Evidence map›Paper›PMID 39119588›Full record

ArticleBrain network and modulation

Resting-state electroencephalography delta and theta bands as compensatory oscillations in chronic neuropathic pain: a secondary data analysis.

Sara Pinto Barbosa, Ygor Nascimento Junqueira, Milena Apetito Akamatsu, Lucas Murrins Marques, Adriano Teixeira, Matheus Lobo, Mohamed H Mahmoud, Walid E Omer, Kevin Pacheco-Barrios, Felipe Fregni

Abstract read
In one paragraph

Article in Brain network and modulation. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

10 authors.

Sara Pinto BarbosaInstituto de Medicina Física e Reabilitação, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brasil.
Ygor Nascimento JunqueiraPrinciples and Practice of Clinical Research Program, Harvard T.H. Chan School of Public Health, Boston.
Milena Apetito AkamatsuInstituto Butantan, Centro Bioindustrial, São Paulo, SP, Brazil.
Lucas Murrins MarquesMental Health Department, Santa Casa de São Paulo School of Medical Sciences, São Paulo, SP, Brazil.
Adriano TeixeiraFederal University of Bahia, Multidisciplinary Health Institute - IMS, Salvador, BA, Brazil.
Matheus LoboSurgical Oncologist at Hospital A. C. Camargo, São Paulo, SP, Brazil.
Mohamed H MahmoudPrimary Health Care Corporation, Doha, Qatar.
Walid E OmerHamad Medical Corporation, Doha, Qatar.
Kevin Pacheco-BarriosNeuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MD, USA.ORCID 0000-0002-7166-2816
Felipe FregniNeuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MD, USA.ORCID 0000-0001-9359-8643

Funding

Optimized tDCS for fibromyalgia: targeting the endogenous pain control systemR01AT009491 · NCCIH · SPAULDING REHABILITATION HOSPITAL · PI FREGNI, FELIPE · 2018 to 2023
$2.3M
NCCIH NIH HHS R01 AT009491
6 · The paper itself

Abstract

Chronic neuropathic pain (CNP) remains a significant clinical challenge, with complex neurophysiological underpinnings that are not fully understood. Identifying specific neural oscillatory patterns related to pain perception and interference can enhance our understanding and management of CNP. To analyze resting electroencephalography data from individuals with chronic neuropathic pain to explore the possible neural signatures associated with pain intensity, pain interference, and specific neuropathic pain characteristics. We conducted a secondary analysis from a cross-sectional study using electroencephalography data from a previous study, and Brief Pain Inventory from 36 patients with chronic neuropathic pain. For statistical analysis, we modeled a linear or logistic regression by dependent variable for each model. As independent variables, we used electroencephalography data with such brain oscillations: as delta, theta, alpha, and beta, as well as the oscillations low alpha, high alpha, low beta, and high beta, for the central, frontal, and parietal regions. All models tested for confounding factors such as age and medication. There were no significant models for Pain interference in general activity, walking, work, relationships, sleep, and enjoyment of life. However, the model for pain intensity during the past four weeks showed decreased alpha oscillations, and increased delta and theta oscillations were associated with decreased levels of pain, especially in the central area. In terms of pain interference in mood, the model showed high oscillatory Alpha signals in the frontal and central regions correlated with mood impairment due to pain.

Indexed as

chronic neuropathic painEEGoscillationpain

Identifiers

PMID39119588
PMCPMC11309019

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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.