Management of Adult Patients With Drug Reaction With Eosinophilia and Systemic Symptoms
Bibliographic record
Abstract
Importance: Drug reaction with eosinophilia and systemic symptoms (DRESS) is a rare but potentially fatal drug hypersensitivity reaction. To our knowledge, there is no international consensus on its severity assessment and treatment. Objective: To reach an international, Delphi-based multinational expert consensus on the diagnostic workup, severity assessment, and treatment of patients with DRESS. Design, Setting, and Participants: The Delphi method was used to assess 100 statements related to baseline workup, evaluation of severity, acute phase, and postacute management of DRESS. Fifty-seven international experts in DRESS were invited, and 54 participated in the survey, which took place from July to September 2022. Main Outcomes/Measures: The degree of agreement was calculated with the RAND-UCLA Appropriateness Method. Consensus was defined as a statement with a median appropriateness value of 7 or higher (appropriate) and a disagreement index of lower than 1. Results: In the first Delphi round, consensus was reached on 82 statements. Thirteen statements were revised and assessed in a second round. A consensus was reached for 93 statements overall. The experts agreed on a set of basic diagnostic workup procedures as well as severity- and organ-specific further investigations. They reached a consensus on severity assessment (mild, moderate, and severe) based on the extent of liver, kidney, and blood involvement and the damage of other organs. The panel agreed on the main lines of DRESS management according to these severity grades. General recommendations were generated on the postacute phase follow-up of patients with DRESS and the allergological workup. Conclusions and Relevance: This Delphi exercise represents, to our knowledge, the first international expert consensus on diagnostic workup, severity assessment, and management of DRESS. This should support clinicians in the diagnosis and management of DRESS and constitute the basis for development of future guidelines.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".