Evidence map›Paper›PMID 34393964›Full record

ArticleFrontiers in neurology2021

Detecting Residual Awareness in Patients With Prolonged Disorders of Consciousness: An fNIRS Study.

Meng Li, Yi Yang, Yujin Zhang, Yuhang Gao, Rixing Jing, Yuanyuan Dang, Xueling Chen, Jianghong He, Juanning Si

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

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

17 citing papers in PubMed, 22 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Meng LiSchool of Instrumentation Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, China.
Yi YangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yujin ZhangBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Yuhang GaoSchool of Instrumentation Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, China.
Rixing JingSchool of Instrumentation Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, China.
Yuanyuan DangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Xueling ChenDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Jianghong HeDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Juanning SiSchool of Instrumentation Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, China.
Beijing Information Science & Technology University · CNCapital Medical University · CNBeijing Tian Tan Hospital · CNInstitute of Automation · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in neuroimaging technologies have provided insights into detecting residual consciousness and assessing cognitive abilities in patients with disorders of consciousness (DOC). Functional near-infrared spectroscopy (fNIRS) is non-invasive and portable and can be used for longitudinal bedside monitoring, making it uniquely suited for evaluating brain function in patients with DOC at appropriate spatiotemporal resolutions. In this pilot study, an active command-driven motor imagery (MI) paradigm based on fNIRS was used to detect residual consciousness in patients with prolonged DOC. A support vector machine (SVM) classifier was used to classify yes-or-no responses. The results showed that relatively reliable responses were detected from three out of five patients in a minimally consciousness state (MCS). One of the patients answered all the questions accurately when assessed according to this method. This study confirmed the feasibility of using portable fNIRS technology to detect residual cognitive ability in patients with prolonged DOC by active command-driven motor imagery. We hope to detect the exact level of consciousness in DOC patients who may have a higher level of consciousness.

Indexed as

disorders of consciousnessfunctional near-infrared spectroscopyminimally consciousness statemotor imagerysupport vector machine

Identifiers

PMID34393964
PMCPMC8355369
OpenAlexW3183891795

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.