Immune Reconstitution Inflammatory Syndrome Mimicking Progressive Multifocal Leucoencephalopathy in a Multiple Sclerosis Patient Treated With Natalizumab: A Case Report and Review of the Literature
Bibliographic record
Abstract
Natalizumab (NTM) represents an effective drug for the treatment of relapsing-remitting multiple sclerosis (RRMS). Progressive multifocal leucoencephalopathy (PML) is a potential life-threatening complication of NTM treatment. A close follow-up and MRI monitoring of patients under NTM are required to avoid such devastating complications. The case of a 47-year-old woman with RRMS (EDSS 1.5) treated with NTM for 44 months is reported. The patient had a relapse with mild cerebellar symptomatology and visual complaints. MRI revealed a new area of abnormal signal intensity in the subcortical white matter of the right parietal lobe with mild peripheral enhancement. Visual fields showed scotomata mostly of the left eye. NTM was discontinued. JC virus (JCV) polymerase chain reaction (PCR) in cerebrospinal fluid was negative. The patient received IV corticosteroids for 5 days and then monthly for 2 months with subsequent clinical and MRI improvement. On month 4, she presented with a new relapse with severe ataxia, mild behavioral change, increase of cerebellar symptoms and internuclear opthalmoplegia (EDSS 3.5). MRI showed reappearance of the right parietal lobe lesion, with decreased size and less pronounced contrast enhancement. A new 2-cm lesion was noted in the left cerebellar hemisphere with a speckled pattern of contrast enhancement. JCV PCR was negative and the patient was treated with IV corticosteroids. On month 12, she demonstrated clinical and MRI improvement. Although initially PML was highly suspected in this patient, the clinical and MRI findings were supportive of the presence of immune reconstitution inflammatory syndrome (IRIS).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| 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".