Unusual aseptic meningitis and cognitive syndrome in a patient under anti-TNF therapy for rheumatoid arthritis: a case report
Bibliographic record
Abstract
Case presentation: A 66-year-old female retired lawyer, with a past medical history of rheumatoid arthritis (RA) treated with Golimumab for the last 10 months, with behavioral change in the past two months, after a single dose of intra-articular corticosteroid due to articular pain. Her family claims that she became progressively agitated, easily irritated and euphoric, and made excessive expenses. She was taken to a psychiatrist and started on olanzapine and valproic acid. Subsequently, her humor became depressed, with a feeling of anguish and loss of interest in her usual activities. Due to progression, she was taken to the emergency department. Her neurological exam was only remarkable for a cognitive impairment, scoring 21 out of 30 points in the Montreal Cognitive Assessment (MoCA), with losses in visuospatial function, attention, delayed recall and orientation. Her CSF showed a mild increase in cellularity of 7 and proteins of 58, and a brain MRI showed aseptic meningitis (AM). Considering her immunosuppressed status, she was started on empirical acyclovir, ceftriaxone and ampicillin, without improvement. A CSF metagenomic was negative. Paraneoplastic investigation was also unremarkable. As an alternative diagnosis, we considered the possibility of Golimumab being the trigger for the AM; therefore, the medication was stopped and she received a course of IVIg followed by IV methylprednisolone. Upon discharge, brain MRI and MoCa improved, and on outpatient follow-up, she no longer had remarkable findings on neuroimaging and her MoCA evaluation was 28/30. Discussion: RA can cause meningitis, but its treatment can also be linked to AM by direct effect or leading to infectious meningitis due to the immunosuppressive effect. 23 cases of RA patients developing AM due to the use of anti-TNF medications were found by Yıldırım, R. et al., with half of them within the first year of exposure. There are no specific findings that differentiate rheumatoid AM from anti-TNF-induced AM, but the development of the condition after starting treatment suggests the later. Since anti-TNF agents cannot cross the blood-brain barrier, it is thought that the inhibition of tumor necrosis factor (TNF) results in paradoxical increase in its concentration within the CNS. Additionally, it can lead to immune dysregulation by inhibiting the apoptosis of self-reactive T cells. There is no consensus on treatment, but discontinuation of the precipitating drug and high-dose corticosteroids are the most common initial choices. Final comments: AM gives rise to a series of possible differential diagnoses, so a thorough investigation is mandatory. Special attention was paid to infectious etiologies, and we only pursued immunotherapy after a negative study of her CSF. It’s a known fact that medications can cause AM, and anti-TNF, already linked to a series of other neurological diseases, has to be on the list of causes when evaluating a patient.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".