Thesis Transdiagnostic symptom clusters among idiopathic pain and fatigue disorders, 2023, Jones

Discussion in 'ME/CFS research' started by Dolphin, Jan 2, 2024.

  1. Dolphin

    Dolphin Senior Member (Voting Rights)

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    This looks like it's from the Younger lab. Only a small part of the thesis is available at the link unfortunately.

    Source: University of Alabama at Birmingham Date: November 7, 2023 URL: https://www.proquest.com/openview/5982633b59420a2cf10136ec8bd59280/1

    Transdiagnostic symptom clusters among idiopathic pain and fatigue disorders
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    Chloe Jones - Medical/Clinical Psychology, University of Alabama at Birmingham

    Abstract

    Background

    There are no established etiologies, biomarkers, or approved treatments for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). It is thought that the ME/CFS criteria may be diagnosing individuals within a spectrum of different disease states, or even different diseases. There likely exist shared mechanisms across idiopathic pain and fatigue disorders, and diverse mechanisms underneath each individual diagnosis. The need to compare ME/CFS to similar, overlapping, and distinct disorders is a critical element in progressing our understanding of idiopathic pain and fatigue.

    Methods

    A total of 2,731 comprehensive medical history and symptom reports were collected from respondents across the globe with a variety of diagnoses. The agreement between reporting an ME/CFS diagnosis and meeting ME/CFS criteria was assessed with Cohen's Kappa. Dimension reduction was performed with principal component analysis and transdiagnostic clusters of pain and fatigue were investigated with unsupervised gaussian mixture models. Prior subtyping efforts were replicated with latent class analysis.

    Results

    The agreement between meeting ME/CFS criteria and reporting an ME/CFS diagnosis was slight (Kappa=0.107; SE=0.024). Gaussian mixture modeling of a wide range of ME/CFS symptoms resulted in a five-cluster solution. Clustering of pain, fatigue, and gastrointestinal symptoms resulted in a nine-cluster solution. Healthy participants were clustered together, while ME/CFS patients did not comprise a distinct cluster. Latent class analysis of non-core symptoms in ME/CFS resulted in a 5-class solution similar to what has been previously reported.

    Conclusion

    Results support the notion that the ME/CFS diagnosis captures a wide range of symptom profiles. Conceptualizing and assessing these groups as a singular entity may hinder research progress towards identifying biomarkers and etiologies.

    Keywords: cluster, subtypes, ME/CFS, chronic fatigue syndrome, myalgic encephalomyelitis, fibromyalgia

     
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