-test score scale) of clinical and laboratory variables in each of the four clusters. A V-test score ≥ 1.96 or ≤ − 1.96 was taken as the cutoff indicating variable over- or underrepresentation in clusters. For example, in cluster 1, a first-recorded shockable rhythm was significantly overrepresented (V-test score, 33; blue color), whereas no-flow time was shorter than in the other clusters (V-test score, − 14.9; red color)
Fig. 3
Fig. 3
Biplot representation of clinical and laboratory variables in each of the four clusters. PCA principal component analysis, Dim dimension
Fig. 4
Fig. 4
Vital status and reasons for death in each of the four clusters. WLST withdrawal of life-sustaining treatments
Fig. 5
Fig. 5
Cumulative incidence of refractory postresuscitation shock (RPRS) in each of the four clusters
See this image and copyright information in PMC

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