Bibliographic record
Abstract
OBJECTIVE: To report a case of recurrent aseptic meningitis temporally associated with the use of ibuprofen. CASE SUMMARY: A previously well 51-year-old white man presented with acute confusion and aphasia 7 days after taking a variety of nonprescription medications, including ibuprofen. Imaging of the brain was unremarkable, and lumbar puncture revealed lymphocytic pleocytosis with an elevated protein level. The symptoms improved shortly after admission, and no infectious cause was identified. Two weeks later, the patient was readmitted with similar symptoms beginning immediately after resumption of ibuprofen. His symptoms resolved promptly after ibuprofen was discontinued. DISCUSSION: Drug-induced aseptic meningitis is an unusual complication of drug therapy. Nonsteroidal antiinflammatory drugs (NSAIDs), particularly ibuprofen, are among the most commonly implicated agents, but rechallenge with the suspected agent is uncommon. Use of an objective causality tool indicated a probable relationship between ibuprofen and development of aseptic meningitis in our patient. CONCLUSIONS: Clinicians should consider NSAIDs as potential causes of aseptic meningitis, especially in patients with recurrent illness and no obvious infectious cause. A detailed drug history is invaluable in the assessment of such patients, with particular attention to nonprescription medications such as ibuprofen.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".