Evidence map›Paper›PMID 39867453›Full record

ArticleFrontiers in neuroscience2024

A novel muscle network approach for objective assessment and profiling of bulbar involvement in ALS.

Panying Rong, Lindsey Heidrick, Gary Pattee

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

4 citing papers in PubMed.

  1. Article
  2. Exploratory associations between APOE-εFrontiers in neurology · 2026
    Article
  3. Article
  4. 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

3 authors.

Panying RongDepartment of Speech-Language-Hearing: Sciences and Disorders, University of Kansas, Lawrence, KS, United States.
Lindsey HeidrickDepartment of Hearing and Speech, University of Kansas Medical Center, Kansas City, KS, United States.
Gary PatteeNeurology Associate P.C., Lincoln, NE, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: As a hallmark feature of amyotrophic lateral sclerosis (ALS), bulbar involvement significantly impacts psychosocial, emotional, and physical health. A validated objective marker is however lacking to characterize and phenotype bulbar involvement, positing a major barrier to early detection, progress monitoring, and tailored care. This study aimed to bridge this gap by constructing a multiplex functional mandibular muscle network to provide a novel objective measurement tool of bulbar involvement. Methods: A noninvasive electrophysiological technique-surface electromyography-was combined with graph network analysis to extract 48 features measuring the regulatory mechanisms, connectivity, integration, segregation, assortativity, and lateralization of the functional muscle network during a speech task. These features were clustered into 10 interpretable latent factors. To evaluate the utility of the muscle network as a bulbar measurement tool, a heterogenous ALS cohort, consisting of eight individuals with overt clinical bulbar symptoms and seven without, along with 10 neurologically healthy controls, was employed to train and validate statistical and machine learning algorithms to assess the disease effects on the network features and the relation of the network performance to the current clinical diagnostic standard and behavioral patterns of bulbar involvement. Results: Significant disease effects were found on most network features. The most robust effects were manifested by reduced and more variable myoelectric activities, and reduced functional connectivity and integration of the muscle network. The 10 latent factors (1) demonstrated acceptably high efficacy for detecting bulbar neuromuscular changes across all clinically confirmed symptomatic cases and clinically silent prodromal cases (area under the curve = 0.89-0.91; F1 score = 0.85-0.87; precision = 0.84-0.86; recall = 0.87-0.88); and (2) selectively correlated with clinically meaningful behavioral patterns (conditional Conclusion: The functional muscle network shows promise for an objective quantifiable measurement tool to improve early detection and profiling of bulbar involvement across the prodromal and symptomatic stages. This tool has various strengths, including the use of a clinically readily available noninvasive instrument, fully automated data processing and analytics, and generation of interpretable objective outcome measures (i.e., latent factors), together rendering it highly scalable in routine clinical practice for assessing and monitoring of bulbar involvement.

Indexed as

amyotrophic lateral sclerosisbiomarkergraph neural networksmasticatory musclesneurodegenerative diseasesquantitative evaluationspeech disorderssurface electromyography

Identifiers

PMID39867453
PMCPMC11759300

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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.