Evidence map›Paper›PMID 35573300›Full record

ArticleFrontiers in neuroscience2022

EEG Evidence Reveals Zolpidem-Related Alterations and Prognostic Value in Disorders of Consciousness.

Zexuan Hao, Xiaoyu Xia, Yang Bai, Yong Wang, Weibei Dou

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
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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

5 authors at 4 institutions in 1 country.

Zexuan HaoDepartment of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China.
Xiaoyu XiaDepartment of Neurosurgery, The First Medical Center of PLA General Hospital, Beijing, China.
Yang BaiCenter for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.
Yong WangKey Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Department of Electrical Engineering, Yanshan University, Qinhuangdao, China.
Weibei DouDepartment of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China.
Tsinghua University · CNAffiliated Hospital of Hangzhou Normal University · CNHainan Branch of People's Liberation Army General Hospital · CNYanshan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effective treatment and accurate long-term prognostication of patients with disorders of consciousness (DOC) remain pivotal clinical issues and challenges in neuroscience. Previous studies have shown that zolpidem produces paradoxical recovery and induces similar change patterns in specific electrophysiological features in some DOC (∼6%). However, whether these specific features are neural markers of responders, and how neural features evolve over time remain unclear. Here, we capitalized on static and dynamic EEG analysis techniques to fully uncover zolpidem-induced alterations in eight patients with DOC and constructed machine-learning models to predict long-term outcomes at the single-subject level. We observed consistent patterns of change across all patients in several static features (e.g., decreased relative theta power and weakened alpha-band functional connectivity) after zolpidem administration, albeit none zolpidem responders. Based on the current evidence, previously published electrophysiological features are not neural markers for zolpidem responders. Moreover, we found that the temporal dynamics of the brain slowed down after zolpidem intake. Brain states before and after zolpidem administration could be completely characterized by the EEG features. Furthermore, long-term outcomes were accurately predicted using connectivity features. Our findings suggest that EEG neural signatures have huge potential to assess consciousness states and predict fine-grained outcomes. In summary, our results extend the understanding of the effects of zolpidem on the brain and open avenues for the application prospect of zolpidem and EEG in patients with DOC.

Indexed as

disorders of consciousnessEEGfunctional connectivitymachine learningmicrostatesprognosisspectral analysiszolpidem

Identifiers

PMID35573300
PMCPMC9093050
OpenAlexW4285744581

What OpenQuestion holds

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LicenceCC BY
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 OpenQuestion graph.