Incidence and natural history of intravenous immunoglobulin–induced aseptic meningitis: a retrospective review at a single tertiary care center
Bibliographic record
Abstract
BACKGROUND: Aseptic meningitis is a rare but significant complication of intravenous immunoglobulin (IVIG) therapy. The majority of literature is limited to case reports, so the true incidence of this complication is uncertain. STUDY DESIGN AND METHODS: A retrospective review of all cases of IVIG-associated adverse transfusion reactions was performed at London Health Sciences Centre (LHSC) from January 1, 2008, to December 31, 2013. All reported transfusion reactions were evaluated to identify cases of aseptic meningitis due to IVIG. All documented IVIG infusions and lumbar punctures performed during the study period were reviewed; patients with both interventions were identified and further chart review was performed to identify aseptic meningitis. RESULTS: During our study period, 1324 unique patients received a total of 11,907 IVIG infusions (554,566 g) for various conditions. Eight cases of aseptic meningitis were identified, suggesting an overall incidence of 0.60% for all patients and 0.067% for all IVIG infusions. Patients presented with symptoms within 24 to 48 hours of the infusion and were treated with antibiotics initially. The reactions were self-limited, as symptoms self-resolved within 5 to 7 days. Treatment was supportive, with subsequent IVIG infusions likely requiring preinfusion medication or possibly a switch in product formulation. CONCLUSION: This review of IVIG-induced aseptic meningitis over a 6-year period identifies a more robust estimate of incidence and risk of 0.60% and 0.067% for all patients and infusions, respectively. Given that this complication can mimic infectious meningitis and cause considerable morbidity, physicians need to be aware of this rare but important condition.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".