Evidence map›Paper›PMID 41430615›Full record

ArticleCritical care (London, England)2025

Intra-arrest transport versus continued on-scene resuscitation in patients with out-of-hospital cardiac arrest by first documented rhythm: a nationwide cohort study using time-dependent propensity score sequential matching.

Yoshimitsu Shimomura, Sho Komukai, Ling Zha, Kosuke Kiyohara, Tadaharu Shiozumi, Tasuku Matsuyama, Tetsuhisa Kitamura

Abstract readComparative Study
In one paragraph

Article 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 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yoshimitsu ShimomuraDivision of Environmental Medicine and Population Sciences, Department of Social Medicine, Graduate School of Medicine, Osaka University, Suita, 565-0871, Osaka, Japan.
Sho KomukaiDepartment of Health Data Science, Tokyo Medical University, Tokyo, Japan.
Ling ZhaDivision of Environmental Medicine and Population Sciences, Department of Social Medicine, Graduate School of Medicine, Osaka University, Suita, 565-0871, Osaka, Japan.
Kosuke KiyoharaDepartment of Food Science, Faculty of Home Economics, Otsuma Women's University, Tokyo, Japan.
Tadaharu ShiozumiDepartment of Emergency Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Tasuku MatsuyamaDepartment of Emergency Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Tetsuhisa KitamuraDivision of Environmental Medicine and Population Sciences, Department of Social Medicine, Graduate School of Medicine, Osaka University, Suita, 565-0871, Osaka, Japan. lucky_unatan@yahoo.co.jp.

Funding

Japan Society for the Promotion of Science 22K09139
6 · The paper itself

Abstract

back groundWhether to transport patients during cardiac arrest or to prioritize on-scene resuscitation presents a critical dilemma. This study aims to evaluate the association between intra-arrest transport versus continued on-scene resuscitation, and survival after out-of-hospital cardiac arrest (OHCA) using time-dependent propensity score sequential matching.

methodWe consecutively collected data on adult OHCA between 2021 and 2022 using a nationwide, prospective, population-based registry of out-of-hospital cardiac arrest in Japan. Patients with OHCA were divided into two cohorts based on their first documented electrocardiographic rhythm: shockable and nonshockable. We performed a time-dependent propensity score-matching analysis to address resuscitation bias and differences in background characteristics. Patients undergoing intra-arrest transport were matched with patients at risk of intra-arrest transport (continued on-scene resuscitation) at the same time in each cohort. Then, outcomes between the matched groups were compared. The primary endpoint was survival at one month or discharge from the hospital within one month.

resultsA total of 13,826 patients with shockable rhythm and 187,036 patients with non-shockable rhythm were eligible for our analysis. After time-dependent propensity score matching, the matched cohorts were well-balanced. More than 90% of patients initially assigned to continued on-scene resuscitation later underwent intra-arrest transport. In the shockable cohort, the corrected risk ratio (RR) for the primary endpoint in the intra-arrest transport group compared with the continued on-scene resuscitation group was 1.03 (0.96–1.10, P = 0.443). In the nonshockable cohort, the corrected RR for the primary endpoint in the intra-arrest transport group compared with the continued on-scene resuscitation group was 0.84 (0.78–0.89, P < 0.001) (P for interaction: <0.001).

conclusionIntra-arrest transport and continued on-scene resuscitation showed similar survival among patients with shockable rhythms, whereas continued on-scene resuscitation was associated with better survival among patients with nonshockable rhythms. Given the high rate and short delay of subsequent intra-arrest transport in the continued on-scene resuscitation group, our analysis more closely reflects a comparison of earlier versus later intra-arrest transport during ongoing on-scene resuscitation.

Indexed as

Cardiopulmonary ResuscitationOut-of-Hospital Cardiac ArrestTransportation of PatientsAgedAged, 80 and overDefibrillatorsFemaleHumansJapanMaleMiddle AgedPatient DischargePractice Guidelines as TopicPropensity ScoreProspective StudiesRegistriesFirst documented electrocardiographic rhythmIntra-arrest transport versus continued on-scene resuscitationOut-of-hospital cardiac arrestTime-dependent propensity score-matching analysis

Identifiers

PMID41430615
PMCPMC12837028

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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.