Pruritus and Neuropsychiatric Symptoms Among Patients with Darier Disease—An Overlooked and Interconnected Challenge
Bibliographic record
Abstract
(1) Background: Darier disease (DD) is a rare autosomal dominant disorder caused by mutations in ATP2A2, a gene that encodes the sarco(endo)plasmic reticulum calcium-ATPase 2 enzyme, which disrupts calcium homeostasis in keratinocytes. Pruritus, a frequently overlooked symptom in DD, can lead to physical and emotional complications, especially in patients with DD who are genetically predisposed to psychiatric comorbidities. (2) Methods: This study aimed to analyze pruritus and other related symptoms in patients with DD and explore their correlation with neuropsychiatric conditions, psychological challenges, disease severity, and body surface area (BSA) involvement through a retrospective review of a tertiary center. (3) Results: Data from 76 patients (equal gender distribution, mean age 44 years) revealed a prevalence of pruritus of 90.8%, surpassing symptoms such as pain (34.3%) and malodor (43.4%). Burning sensations due to DD lesions were significantly correlated with the diagnosis of comorbid neuropsychiatric conditions (p = 0.047) and psychiatric medication use (p = 0.019). While pruritus correlated with disease severity and %BSA involvement, the findings were not statistically significant. Patients reporting pruritus had a significantly higher Dermatology Life Quality Index symptom score (2.4 ± 1.0), which is defined as the presence of itch, soreness, pain, or stinging, than those who did not (1.5 ± 0.6), indicating accurate symptom reporting. (4) Conclusions: In conclusion, a striking majority of patients with DD experience pruritus, with higher prevalence among those with neuropsychiatric challenges, severe Darier disease, and greater %BSA skin involvement. Clinicians should recognize pruritus as a key therapeutic target and adopt comprehensive treatment approaches that both address the neuropsychiatric comorbidities and the added psychological burden of pruritus in patients with DD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".