Unmet Educational Needs and Clinical Practice Gaps in the Management of Generalized Pustular Psoriasis: Global Perspectives from the Front Line
Bibliographic record
Abstract
INTRODUCTION: Generalized pustular psoriasis (GPP) is a rare, potentially life-threatening, neutrophilic, autoinflammatory skin disease characterised by recurrent flares of generalised sterile pustules and associated systemic features. Inconsistent diagnostic criteria and a lack of approved therapies pose serious challenges to GPP management. Our objectives were to discuss the challenges encountered in the care of patients with GPP and identify healthcare provider (HCP) educational needs and clinical practice gaps in GPP management. METHODS: On 24 July 2020, 13 dermatologists from 10 countries (Brazil, Canada, China, Egypt, France, Germany, Japan, Malaysia, the UK and the USA) attended a workshop to share experiences in managing patients with GPP. Educational needs and clinical practice gaps grouped according to healthcare system level were discussed and ranked using interactive polling. RESULTS: Lack of experience of GPP among HCPs was identified as an important individual HCP-level clinical practice gap. Limited understanding of the presentation and pathogenesis of GPP among non-specialists means misdiagnosis is common, delaying referral and treatment. In countries where patients may present to general practitioners or emergency department HCPs, GPP is often mistaken for an infection. Among dermatologists who can accurately diagnose GPP, limited knowledge of treatments may necessitate referral to a colleague with more experience in GPP. At the organisational level, important needs identified were educating emergency department HCPs to recognise GPP as an autoinflammatory disease and improving communication, cooperation and definitions of roles within multidisciplinary teams supporting patients with GPP. At the regulatory level, robust clinical trial data, clear and consistent treatment guidelines and approved therapies were identified as high priorities. CONCLUSIONS: The educational imperative most consistently identified across the participating countries is for HCPs to understand that GPP can be life-threatening if appropriate treatment initiation is delayed, and to recognise when to refer patients to a colleague with more experience of GPP management.
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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".