Evidence map›Paper›PMID 40087116›Full record

ArticleChinese journal of traumatology = Zhonghua chuang shang za zhi2025

Construction and preliminary trial test of a decision-making app for pre-hospital damage control resuscitation.

Haoyang Yang, Wenqiong Du, Zhaowen Zong, Xin Zhong, Yijun Jia, Renqing Jiang, Chenglin Dai, Zhao Ye

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In one paragraph

Article in Chinese journal of traumatology = Zhonghua chuang shang za zhi, 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

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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

8 authors.

Haoyang YangState Key Laboratory of Trauma, Burn and Combined Injury, Department for Combat Casualty Care Training, Army Medical University, Chongqing, 400038, China.
Wenqiong DuState Key Laboratory of Trauma, Burn and Combined Injury, Department for Combat Casualty Care Training, Army Medical University, Chongqing, 400038, China.
Zhaowen ZongState Key Laboratory of Trauma, Burn and Combined Injury, Department for Combat Casualty Care Training, Army Medical University, Chongqing, 400038, China. Electronic address: zongzhaowen@163.com.
Xin ZhongState Key Laboratory of Trauma, Burn and Combined Injury, Department for Combat Casualty Care Training, Army Medical University, Chongqing, 400038, China.
Yijun JiaState Key Laboratory of Trauma, Burn and Combined Injury, Department for Combat Casualty Care Training, Army Medical University, Chongqing, 400038, China.
Renqing JiangState Key Laboratory of Trauma, Burn and Combined Injury, Department for Combat Casualty Care Training, Army Medical University, Chongqing, 400038, China.
Chenglin DaiState Key Laboratory of Trauma, Burn and Combined Injury, Department for Combat Casualty Care Training, Army Medical University, Chongqing, 400038, China.
Zhao YeState Key Laboratory of Trauma, Burn and Combined Injury, Department for Combat Casualty Care Training, Army Medical University, Chongqing, 400038, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo construct a decision-making app for pre-hospital damage control resuscitation (PHDCR) for severely injured patients, and to make a preliminary trial test on the effectiveness and usability aspects of the constructed app.

methodsDecision-making algorithms were first established by a thorough literature review, and were then used to be learned by computer with 3 kinds of text segmentation algorithms, i.e., dictionary-based segmentation, machine learning algorithms based on labeling, and deep learning algorithms based on understanding. B/S architecture mode and Spring Boot were used as a framework to construct the app. A total of 16 Grade-5 medical students were recruited to test the effectiveness and usability aspects of the app by using an animal model-based test on simulated PHDCR. Twelve adult Bama miniature pigs were subjected to penetrating abdominal injuries and were randomly assigned to the 16 students, who were randomly divided into 2 groups (n = 8 each): group A (decided on PHDCR by themselves) and group B (decided on PHDCR with the aid of the app). The students were asked to complete the PHDCR within 1 h, and then blood samples were taken and thromboelastography, routine coagulation test, blood cell count, and blood gas analysis were examined. The lab examination results along with the value of mean arterial pressure were used to compare the resuscitation effects between the 2 groups. Furthermore, a 4-statement-based post-test survey on a 5-point Likert scale was performed in group B students to test the usability aspects of the constructed app.

resultsWith the above 3 kinds of text segmentation algorithm, B/S architecture mode, and Spring Boot as the development framework, the decision-making app for PHDCR was successfully constructed. The time to decide PHDCR was (28.8 ± 3.41) sec in group B, much shorter than that in group A (87.5 ± 8.53) sec (p < 0.001). The outcomes of animals treated by group B students were much better than that by group A students as indicated by higher mean arterial pressure, oxygen saturation and fibrinogen concentration and maximum amplitude, and lower R values in group B than those in group A. The post-test survey revealed that group B students gave a mean score of no less than 4 for all 4 statements.

conclusionA decision-making app for PHDCR was constructed in the present study and the preliminary trial test revealed that it could help to improve the resuscitation effect in animal models of penetrating abdominal injury.

Indexed as

Decision MakingEmergency Medical ServicesMobile ApplicationsResuscitationAlgorithmsAnimalsFemaleHumansMaleSwineAppDecision-makingPre-hospital damage control resuscitationSeverely injured patientsTrauma

Identifiers

PMID40087116
PMCPMC12489481

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.