Non-scarring patchy alopecia in patients with systemic lupus erythematosus differs from that of alopecia areata
Bibliographic record
Abstract
BACKGROUND: Non-scaring patchy alopecia associated with systematic lupus erythematosus (SLE) is sometimes mis-diagnosed as alopecia areata (AA). OBJECTIVES: Our aim was to differentiate non-scarring patchy SLE alopecia features from patchy AA. METHODS: Clinical, dermatoscopic and histopathological data from 21 SLE patients with patchy alopecia were compared with data from 21 patients with patchy AA. RESULTS: Incomplete alopecia was common in SLE alopecia patches, while AA patches exhibited complete alopecia. Exclamation-mark hairs, black dots, broken hair and yellow dots were common to AA, while hair shaft thinning and hypopigmentation, angiotelectasis, peripilar sign, perifollicular red dots, white dots and honeycomb pigment patterns were more common in SLE. Interfollicular polymorphous vessels were the most common angiotelectasis presentation in the SLE alopecia patches, but interfollicular arborizing vessels were significantly more common in non-hair-loss-affected SLE regions and in AA hair-loss regions. During follow-up, increased vellus hair was the earliest feature that emerged after treatment both in SLE and AA, while the earliest feature that disappeared was hair shaft hypopigmentation in SLE and broken hair in AA. After treatment, no SLE patients had relapse of alopecia, while 41.7% of AA patients did. CONCLUSION: Distinct clinical, dermatoscopic and histopathological features were found in SLE-associated alopecia regions, which were different from those of AA. Serological autoantibody tests are of value to confirm the differential diagnosis. Local angiotelectasis and vasculitis close to hair follicles may be involved in the pathogenesis of alopecia in SLE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".