Evidence map›Paper›PMID 42148664›Full record

ReviewBrain : a journal of neurology2026

Designing studies for post-treatment Lyme disease and other infection-associated chronic illnesses.

Paul M Arnaboldi, Jacqueline Becker, Avindra Nath, Patricia K Coyle, Andrew Handel, Timothy J Sellati, Maria Gomes-Solecki, Sandra Garcet, Marianne K Henderson, Piper Mullins and 6 more

Abstract readReview
In one paragraph

Review in Brain : a journal of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Paul M ArnaboldiDepartment of Pathology, Microbiology, and Immunology, New York Medical College, Valhalla, NY 10595, USA.
Jacqueline BeckerDepartment of Medicine, Ichan School of Medicine, New York, NY 10029, USA.ORCID 0000-0003-2708-6046
Avindra NathNational Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.ORCID 0000-0003-0927-5855
Patricia K CoyleDepartment of Neurology, Stony Brook University Health Sciences Center School of Medicine, Stony Brook, NY 11794, USA.
Andrew HandelDepartment of Pediatrics, Stony Brook University Health Sciences Center School of Medicine, Stony Brook, NY 11794, USA.ORCID 0000-0003-3544-4376
Timothy J SellatiDiaSorin, Inc., Stillwater, MN 55082, USA.
Maria Gomes-SoleckiDepartment of Microbiology, Immunology, and Biochemistry, University of Tennessee Health Science Center College of Medicine, Memphis, TN 38163, USA.
Sandra GarcetCenter for Clinical and Translational Science, Rockefeller University, New York, NY 10065, USA.
Marianne K HendersonNational Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Piper MullinsPan-Smithsonian Cryo-Initiative, Smithsonian Institution, Washington, DC 20013, USA.
Elliot CowanPartners in Diagnostics, Rockville, MD 20850, USA.
W Richard McCombieCold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
Anna-Marie WellinsStony Brook School of Nursing, Stony Brook University, Stony Brook, NY 11794, USA.
Mark AllegrettaNational Multiple Sclerosis Society, New York, NY 10017, USA.
Jonas BergquistDepartment of Chemistry-BMC, Analytical Chemistry and Neurochemistry, Uppsala University, Uppsala SE-751 24, Sweden.ORCID 0000-0002-4597-041X
Steven E SchutzerDepartment of Medicine, Rutgers New Jersey Medical School, Newark, NJ 07103, USA.

Funding

Banbury Center of Cold Spring Harbor Laboratory
6 · The paper itself

Abstract

Infection-associated chronic illnesses (IACIs) encompass a spectrum of poorly understood syndromes often marked by significant neurologic and multisystem symptoms following an infectious event. This review focuses on several diseases representative of the IACI spectrum. These are post-treatment Lyme disease syndrome (PTLDS), long COVID, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and multiple sclerosis (MS). Their clinical and biological complexity, combined with a lack of clear diagnostic criteria and objective available laboratory biomarkers, makes them difficult to distinguish from conditions with overlapping features. This presents challenges for research studies, as well as diagnosis and clinical management. This diagnostic ambiguity, coupled with heterogeneous patient presentations, has led to challenges in research, including misclassification of study participants and inconsistent or irreproducible findings. Some PTLDS research exemplifies these issues, which also extend to other IACIs. To advance the field, we highlight key methodological refinements and approaches for studying IACIs, including rigorous participant selection, standardized sample collection protocols, and the use of appropriate control groups, including those with microbiologic proof of the initial infection when known and technologically feasible. We also address broader influences on research quality, such as stigma, historical neglect, and the urgency to find treatments, which have contributed to the proliferation of poorly controlled studies and questionable practices. Drawing lessons from past challenges, we propose a path forward grounded in fit-for-purpose methodological rigour to improve scientific understanding and support evidence-based therapeutic development for IACIs.

Indexed as

Fatigue Syndrome, ChronicLyme DiseaseMultiple SclerosisResearch DesignChronic DiseaseCOVID-19HumansPost-Lyme Disease Syndromeinfection associated chronic illnesslong COVIDmultiple sclerosismyalgic encephalomyelitis/chronic fatigue syndromepost-treatment Lyme disease syndrome

Identifiers

PMID42148664
PMCPMC13232051

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.