Evidence map›Paper›PMID 39041609›Full record

ArticleJournal of the American Heart Association2024

Inflammation-Derived and Clinical Indicator-Based Predictive Model for Ischemic Stroke Recovery.

Jiao Luo, You Cai, Peng Xiao, Changchun Cao, Meiling Huang, Xiaohua Zhang, Jie Guo, Yongyang Huo, Qiaoyan Tang, Liuyang Zhao and 5 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Collateral Circulation andJournal of the American Heart Association · 2025
    Trial
  2. Review
  3. Article
  4. Article
  5. 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

15 authors.

Jiao LuoDepartment of Rehabilitation Medicine, Dapeng New District Nan'ao People's Hospital Rehabilitation Branch of the First Affiliated Hospital of Shenzhen University Shenzhen China.
You CaiGreater Bay Biomedical Innocenter Shenzhen Bay Laboratory Shenzhen China.ORCID 0000-0002-7717-9630
Peng XiaoDepartment of Rehabilitation Medicine, Dapeng New District Nan'ao People's Hospital Rehabilitation Branch of the First Affiliated Hospital of Shenzhen University Shenzhen China.
Changchun CaoDepartment of Rehabilitation Medicine, Dapeng New District Nan'ao People's Hospital Rehabilitation Branch of the First Affiliated Hospital of Shenzhen University Shenzhen China.
Meiling HuangDepartment of Rehabilitation, Shenzhen Second People's Hospital the First Affiliated Hospital of Shenzhen University Shenzhen China.
Xiaohua ZhangDepartment of Rehabilitation Medicine, Dapeng New District Nan'ao People's Hospital Rehabilitation Branch of the First Affiliated Hospital of Shenzhen University Shenzhen China.
Jie GuoDepartment of Rehabilitation, Shenzhen Second People's Hospital the First Affiliated Hospital of Shenzhen University Shenzhen China.
Yongyang HuoDepartment of Rehabilitation Medicine, Dapeng New District Nan'ao People's Hospital Rehabilitation Branch of the First Affiliated Hospital of Shenzhen University Shenzhen China.
Qiaoyan TangDepartment of Rehabilitation Medicine, Dapeng New District Nan'ao People's Hospital Rehabilitation Branch of the First Affiliated Hospital of Shenzhen University Shenzhen China.
Liuyang ZhaoDepartment of Rehabilitation Medicine, Dapeng New District Nan'ao People's Hospital Rehabilitation Branch of the First Affiliated Hospital of Shenzhen University Shenzhen China.
Jiabang LiuShenzhen Institute of Translational Medicine, Shenzhen Second People's Hospital the First Affiliated Hospital of Shenzhen University Shenzhen China.
Yaqi MaDepartment of Rehabilitation, Shenzhen Second People's Hospital the First Affiliated Hospital of Shenzhen University Shenzhen China.
Anqun YangDepartment of Rehabilitation Medicine, Dapeng New District Nan'ao People's Hospital Rehabilitation Branch of the First Affiliated Hospital of Shenzhen University Shenzhen China.ORCID 0009-0001-4578-0261
Mingchao ZhouDepartment of Rehabilitation, Shenzhen Second People's Hospital the First Affiliated Hospital of Shenzhen University Shenzhen China.ORCID 0000-0002-3820-731X
Yulong WangDepartment of Rehabilitation, Shenzhen Second People's Hospital the First Affiliated Hospital of Shenzhen University Shenzhen China.ORCID 0000-0002-0947-6967

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeuroinflammatory responses are closely associated with poststroke prognosis severity. This study aimed to develop a predictive model, combining inflammation-derived markers and clinical indicators, for distinguishing functional outcomes in patients with subacute ischemic stroke. METHODS AND

resultsBased on activities of daily living assessments, ischemic stroke participants were categorized into groups with little effective (LE) recovery and obvious effective (OE) recovery. Initial biocandidates were identified by overlapping differentially expressed proteins from proteomics of clinical serum samples (5 LE, 5 OE, and 6 healthy controls) and differentially expressed genes from an RNA sequence of the ischemic cortex in middle cerebral artery occlusion mice (n=3). Multidimensional validations were conducted in ischemia-reperfusion models and a clinical cohort (15 LE, 11 OE, and 18 healthy controls). Models of robust biocandidates combined with clinical indicators were developed with machine learning in the training data set and prediction in another test data set (15 LE and 11 OE). We identified 194 differentially expressed proteins (LE versus healthy controls) and 174 differentially expressed proteins (OE versus healthy controls) in human serum, and 5121 differentially expressed genes (day 3) and 5906 differentially expressed genes (day 7) in middle cerebral artery occlusion mice cortex. Inflammation-derived biomarkers TIMP1 (tissue inhibitor metalloproteinase-1) and galactosidase-binding protein LGLAS3 (galectin-3) exhibited robust increases under ischemic injury in mice and humans. TIMP1 and LGALS3 coupled with clinical indicators (hemoglobin, low-density lipoprotein cholesterol, and uric acid) were developed into a combined model for differentiating functional outcome with high accuracy (area under the curve, 0.8).

conclusionsThe combined model is a valuable tool for evaluating prognostic outcomes, and the predictive factors can facilitate development of better treatment strategies.

Indexed as

BiomarkersDisease Models, AnimalIschemic StrokeRecovery of FunctionAgedAnimalsCase-Control StudiesFemaleHumansInfarction, Middle Cerebral ArteryMachine LearningMaleMiceMice, Inbred C57BLMiddle AgedPredictive Value of TestsBiomarkersischemic strokeLGALS3neuroinflammationrecovery biomarkersTIMP1

Identifiers

PMID39041609
PMCPMC11964079

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.