Evidence map›Paper›PMID 42004712›Full record

ArticlePeerJ2026

Development and validation of an early predictive model for acute stress disorder after trauma: a clinical cohort study.

Xiahong Li, Shangpeng Shi, Juan Gu, Xiangyuan Chu, Xiu Dai, Xiuquan Shi

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xiahong Li *Medical Reform Office, The Third Affiliated Hospital of Zunyi Medical University, The First People's Hospital of Zunyi, Zunyi, Guizhou, China.
Shangpeng Shi *Medical Reform Office, The Third Affiliated Hospital of Zunyi Medical University, The First People's Hospital of Zunyi, Zunyi, Guizhou, China.
Juan GuZunyi Medical and Pharmaceutical College, Zunyi, Guizhou, China.
Xiangyuan ChuDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.
Xiu DaiDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.
Xiuquan ShiDepartment of Epidemiology and Health Statistics, School of Public Health, Zunyi Medical University, Zunyi, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Injury is sudden and unpredictable and has become a major public health problem in the world, and many trauma patients may experience cognitive or psychological problems including acute stress disorder (ASD). However, the ability to identify ASD early is still limited. The aim of this study was to investigate the risk factors for post-traumatic ASD and to establish a visual prediction model. Methods: This prospective cohort study was conducted from the trauma center of one general hospital in Zunyi. Cases of 216 inpatients with trauma were selected from September 2020 to August 2021. The participants were divided into the ASD ( Results: Patients in the ASD group differed significantly from those in the non-ASD group in terms of general demographic and clinical characteristics ( Conclusions: Our prediction model had a good discriminatory capacity and showed better effects in calibration. It may have potential value for the early identification of ASD.

Indexed as

Stress Disorders, Traumatic, AcuteWounds and InjuriesAdultFemaleHumansLogistic ModelsMaleMiddle AgedNomogramsPrediction AlgorithmsProspective StudiesRisk FactorsASDEpidemiological characteristicsInflammationPredictive modelTrauma

Identifiers

PMID42004712
PMCPMC13086026

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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.