Evidence map›Paper›PMID 28396994›Full record

ArticleEuropean radiology2017

Identifying the white matter impairments among ART-naïve HIV patients: a multivariate pattern analysis of DTI data.

Zhenchao Tang, Zhenyu Liu, Ruili Li, Xin Yang, Xingwei Cui, Shuo Wang, Dongdong Yu, Hongjun Li, Enqing Dong, Jie Tian

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Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 5% of its field
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

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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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.

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4 · The record

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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

10 authors at 6 institutions in 1 country.

Zhenchao TangSchool of Mechanical, Electrical & Information Engineering, Shandong University, Weihai, Shandong Province, 264209, China.
Zhenyu LiuCAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China.
Ruili LiDepartment of Radiology, Beijing YouAn Hospital, Capital Medical University, Beijing, 100069, China.
Xin YangCAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China.
Xingwei CuiCooperative Innovation Center of Internet Healthcare, Zhengzhou University, Zhengzhou, China, 450052.
Shuo WangCAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China.
Dongdong YuCAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China.
Hongjun LiDepartment of Radiology, Beijing YouAn Hospital, Capital Medical University, Beijing, 100069, China. lihongjun00113@126.com.
Enqing DongSchool of Mechanical, Electrical & Information Engineering, Shandong University, Weihai, Shandong Province, 264209, China. enqdong@sdu.edu.cn.
Jie TianCAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China. jie.tian@ia.ac.cn.
Shandong Institute of Automation · CNBeijing YouAn Hospital · CNCapital Medical University · CNShandong University · CNUniversity of Chinese Academy of Sciences · CNZhengzhou University · CN

Funding

Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding ZYLX201511Beijing Municipal Administration of Hospitals Incubating Program PX2016036Beijing Municipal Science and Technology Commission Z161100002616022National Natural Science Foundation of China 61231004National Natural Science Foundation of China 81571634National Natural Science Foundation of China (CN) 81371635National Natural Science Foundation of China (CN) 81501549National Natural Science Foundation of China (CN) 81671848Science and Technology Service Network Initiative Program of Chinese Academy of Science KFJ-SW-STS-160Strategic Priority Research Program from Chinese Academy of Sciences XDB02060010
6 · The paper itself

Abstract

objectiveTo identify the white matter (WM) impairments of the antiretroviral therapy (ART)-naïve HIV patients by conducting a multivariate pattern analysis (MVPA) of Diffusion Tensor Imaging (DTI) data

methodsWe enrolled 33 ART-naïve HIV patients and 32 Normal controls in the current study. Firstly, the DTI metrics in whole brain WM tracts were extracted for each subject and feed into the Least Absolute Shrinkage and Selection Operators procedure (LASSO)-Logistic regression model to identify the impaired WM tracts. Then, Support Vector Machines (SVM) model was constructed based on the DTI metrics in the impaired WM tracts to make HIV-control group classification. Pearson correlations between the WM impairments and HIV clinical statics were also investigated.

resultsExtensive HIV-related impairments were observed in the WM tracts associated with motor function, the corpus callosum (CC) and the frontal WM. With leave-one-out cross validation, accuracy of 83.08% (P=0.002) and the area under the Receiver Operating Characteristic curve of 0.9110 were obtained in the SVM classification model. The impairments of the CC were significantly correlated with the HIV clinic statics.

conclusionThe MVPA was sensitive to detect the HIV-related WM changes. Our findings indicated that the MVPA had considerable potential in exploring the HIV-related WM impairments. KEY POINTS: • WM impairments along motor pathway were detected among the ART-naïve HIV patients • Prominent HIV-related WM impairments were observed in CC and frontal WM • The impairments of CC were significantly related to the HIV clinic statics • The CC might be susceptible to immune dysfunction and HIV replication • Multivariate pattern analysis had potential for studying the HIV-related white matter impairments.

Indexed as

AdultAntiretroviral Therapy, Highly ActiveBrainCase-Control StudiesCorpus CallosumDiffusion Tensor ImagingEfferent PathwaysFemaleFrontal LobeHIV InfectionsHumansMaleMultivariate AnalysisWhite MatterCorpus CallosumDiffusion tensor ImagingHIVMultivariate AnalysisWhite Matter

Identifiers

PMID28396994
OpenAlexW2606582956

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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.