Hyperpigmented Macules and Patches on the Face: Exogenous Ochronosis or Lichen Planus Pigmentosus?
Bibliographic record
Abstract
We present a case of a patient with a 10-year history of blue-black macules and patches on the face and an associated history of skin-lightening cream usage. The skin lightening cream contained hydroquinone, which is often associated with exogenous ochronosis (EO). Interestingly, the biopsy did not show characteristic findings of ochronosis, confusing the final diagnosis, however discontinuing the skin-lightening creams halted the progression of the patient's skin lesions supporting a diagnosis of EO. EO presents as asymptomatic hyperpigmentation after using products containing hydroquinone. This condition is most common in Black populations, likely due to the increased use of skin care products and bleaching cream containing hydroquinone in these populations. Topical hydroquinone is FDA-approved to treat melasma, chloasma, freckles, senile lentigines, and hyperpigmentation and is available by prescription only in the US and Canada. However, with the increased use of skin-lightening creams in certain populations, it is important for dermatologists to accurately recognize the clinical features of exogenous ochronosis to differentiate it from similar dermatoses. An earlier diagnosis can prevent the progression to severe presentations with papules and nodules. We summarize the clinical presentations diagnostic features, and treatment pearls, concluding with a discussion of the differential diagnoses. J Drugs Dermatol. 2024;23(7):567-568. doi:10.36849/JDD.8248.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".