Evidence map›Paper›PMID 38874064›Full record

ArticleJournal of the American Heart Association2024

Data-Driven Analysis Reveals Cortical Infarction Patterns Correlated With Inflammation and Prognosis: A Retrospective, Multicenter Cohort Study.

Wen-Jie Wang, Lingling Ding, Qiang Zhang, Jing Jing, Yong Jiang, Xia Meng, Hongqiu Gu, Kaixuan Yang, Yilong Wang, Hao Li and 3 more

Abstract readMulticenter Study
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 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.

Wen-Jie WangDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0003-2531-7285
Lingling DingDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0003-0114-8157
Qiang ZhangChina National Clinical Research Center-Hanalytics Artificial Intelligence Research Centre for Neurological Disorders Beijing China.
Jing JingDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0001-9822-5758
Yong JiangDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0001-7700-6054
Xia MengDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0002-8764-9739
Hongqiu GuDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0003-1608-1856
Kaixuan YangNational Center for Healthcare Quality Management in Neurological Diseases, Beijing Tiantan Hospital Capital Medical University Beijing China.ORCID 0000-0001-5156-6889
Yilong WangDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0003-2725-2788
Hao LiDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.
Yongjun WangDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0002-9976-2341
Xingquan ZhaoDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0001-8345-5147
Zixiao LiDepartment of Neurology Beijing Tiantan Hospital, Capital Medical University Beijing China.ORCID 0000-0002-4713-5418

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aim to identify the distinct lesion patterns and regions associated with functional outcome and inflammation in patients with acute ischemic stroke, and investigate whether the association between lesion patterns and functional outcome was mediated by inflammation. METHODS AND

resultsWe performed nonnegative matrix factorization to derived low-dimensional lesion patterns (atoms), and Bayesian linear regression models were applied to explore the associations of lesion patterns with inflammatory factors including high-sensitivity C-reactive protein and interleukin-6, as well as functional outcome (defined as modified Rankin Scale score at 3 months). The difference distribution mean and 95% highest probability density interval (HPDI) were calculated. Mediation analysis was used to examine the mediating effects of inflammation on the relationships between lesion patterns and functional outcome. Seven lesion patterns were derived from 5914 patients with acute ischemic stroke. Lesion patterns distributed in the cortical regions were associated with inflammatory response, including atom 1 (interleukin-6: mean, 0.113 [95% HPDI, 0.073-0.162]; high-sensitivity C-reactive protein: mean, 0.082 [95% HPDI, 0.038-0.123]) and atom 4 (interleukin-6: mean, 0.113 [95% HPDI, 0.071-0.167]; high-sensitivity C-reactive protein: mean, 0.108 [95% HPDI, 0.058-0.165]). These lesion patterns were also significantly associated with functional outcome (atom 1: mean, 1.958 [95% HPDI, 1.538-2.383]; atom 4: mean, 2.245 [95% HPDI, 1.773-2.741]). Mediation analysis suggested that interleukin-6 explained 15.34% and 7.47% in the association of atom 1 and atom 4 with functional outcome, respectively.

conclusionsCertain lesion patterns that are associated with both inflammation and functional outcome of acute ischemic stroke, especially cortical infarction, may play a role in functional outcome through modulating inflammatory reactions.

Indexed as

C-Reactive ProteinInflammationInterleukin-6Ischemic StrokeAgedBayes TheoremBiomarkersCerebral InfarctionFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedPrognosisRetrospective StudiesBiomarkersC-Reactive ProteinIL6 protein, humanInterleukin-6functional outcomeinflammatory responseischemic strokelesion patternsmachine learning

Identifiers

PMID38874064
PMCPMC11255772

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Registered trials

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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.