Evidence map›Paper›PMID 39373749›Full record

ArticleSkeletal radiology2025

MRI features distinguishing pediatric Lyme arthritis from septic arthritis.

Joshua E Powell, Vincent K Lee, Suraj S Parikh, Andrew J Nowalk, Amisha J Shah

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Article in Skeletal radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

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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

5 authors.

Joshua E PowellDepartment of Radiology, Division of Musculoskeletal Imaging, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA. powellj713@gmail.com.ORCID http://orcid.org/0009-0006-3257-5900
Vincent K LeeDepartment of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
Suraj S ParikhDepartment of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Andrew J NowalkDepartment of Pediatrics, Division of Pediatric Infectious Diseases, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.
Amisha J ShahDepartment of Radiology, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aims to identify distinguishing MRI features of Lyme arthritis (LA), an increasingly prevalent cause of pediatric infectious arthritis in the USA, to enable rapid discrimination from septic arthritis (SA) and facilitate appropriate management. MATERIALS AND

methodsA single-center, retrospective analysis was conducted on a convenience sample of pediatric patients with LA in an endemic area using EPIC electronic health record data between January 2010 and December 2020. Patients with positive serologic testing and concurrent MRI were selected. MRI scans were reviewed by a subspecialty-trained pediatric radiologist. Key MRI features analyzed include joint effusion, synovitis, myositis, soft tissue edema, and osseous edema and erosions. MRI features, demographics, and clinical data were compared using univariable and multivariable analyses.

resultsFifty cases of knee LA and 13 cases of knee SA were included. Larger joint effusion (p = 0.0055, z =  - 2.779) and abnormally thickened synovium (p = 0.0011, χ

conclusionMRI can be a valuable tool in differentiating LA from SA. Abnormal synovium and increasing joint effusion favor LA, while increasing soft tissue edema and osseous changes favor SA. Notably, the presence of bone erosion effectively excluded LA from consideration.

Indexed as

Arthritis, InfectiousLyme DiseaseMagnetic Resonance ImagingAdolescentChildChild, PreschoolDiagnosis, DifferentialFemaleHumansKnee JointMaleRetrospective StudiesArthritisKneeLymeMRIPediatricSepticSynovitis

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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.