Evidence map›Paper›PMID 37881452›Full record

ArticleNIHR open research2023

Typing myalgic encephalomyelitis by infection at onset: A DecodeME study.

Andrew D Bretherick, Simon J McGrath, Andy Devereux-Cooke, Sian Leary, Emma Northwood, Anna Redshaw, Pippa Stacey, Claire Tripp, Jim Wilson, Sonya Chowdhury and 16 more

Open access · diamondAbstract read
In one paragraph

Article in NIHR open research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Recent research in myalgic encephalomyelitis/chronic fatigue syndrome: an evidence map.Health technology assessment (Winchester, England) · 2025
    Pooled it
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  11. Review
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  15. The German Multicenter Registry for ME/CFS (MECFS-R).Journal of clinical medicine · 2024
    Article
  16. 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

26 authors at 3 institutions in 1 country.

Andrew D BretherickMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.ORCID https://orcid.org/0000-0001-9258-3140
Simon J McGrathc/o DecodeME, MRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Andy Devereux-Cookec/o DecodeME, MRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Sian Learyc/o DecodeME, MRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Emma Northwoodc/o DecodeME, MRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Anna Redshawc/o DecodeME, MRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Pippa Staceyc/o DecodeME, MRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Claire Trippc/o DecodeME, MRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Jim Wilsonc/o DecodeME, MRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Sonya Chowdhury42 Temple Street, Keynsham, Action For ME, Bristol, England, BS31 1EH, UK.
Isabel Lewis42 Temple Street, Keynsham, Action For ME, Bristol, England, BS31 1EH, UK.
Øyvind AlmelidMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.ORCID https://orcid.org/0000-0003-0163-3486
Sumy V BabyMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Tom BakerMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Hannes BecherMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Thibaud BoutinMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Malgorzata ClydeMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Diana GarciaMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
John IrelandMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Shona M KerrMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.ORCID https://orcid.org/0000-0002-4137-1495
Ewan McDowallMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
David PerryMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Gemma L SammsMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Veronique VitartMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Jareth C WolfeMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.
Chris P PontingMRC Human Genetics Unit, The University of Edinburgh, Edinburgh, Scotland, EH4 2XU, UK.ORCID https://orcid.org/0000-0003-0202-7816
Institute of Genetics and Cancer · GBAction for ME · GBNHS Tayside · GB

Funding

Medical Research Council MC_UU_00035/14Wellcome Trust
6 · The paper itself

Abstract

Background: People with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) experience core symptoms of post-exertional malaise, unrefreshing sleep, and cognitive impairment. Despite numbering 0.2-0.4% of the population, no laboratory test is available for their diagnosis, no effective therapy exists for their treatment, and no scientific breakthrough regarding pathogenesis has been made. It remains unknown, despite decades of small-scale studies, whether individuals experience different types of ME/CFS separated by onset-type, sex or age. Methods: DecodeME is a large population-based study of ME/CFS that recruited 17,074 participants in the first 3 months following full launch. Detailed questionnaire responses from UK-based participants who all reported being diagnosed with ME/CFS by a health professional provided an unparalleled opportunity to investigate, using logistic regression, whether ME/CFS severity or onset type is significantly associated with sex, age, illness duration, comorbid conditions or symptoms. Results: The well-established sex-bias among ME/CFS patients is evident in the initial DecodeME cohort: 83.5% of participants were females. What was not known previously was that females tend to have more comorbidities than males. Moreover, being female, being older and being over 10 years from ME/CFS onset are significantly associated with greater severity. Five different ME/CFS onset types were examined in the self-reported data: those with ME/CFS onset (i) after glandular fever (infectious mononucleosis); (ii) after COVID-19 infection; (iii) after other infections; (iv) without an infection at onset; and, (v) where the occurrence of an infection at or preceding onset is not known. Among other findings, ME/CFS onset with unknown infection status was significantly associated with active fibromyalgia. Conclusions: DecodeME participants differ in symptoms, comorbid conditions and/or illness severity when stratified by their sex-at-birth and/or infection around the time of ME/CFS onset.

Indexed as

Myalgic encephalomyelitisPost-exertional malaisePost-viral syndromeSex-biasSub-types

Identifiers

PMID37881452
PMCPMC10593357
OpenAlexW4386031042

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.