A Case of Stevens–Johnson Syndrome in Recurrent Late-Stage Ovarian Cancer Patient after Management of Chronic Pain with Elastomeric Pump
Bibliographic record
Abstract
(1) Background. Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are severe mucocutaneous reactions, characterized by extensive necrosis and detachment of the epidermis. (2) Case presentation. We present a case of a 46-year-old patient with late-stage high-grade serous ovarian cancer who was primarily treated with neoadjuvant chemotherapy and interval debulking, which was followed by adjuvant chemotherapy. At first recurrence, she was again treated with chemotherapy, and due to severe abdominal pain, an elastomeric pump containing analgesics, anti-inflammatories, and ondansetron was administered. In the same month, she was admitted to the hospital due to severe dysphagia, and in the following days she developed haemorrhagic vesiculobullous lesions on the facial skin and trunk. Stevens-Johnson syndrome was confirmed and ondansetron as a plausible leading cause was discontinued. Despite multimodal treatment, her condition deteriorated, and she died. (3) Discussion and conclusion. Although gynaecologists rarely encounter Stevens-Johnson syndrome, high mortality of the disease should ensure a low threshold for diagnosing and treating this disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".