Seborrheic Dermatitis: A Case of an Atypical Side Effect of Atypical Antipsychotics
Bibliographic record
Abstract
Dear Editor: A 40-year-old female with depression and schizophrenia presented with a new erythematous rash with thick sebum crust on the nasolabial folds, following a change in antipsychotic medication.She had previously been treated with various antidepressants and antipsychotics, including citalopram, risperidone, and quetiapine.Due to non-adherence to oral medications, she was switched to paliperidone palmitate (INVEGA SUSTENNA ® ; Janssen Pharmaceuticals) injection 150 mg every four weeks.She developed several common side effects of atypical antipsychotics, including weight gain and hyperprolactinemia.Following her second dose of paliperidone, she also developed skin changes on the nasolabial folds (Fig. 1), clinically consistent with seborrheic dermatitis (SD).She did not have known SD previously.There were no other medication changes prior to this presentation.The patient's SD did not improve significantly with topical therapy-first 2% ketoconazole with 1% hydrocortisone cream, which was subsequently changed to 2% ketoconazole with 1% salicylic acid and 3% sulfur.The patient's antipsychotic was later switched to oral aripiprazole, a third-generation antipsychotic, and her skin condition progressively resolved (Fig. 2).SD affects 1% to 3% of the general population 1,2 .While other factors including genetic predisposition and lifestyle likely also contributed to this patient's severe SD, the acute onset and timing within weeks of starting a new medication indicates potential causality with paliperidone.Based on clinical tools for assessing the causality of adverse drug reactions, including the WHO-Uppsala causality categories and Naranjo probability scale, this patient's skin changes can be classified as a probable drug reaction.The adverse reaction of SD was an objective finding documented after the suspected drug used, and only
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".