Evidence map›Paper›PMID 40696402›Full record

Observational studyCritical care (London, England)2025

Sub-phenotypes in patients with out-of-hospital cardiac arrest who undergo extracorporeal cardiopulmonary resuscitation: a retrospective observational study from a multicenter registry.

Masahiro Kashiura, Yuki Kishihara, Hiroyuki Tamura, Shunsuke Amagasa, Hideto Yasuda, Takashi Moriya

Abstract readObservational StudyMulticenter Study
In one paragraph

Observational study in Critical care (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Masahiro KashiuraDepartment of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma-cho, Omiya-ku, Saitama, Saitama, 330-8503, Japan. kashiura@me.com.
Yuki KishiharaDepartment of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma-cho, Omiya-ku, Saitama, Saitama, 330-8503, Japan.
Hiroyuki TamuraDepartment of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma-cho, Omiya-ku, Saitama, Saitama, 330-8503, Japan.
Shunsuke AmagasaDivision of Emergency and Transport Services, National Center for Child Health and Development, 2-10-1, Okura, Setagaya-ku, Tokyo, 157-8535, Japan.
Hideto YasudaDepartment of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma-cho, Omiya-ku, Saitama, Saitama, 330-8503, Japan.
Takashi MoriyaDepartment of Emergency and Critical Care Medicine, Saitama Medical Center, Jichi Medical University, 1-847, Amanuma-cho, Omiya-ku, Saitama, Saitama, 330-8503, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOut-of-hospital cardiac arrest (OHCA) has poor survival rates, but extracorporeal cardiopulmonary resuscitation (ECPR) shows promise for selected patients, as a second line of therapy after failure of conventional CPR to obtain return of spontaneous circulation, despite implementation challenges. This study aimed to identify distinct sub-phenotypes among patients with OHCA who undergo ECPR and to investigate their association with clinical outcomes.

methodsThis multi-center, retrospective, observational study used the Japanese Association for Acute Medicine OHCA registry from 83 hospitals that performed ECPR among 91 participating centers between June 2014 and December 2020. We included adult patients with OHCA who received ECPR during cardiac arrest. Three-class latent class analysis (LCA) was employed to identify sub-phenotypes based on 15 variables, including pre- and in-hospital factors. Logistic regression analysis was used to assess the association between sub-phenotypes and 30-day survival and neurological outcomes.

resultsA total of 1528 patients were included. The median low-flow time was 47 min (interquartile rage: 38-58 min). The 30-day survival rate for eligible patients was 20.9%. LCA identified three distinct sub-phenotypes: Standard ECPR Group (n = 702), Delayed ECPR Group (n = 457), and Non-shockable Rhythm Group (n = 369). The variables with high discriminative power in the LCA was low-flow time, followed by pre-hospital shock delivery and initial cardiac rhythm. Thirty-day survival rates varied significantly among the sub-phenotypes (p = 0.001): Standard ECPR Group (26.9%), Delayed ECPR Group (17.1%), and Non-shockable Rhythm Group (14.1%). Favorable neurological outcomes at 30 days also differed significantly (p = 0.004), with the Standard ECPR Group showing the highest rate (12.1%). After adjusting for covariates, both the Delayed ECPR Group (adjusted OR: 0.61, 95% CI 0.44-0.82) and Non-shockable Rhythm Group (adjusted OR: 0.47, 95% CI 0.32-0.68) had significantly lower odds of 30-day survival compared to the Standard ECPR Group.

conclusionsThree clinically meaningful sub-phenotypes were identified using simple pre-hospital and in-hospital factors, with low-flow time emerging as the most critical discriminating factor. The sub-phenotypes showed significant associations with clinical outcomes and provide a practical framework for ECPR patient stratification. These findings suggest that timing optimization may be as important as rhythm characteristics for ECPR patient selection and support the development of sub-phenotype-specific treatment strategies.

Indexed as

Cardiopulmonary ResuscitationExtracorporeal Membrane OxygenationOut-of-Hospital Cardiac ArrestPhenotypeAgedFemaleHumansJapanLogistic ModelsMaleMiddle AgedRegistriesRetrospective StudiesCardiac arrestExtracorporeal cardiopulmonary resuscitationLatent class analysisSub-phenotype

Identifiers

PMID40696402
PMCPMC12281804

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.