Clinical and histological features of fixed drug eruption: a single-centre series of 73 cases with comparison between bullous and non-bullous forms
Bibliographic record
Abstract
The clinical and pathological aspects of fixed drug eruption (FDE) have been described based on a few case series. To compare bullous FDE (BFDE) and non-bullous FDE (NBFDE) and to determine whether BFDE can be histologically distinguished from other dermatoses presenting with an apoptotic pan-epidermolysis. In this retrospective monocentre study (2005-2016), FDE was classified as BFDE or NBFDE and localized (one anatomical site) or generalized (≥ two sites; GBFDE). Clinical data were extracted from charts, and images were reviewed. Skin biopsies were analysed and compared to the clinical presentation. Three dermatopathologists, blinded to the final clinical diagnosis, evaluated a subset of BFDE cases (n = 8) and 25 biopsies of other bullous diseases known to have an epidermal necrolysis (EN)-like pattern. In total, 73 patients were included in the study. Patients with BFDE (n = 58; GBFDE n = 48) were significantly older (p < 0.001). All patients with GBFDE were hospitalized; 25 had a complication (infectious; n = 19), and eight died (median age: 80). Histology revealed spongiotic (6.7%), interface dermatitis (48.3%) and EN-like (66.3%) patterns. The EN-like pattern was more frequent in BFDE than NBFDE (74% vs 27%; p = 0.008). Melanophages (100% vs 66%; p = 0.02) and massive dermal melanosis (40% vs 4%; p = 0.0005) were more prominent in NBFDE than BFDE. BFDE could not be reliably distinguished from other bullous diseases with EN-like patterns. BFDE belongs to the spectrum of skin conditions with an EN pattern, for which the concept of acute syndrome of apoptotic pan-epidermolysis (ASAP) was previously introduced. Clinical-pathological correlation is mandatory for a diagnosis of BFDE.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".