Evidence map›Paper›PMID 41609886›Full record

ArticleNeurosurgical review2026

Identifying four distinct prognostic trajectories using latent class growth analysis in moderate-severe TBI: a 10-year retrospective cohort study.

Ren-Ci Wang, Jing Yan, Jun-Jie Zhao, Tian-Chi Ma, Wen-Heng Guo, He-Rong Wang, Jing-Yi Han, Wen-Jun Tang, Feng-Bo Wu, An-An Yin and 3 more

Abstract read
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In one paragraph

Article in Neurosurgical review, 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

13 authors.

Ren-Ci WangDepartment of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Jing YanDepartment of Neurosurgery, The 960th Hospital of the People's Liberation Army, Jinan, China.
Jun-Jie ZhaoDepartment of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Tian-Chi MaDepartment of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Wen-Heng GuoDepartment of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
He-Rong WangDepartment of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Jing-Yi HanSchool of Basic Medical, Fourth Military Medical University, Xi'an, China.
Wen-Jun TangSchool of Basic Medical, Fourth Military Medical University, Xi'an, China.
Feng-Bo WuDepartment of Mathematics, University of California, Santa Barbara, Santa Barbara, USA.
An-An YinDepartment of Plastic and Reconstructive Surgery, Craniomaxillofacial Surgery Group, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Wei LinDepartment of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Xi'an, China. linwei@fmmu.edu.cn.
Xia LiDepartment of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Xi'an, China. naowaike1975@163.com.
Ya-Long HeDepartment of Neurosurgery, Xijing Institute of Clinical Neuroscience, Xijing Hospital, Fourth Military Medical University, Xi'an, China. heyl.fmmu@hotmail.com.

Funding

The Shaanxi Provincial Natural Science Foundation for Young Scholars 2014JQ2-8051
6 · The paper itself

Abstract

Moderate-to-severe traumatic brain injury (msTBI) is associated with heterogeneous long-term outcomes, yet the dynamic trajectories of functional recovery remain poorly characterized. This study aimed to identify distinct prognostic trajectory subgroups and their risk factors in msTBI patients. A retrospective cohort study was conducted on msTBI patients admitted to our institution. Glasgow Outcome Scale (GOS) scores were assessed at discharge and at 3, 6, 12, and 24 months post-discharge. Latent class growth analysis (LCGA) was employed to identify distinct prognostic trajectories. Univariate analysis and multivariable ordinal regression models were used to identify factors associated with trajectory membership. A total of 401 patients were included in the final analysis. Four distinct prognostic trajectories were identified: (1) Catastrophic Outcome without Recovery (Trajectory 1), (2) Limited Improvement with Unfavorable Outcome (Trajectory 2), (3) Delayed but Sustained Favorable Recovery (Trajectory 3), and (4) Early Stable Favorable Outcome (Trajectory 4). Multivariable ordinal regression analysis identified admission and discharge levels of consciousness (LOC), discharge GOS score, age, and chronic comorbidities as significant independent factors associated with the prognostic trajectories. msTBI patients exhibit heterogeneous long-term recovery patterns that can be classified into four distinct trajectories. Early identification of trajectory membership through baseline clinical characteristics may facilitate personalized rehabilitation strategies and prognostic counseling.

Indexed as

Brain Injuries, TraumaticAdultCohort StudiesFemaleGlasgow Outcome ScaleHumansLatent Class AnalysisMaleMiddle AgedPrognosisRecovery of FunctionRetrospective StudiesRisk FactorsGlasgow outcome scaleLatent class growth analysisLong-term outcomeTrajectory analysisTraumatic brain injury

Identifiers

PMID41609886

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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.