Evidence map›Paper›PMID 42190694›Full record

ArticleJournal of Korean medical science2026

Predictors of Massive Transfusion in Adult Blunt Trauma Patients: Analysis of a Nationwide Trauma Registry in Korea.

Dongmin Seo, Juyoung Kim, Kyoungwon Jung, Juhong Park, Junsik Kwon, Hye-Min Sohn, Sora Kim, Jayoung Yoo, Jae Hun Kim, Hangjoo Cho and 2 more

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Dongmin Seo *Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea.ORCID https://orcid.org/0009-0009-6716-3959
Juyoung Kim *Division of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea.ORCID https://orcid.org/0000-0002-5442-5106
Kyoungwon JungDivision of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea.ORCID https://orcid.org/0000-0001-7895-0362
Juhong ParkDivision of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea.ORCID https://orcid.org/0000-0003-4574-2203
Junsik KwonDivision of Trauma Surgery, Department of Surgery, Ajou University School of Medicine, Suwon, Korea.ORCID https://orcid.org/0000-0003-3164-4995
Hye-Min SohnGyeonggi South Regional Trauma Center, Ajou University Hospital, Suwon, Korea.ORCID https://orcid.org/0000-0003-3545-3248
Sora KimGyeonggi South Regional Trauma Center, Ajou University Hospital, Suwon, Korea.ORCID https://orcid.org/0000-0001-9787-2339
Jayoung YooGyeonggi South Regional Trauma Center, Ajou University Hospital, Suwon, Korea.ORCID https://orcid.org/0000-0003-0822-1935
Jae Hun KimDepartment of Trauma and Surgical Critical Care, Pusan National University Hospital, Busan, Korea.ORCID https://orcid.org/0000-0003-4504-9898
Hangjoo ChoDivision of Trauma Surgery, Department of Emergency Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0003-3322-744X
Younghwan KimDivision of Surgery, Department of Trauma Surgery, Seoul Regional Trauma Center, National Medical Center, Seoul, Korea.ORCID https://orcid.org/0000-0003-3836-8743
Taegyun KimDepartment of Emergency Medicine, Seoul National University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-3770-3944

Funding

Korea Health Industry Development InstituteMinistry of Health and Welfare HI22C1806
6 · The paper itself

Abstract

backgroundMassive transfusion (MT) is critical for trauma patients with severe hemorrhage; however, predicting the need for MT upon hospital arrival remains challenging. Herein, we aimed to identify predictors of MT in adult blunt trauma patients using data from the Korean Trauma Data Bank (KTDB), a nationwide trauma registry in Korea.

methodsWe retrospectively analyzed data from patients registered in the KTDB from 2017 to 2021. Adult blunt trauma patients who received packed red blood cell (pRBC) transfusion within 24 hours of arrival were included. We divided the patients into the MT and non-MT groups, with MT defined as the administration of ≥ 10 units of pRBCs within 24 hours. We compared the characteristics of the two groups and performed multivariable logistic regression analysis to identify significant predictors of MT, using multiple imputation to address missing data.

resultsAmong 12,145 patients registered in the KTDB, 2,098 (17.3%) received MT. Compared with the non-MT group, the MT group exhibited lower initial systolic blood pressure, lower Glasgow Coma Scale (GCS) scores, and higher heart rates compared to the non-MT group. Multivariable logistic regression analysis identified systolic blood pressure ≤ 90 mmHg (adjusted odds ratio [aOR], 2.34), heart rate ≥ 120 bpm (aOR, 2.15), respiratory rate < 10 or > 29 breaths per minute (aOR, 2.16), GCS < 13 (aOR, 2.45), and a positive Focused Assessment with Sonography for Trauma (FAST) result (aOR, 2.35) as significant predictors of MT upon arrival.

conclusionWe identified initial systolic blood pressure, heart rate, respiratory rate, GCS, and FAST results as significant predictors of MT in adult blunt trauma patients. These predictors may aid in the development of a Korea-specific MT prediction model, contributing to the timely activation of MT protocols and optimization of blood product utilization.

Indexed as

Blood TransfusionErythrocyte TransfusionHemorrhageWounds, NonpenetratingAdultAgedBlood PressureFemaleGlasgow Coma ScaleHeart RateHumansLogistic ModelsMaleMiddle AgedOdds RatioRegistriesBlood TransfusionKoreaPrediction Value of TestsWounds and InjuriesWounds, Nonpenetrating

Identifiers

PMID42190694
PMCPMC13213035

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LicenceCC BY-NC
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Registered trials

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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.