A case of pediatric serum sickness like reaction (SSLR) after a 2-month re-exposure to amoxicillin
Bibliographic record
Abstract
Abstract Background Serum-sickness like reactions (SSLRs) to amoxicillin have been documented in the medical literature. Beta-lactams are important and commonly used medications especially in the pediatric population. Often, SSLRs present within days of and during first exposure/ingestion to the offending agent. We described a unique case of a 4-year-old boy who presented with symptoms of amoxicillin SSLR following his second course of amoxicillin with only 2 months and 10 days between his second and first course. Case presentation A 4-year-old boy presented to hospital with a pruritic rash on day 7 of a 10-day course of amoxicillin for otitis media accompanied by fever (38.7 degrees Celsius). On day 7 of his second course of amoxicillin, which was separated from his first course by only 2 months and 10 days, his mother noticed erythematous, raised, pruritic lesions with central clearing on his sternum. He presented to the ED with emesis, progression of the rash to his torso, back, legs, and face, hypotension, angioedema, and joint pain. His bloodwork demonstrated a leukocytosis of 18.6 × 10 9 g/L with neutrophilic predominance and thrombocytosis with a platelet count of 653 × 10 9 g/L. He was treated with 5 mg oral cetirizine daily and 1 mg/kg oral prednisone which improved his rash and angioedema. He was managed with up to 4 times the usual dose of cetirizine. He was assessed in our outpatient clinic as an outpatient and penicillin skin testing was unremarkable. A diagnosis of a probable SSLR to amoxicillin was made. Conclusion We report an unusual presentation of SSLR following re-exposure to amoxicillin. Our case highlights that patients with previous asymptomatic exposure to amoxicillin can develop SSLR with repeat exposure. Although it is not uncommon for children to develop amoxicillin SSLRs after previous exposure to the drug, this case is unique because of its short time course of 2 months and 10 days months between drug courses. Penicillins are commonly used in the pediatric population. Therefore, it is important to correctly characterize adverse drug reactions to broaden our understanding of SSLRs, prevent unnecessary avoidance of the triggering agent, and improve patient management.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| 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".