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Record W4411884124 · doi:10.3899/jrheum.2025-0314.133

Salmonella Septic Arthritis and Osteomyelitis in Patients Receiving Tumor Necrosis Factor Alpha Inhibitors

2025· article· en· W4411884124 on OpenAlexaffvenue
Shahrukh Towheed, Evan Wilson

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineSeptic arthritisEtanerceptOsteomyelitisInfliximabRheumatoid arthritisTumor necrosis factor alphaArthritisDiscontinuationTNF inhibitorInternal medicineImmunologyIntensive care medicine

Abstract

fetched live from OpenAlex

Objectives Tumor necrosis factor (TNF) alpha inhibitor therapies are used worldwide to treat a variety of rheumatic diseases. However, they are also associated with serious infections. This review summarizes and critically appraises the literature surrounding Salmonella musculoskeletal infections in patients receiving TNF alpha inhibitors. The objective of this review is to raise awareness of the risk of Salmonella septic arthritis and osteomyelitis in patients receiving TNF alpha inhibitors. Potential pathophysiologic and immunologic mechanisms are discussed. Methods The MEDLINE, EMBASE, and Google Scholar Databases were searched for this review. Relevant keywords and MeSH terms were incorporated in conjunction with Boolean operators to retrieve appropriate peer-reviewed articles. The reference lists of the most relevant articles were searched manually for additional articles of relevance.[1] Results Twelve reports of Salmonella septic arthritis and 4 reports of Salmonella osteomyelitis were discovered among patients receiving TNF alpha inhibitors. There was considerable variation with respect to onset of infection after therapy initiation, underlying indication for TNF alpha inhibitor therapy, the type of TNF alpha inhibitor used, and long-term outcome. The knee joint was the most common site of musculoskeletal infection, and rheumatoid arthritis was the most common underlying indication for TNF alpha inhibitor therapy. Most patients require at least 1 invasive procedure and extended antimicrobials as part of therapy. When specified, all reports indicated discontinuation of TNF alpha inhibitor therapy after identification of infection. The critical role of TNF alpha in necroptosis and pyroptosis likely allows intracellular pathogens such as Salmonellae to thrive upon TNF alpha inhibition. Conclusion TNF alpha inhibitors are used worldwide to treat a variety of rheumatic diseases. However, TNF alpha inhibitors are associated with serious infections, including atypical musculoskeletal infections. An important yet under-recognized pathogen that can cause musculoskeletal infections in patients receiving TNF alpha inhibitors is Salmonella, with several reports identified in the recent literature. We hypothesize that TNF alpha blockade disrupts the innate immune response against intracellular pathogens, in turn providing Salmonellae a golden opportunity to thrive. Importantly, the identification of Salmonella musculoskeletal infection had significant clinical implications, often requiring extensive medical and/or surgical management and interruption of TNF alpha inhibitor therapy. Clinicians should be aware of the risk of Salmonella infections in patients starting or currently receiving TNF alpha inhibitors. Patients receiving TNF alpha inhibitors should be counseled regarding best practices for reducing the risk of contracting Salmonella infection, such as avoiding high-risk foods and being vigilant while traveling abroad. [1.] Li X. Front Microbiol 2020;11:1643.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.238
Teacher spread0.233 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes2
Has abstractyes

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