The psychological impact of Stevens–Johnson syndrome and toxic epidermal necrolysis on patients’ lives: a Critically Appraised Topic*
Bibliographic record
Abstract
CLINICAL SCENARIO: A 65-year-old man presented with a 12-h history of deteriorating rash. Two weeks previously he had completed a course of neoadjuvant chemotherapy for ductal carcinoma of the breast. On examination there were bullae, widespread atypical targetoid lesions and 15% epidermal detachment. There was no mucosal involvement on presentation, but subsequently it did evolve. Skin biopsy showed subepidermal blistering with epidermal necrosis. This confirmed our clinical diagnosis of overlap Stevens-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN). On transfer to intensive care he was anxious and fearful. MANAGEMENT QUESTION: What are the psychological impacts of SJS/TEN on this man's life? BACKGROUND: SJS and TEN have devastating outcomes for those affected. OBJECTIVES: To conduct a Critically Appraised Topic to (i) analyse existing research related to the psychological impact of SJS and TEN and (ii) apply the results to the clinical scenario. METHODS: Seven electronic databases were searched for publications focusing on the psychological impact of SJS/TEN on adults over 18 years of age. RESULTS: Six studies met the inclusion criteria. Healthcare practitioners' (HCPs') lack of information around the disorder was highlighted. Patients experienced undue stress and fear. Some patients had symptoms aligned to post-traumatic stress disorder (PTSD), anxiety and depression. DISCUSSION AND RECOMMENDATION: The evidence suggests that SJS and TEN impact psychologically on patients' lives. Education of HCPs, to address their lack of awareness and information on SJS/TEN, should facilitate their capacity to provide information and support to patients, thereby reducing patient anxiety. On discharge, a follow-up appointment with relevant HCPs to reduce the possibility of PTSD occurring should be considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".