Evidence map›Paper›PMID 37239295›Full record

ArticleBrain sciences2023

Kullback-Leibler Divergence of Sleep-Wake Patterns Related with Depressive Severity in Patients with Epilepsy.

Mingsu Liu, Jian Jiang, Yu Feng, Yang Cai, Jing Ding, Xin Wang

Open access · goldAbstract read
In one paragraph

Article in Brain sciences, 2023. 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
0.9field-weighted citation impact, top 27% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Investigating Metrics of Discrete-Individual Repeatability of the Stress Response.Integrative organismal biology (Oxford, England) · 2025
    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

6 authors at 5 institutions in 1 country.

Mingsu LiuDepartment of Neurology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Jian JiangInstitute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Yu FengDepartment of Neurology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Yang CaiDepartment of Neurology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Jing DingDepartment of Neurology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Xin WangDepartment of Neurology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Fudan University · CNChinese Academy of Sciences · CNSun Yat-sen University · CNThe First Affiliated Hospital, Sun Yat-sen University · CNZhongshan Hospital · CN

Funding

the Clinical Research Plan of SHDC SHDC2020CR3066Bthe Lingang Laboratory LG202105-02-05
6 · The paper itself

Abstract

(1) Objective: Whether abnormal sleep-wake rhythms were associated with depressive symptoms in patents with epilepsy had remained unclear. Our study aimed to establish relative entropy for the assessment of sleep-wake patterns and to explore the relationship between this index and the severity of depressive symptoms in patients with epilepsy. (2) Methods: We recorded long-term scalp electroencephalograms (EEGs) and Hamilton Depression Rating Scale-17 (HAMD-17) questionnaire scores from 64 patients with epilepsy. Patients with HAMD-17 scores of 0-7 points were defined as the non-depressive group, while patients with scores of 8 or higher were defined as the depression group. Sleep stages were firstly classified based on EEG data. We then quantified sleep-wake rhythm variations in brain activity using the Kullback-Leibler divergence (KLD) of daytime wakefulness and nighttime sleep. The KLD at different frequency bands in each brain region was analyzed between the depression and non-depression groups. (3) Results: Of the 64 patients with epilepsy included in our study, 32 had depressive symptoms. It was found that patients with depression had significantly decreased KLD for high-frequency oscillations in most brain areas, especially the frontal lobe. A detailed analysis was conducted in the right frontal region (F4) because of the significant difference in the high-frequency band. We found that the KLDs at the gamma bands were significantly decreased in the depression groups compared to the non-depression group (KLD

Indexed as

depressionEEGepilepsyKullback–Leibler divergence

Identifiers

PMID37239295
PMCPMC10216093
OpenAlexW4377091099

What OpenQuestion holds

Textmetadata
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.