Evidence mapPaperPMID 40903408Full record

ArticleAcute and critical care2025

Initial arterial pH predicts survival of out-of-hospital cardiac arrest in South Korea.

Daun Jeong, Sang Do Shin, Tae Gun Shin, Gun Tak Lee, Jong Eun Park, Sung Yeon Hwang, Jin-Ho Choi

Registry-linked trialAbstract read
In one paragraph

Article in Acute and critical care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03222999 (Korean Cardiac Arrest Research Consortium), which is not on this map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing 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.

NCT03222999 recruitingnot on this map

Korean Cardiac Arrest Research Consortium

Typeobservational_patient_registrySponsorKorean Cardiac Arrest Research ConsortiumRan2015 to 2030Enrolled30,000ConditionsOut-of-Hospital Cardiac ArrestArmsNo intervention planned
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Daun JeongDivision of Critical Care Medicine, Department of Emergency Medicine, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong, Korea.
Sang Do ShinDepartment of Emergency Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Tae Gun ShinDepartment of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Gun Tak LeeDepartment of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Jong Eun ParkDepartment of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Sung Yeon HwangDepartment of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Jin-Ho ChoiDepartment of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArterial pH reflects both metabolic and respiratory distress in cardiac arrest and has prognostic implications. However, it was excluded from the 2024 update of the Utstein out-of-hospital cardiac arrest (OHCA) registry template. We investigated the rationale for including arterial pH into models predicting clinical outcomes.

methodsData were sourced from the Korean Cardiac Arrest Research Consortium, a nationwide OHCA registry (NCT03222999). Prediction models were constructed using logistic regression, random forest, and eXtreme Gradient Boosting frameworks. Each framework included three model types: pH, low-flow time, and combined models. Then the area under the receiver operating characteristic curve (AUROC) of each predicting model was compared. The primary outcome was 30- day death or neurologically unfavorable status (cerebral performance category ≥3).

resultsAmong the 15,765 patients analyzed, 92.2% experienced death or unfavorable neurological outcomes. The predicting performance of the models including pH (AUROC, 0.92-0.94) were comparable to the models including low-flow time in all frameworks (0.93-0.94) (all P>0.05). Inclusion of pH into low-flow time models consistently showed higher AUROCs than individual models in all frameworks (AUROC, 0.93-0.95; all P<0.05).

conclusionsThe predicting performance of models including arterial pH was comparable to models including low-flow time, and addition of arterial pH into low-flow time models could increase the performance of the models. Key Words: blood pH; hydrogen-ion con.

Indexed as

blood pHhydrogen-ion concentrationmachine learningout-of-hospital cardiac arrestprognosisresuscitation

Identifiers

PMID40903408
PMCPMC12408451

What Socratic holds

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Registered trials

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 Socratic graph.