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<strong></strong>How Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME/CFS) Progresses: A Framework for Research and the Prevention, Treatment, and Rehabilitation in ME/CFS

2019· preprint· en· W2973857405 on OpenAlexaff
Luís Nacul, Shennae O’Boyle, Flávio E. Nácul, Kathleen Mudie, Caroline C. Kingdon, Jacqueline M. Cliff, Taane G. Clark, Hazel M. Dockrell, Eliana Lacerda

Bibliographic record

VenuePreprints.org · 2019
Typepreprint
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsB.C. Women's Hospital & Health Centre
FundersNational Institutes of Health
KeywordsChronic fatigue syndromeDiseaseMedicineEncephalomyelitisAsymptomaticPathophysiologyImmunologyDysfunctional familyImmune systemNeuroscienceBioinformaticsPsychologyPsychiatryPathologyBiology

Abstract

fetched live from OpenAlex

We propose a framework for the understanding of the pathophysiology and management of Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME/CFS) that considers wider determinants of health and long-term temporal variation in pathophysiological features and disease phenotype throughout the natural history of the disease. As in other chronic diseases, ME/CFS evolves through different stages, from asymptomatic predisposition, progressing to a prodromal stage, and then to symptomatic disease. Disease incidence depends on genetic makeup and environment factors, the exposure to an insult, or repeated insults, and the nature of the host response. In people who develop ME/CFS, normal homeostatic processes in response to adverse insults may be replaced by aberrant responses leading to dysfunctional states. Thus, the predominantly neuro-immune and autonomic manifestations, underlined by a hyper-metabolic state, that characterise early disease, may be followed by various processes leading to multi-systemic related symptoms. This abnormal metabolic state and the effects of a range of mediators such as products of oxidative and nitrosamine stress, may lead to progressive cell and metabolic dysfunction culminating in a hypometabolic state with low energy production. These processes do not seem to happen uniformly; although a spiralling of progressive inter-related and self-sustaining abnormalities may ensue, reversion to states of milder abnormalities is possible if the host is able to restate responses to improve homeostatic equilibrium. Disease management and research efforts should seek to identify and apply strategies targeted at the different pathophysiological dysfunctions that characterise different disease stages. As disease presentation varies over time, no single case description, set of diagnostic criteria, or molecular feature is currently diagnostic for all patients at all times. While acknowledging its limitations due to the incomplete research evidence, we suggest the proposed framework may improve research design and health care interventions for people with ME/CFS.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.009
Scholarly communication0.0080.009
Open science0.0030.004
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0160.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.137
GPT teacher head0.423
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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