<i>Clostridium septicum</i> myonecrosis in a pediatric patient with a self-reported penicillin allergy
Bibliographic record
Abstract
Infections with Clostridium septicum are especially rare in pediatric patients. C. septicum is the most common cause of spontaneous myonecrosis and is usually associated with comorbid malignancy. Treatment of choice for cases of C. septicum myonecrosis is prompt and thorough surgical debridement and antimicrobial therapy with high dose penicillin. The experience and management of C. septicum infections in patients who are unable to take penicillin are not well described, and the optimal duration of therapy is largely unknown. We describe a case of spontaneous myonecrosis in a 14-year-old receiving cytotoxic chemotherapy for Burkitt’s lymphoma who had an anecdotal history of a penicillin allergy. Her infection was initially treated with ceftazidime and metronidazole in concert with debridement but was ultimately cured with 3 weeks of intravenous penicillin therapy following a graded penicillin challenge in hospital. We observed a delayed inflammatory tissue response to a C. septicum skin, soft tissue infection that temporally corresponded to neutrophil reconstitution in our patient with severe neutropenia. Our experience demonstrates that C. septicum myonecrosis can present indolently and progress rapidly and highlights the need for clinical vigilance and repeat “second-look” surgeries. Our case also emphasizes the importance of de-labelling penicillin allergies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".