New-Onset Salt-and-Pepper Skin Changes Associated With Vaccination and Trauma in Systemic Sclerosis: Immunity Matters
Bibliographic record
Abstract
To the Editor: In the recent issue of The Journal of Rheumatology , Chung et al1 reported the associations of perifollicular hypopigmentation with disease subtypes and organ involvement in a systemic sclerosis (SSc) cohort in the United States. Perifollicular hypopigmentation, also termed salt-and-pepper appearance , is a typical manifestation in SSc. However, as the authors mentioned,1 the etiopathogenesis is not well understood and relatively unexplored. Herein, we report 2 interesting cases that shed light on the pathogenesis of salt-and-pepper appearance. This study was approved by the Committee of Renji Hospital, Shanghai, China (ID: 2017[201]). The patients gave written informed consent to publish their case details. The first case was an Asian woman in her 40s with SSc who developed salt-and-pepper skin changes on her injected arm after influenza vaccination (Figure A). She reported that patches of erythematous swelling appeared soon after she got vaccinated, followed by pruritus and skin color change. The affected areas gradually became thicker. Physical examination showed sclerodactyly and salt-and-pepper appearance on the right arm. Laboratory examinations revealed positive anti-Scl70 antibodies. Figure. New-onset salt-and-pepper appearance secondary to vaccination or trauma. (A) … Address correspondence to Dr. L. Lu, Department of Rheumatology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 145 Middle Shandong Rd, Shanghai 200001, China. Email: lu_liangjing{at}163.com.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".