Evidence map›Paper›PMID 41102718›Full record

ArticleCritical care (London, England)2025

Therapeutic target of high fresh frozen plasma to red blood cell ratio in severe blunt trauma.

Gaku Fujiwara, Kosuke Inoue, Wataru Ishii, Tadashi Echigo, Shoji Yokobori, Naoto Shiomi, Naoya Hashimoto, Shigeru Ohtsuru, Yohei Okada

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
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. Not yet cited in PubMed.

0numbers the graph read from it
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.

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

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

9 authors.

Gaku FujiwaraDepartment of Neurosurgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kamigyo-ku, Kyoto, Japan. gfujiwara-tuk@umin.ac.jp.
Kosuke InoueDepartment of Social Epidemiology, School of Public Health, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Wataru IshiiDepartment of Emergency Medicine and Critical Care, Japanese Red Cross Society Kyoto Daini Hospital, Kyoto, Japan.
Tadashi EchigoNational Health Insurance Yamato Clinic, Kagoshima, Japan.
Shoji YokoboriDepartment of Emergency and Critical Care Medicine, Nippon Medical School, Tokyo, Japan.
Naoto ShiomiDepartment of Critical and Intensive Care Medicine, Shiga University of Medical Science, Shiga, Japan.
Naoya HashimotoDepartment of Neurosurgery, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kamigyo-ku, Kyoto, Japan.
Shigeru OhtsuruDepartment of Primary Care and Emergency Medicine, Kyoto University, Kyoto, Japan.
Yohei OkadaDepartment of Preventive Services, School of Public Health, Kyoto University, Kyoto, Japan.

Funding

Japan Society for the Promotion of Science JP25K24218
6 · The paper itself

Abstract

backgroundTo assess heterogeneous treatment effects of high fresh frozen plasma (FFP) to red blood cell (RBC) transfusion ratios in patients with severe blunt trauma and to identify subgroups that derive the greatest survival benefit.

methodsThis multicenter retrospective cohort study used data from the Japan Trauma Data Bank (2019–2023). Adults with severe blunt trauma (Injury Severity Score ≥ 16) who received transfusions were included. Patients were categorized into high-FFP (FFP:RBC > 1) and low-FFP (FFP:RBC ≤ 1) groups. A causal forest machine learning model was applied to a derivation cohort (2019–2021) to estimate conditional average treatment effects (CATEs) and identify subgroups with the highest predicted benefit. Findings were validated in a separate cohort (2022–2023).

resultsAmong 6,679 patients, in-hospital mortality was 23.3% in the derivation and 23.2% in the validation cohort. Causal forest analysis revealed lactate level and Glasgow Coma Scale (GCS) score as key effect modifiers. A therapeutic target subgroup—defined as lactate ≥ 4.5 mmol/L and GCS ≤ 12—comprised 20.7% of the validation cohort. This subgroup showed a substantially greater mortality reduction with high-FFP transfusion (risk difference –13.3%, 95% CI –22.4 to –4.2%; number needed to treat [NNT] 7.5), compared with the overall cohort (risk difference –3.3%, 95% CI –6.7 to 0.5%; NNT 32.1). Results were consistent across sensitivity analyses.

conclusionsHigh FFP-to-RBC transfusion ratios may confer the greatest benefit in patients with impaired consciousness and metabolic acidosis. Identifying high-benefit subgroups using machine learning could support more individualized transfusion strategies in trauma care.

Indexed as

PlasmaWounds, NonpenetratingAdultAgedCohort StudiesFemaleGlasgow Coma ScaleHospital MortalityHumansInjury Severity ScoreJapanMaleMiddle AgedRetrospective StudiesBlood product ratioBlunt traumaCausal forestCoagulopathyFresh frozen plasmaHeterogeneous treatment effectMachine learningMassive transfusionMultiple traumaTransfusion

Identifiers

PMID41102718
PMCPMC12532888

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.