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Management of Adult Patients With Drug Reaction With Eosinophilia and Systemic Symptoms

2023· article· en· W4388695067 on OpenAlexaff
Marie‐Charlotte Brüggen, Sarah Walsh, Milad Ameri, Natalie Anasiewicz, Emanual Maverakis, Lars E. French, S. Oro, Richiiro Abe, Michael R. Ardern‐Jones, H. Assier, A. Barbaud, Benoît Bensaïd, William Bernal, C. Bernier, Alain Brassard, Eva Březinová, Rosario Cabañas, Adela R. Cardones, Chia‐Yu Chu, Ser‐Ling Chua, V. Descamps, Biagio Didona, Sherrie J. Divito, Roni P. Dodiuk‐Gad, Scott A. Elman, Krisztián Gáspár, Charlotte G. Mørtz, Natsumi Hama, Haur Yueh Lee, Barbara Horváth, Lukas Jörg, Benjamin H. Kaffenberger, Vesta Kučinskienė, Bénédicte Lebrun‐Vignes, Rannakoe Lehloenya, Damian Meyersburg, Robert G. Micheletti, B. Milpied, Fumi Miyagawa, Arash Mostaghimi, Mirjam Nägeli, Luigi Naldi, Eva Oppel, Elizabeth J. Phillips, Tasneem Pirani, Annamari Ranki, Tarja Mälkönen, Misha Rosenbach, Carmen Sălăvăstru, D. Staumont‐Sallé, Heidi Sandberg, Jane Setterfield, Kanade Shinkai, Tetsuo Shiohara, A. Soria, Danielle Tartar, George‐Sorin Ţiplica, Stephan Traidl, Artem Vorobyev, Camilla von Wachter, Scott Worswick, Yung‐Tsu Cho

Bibliographic record

VenueJAMA Dermatology · 2023
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersNational Institute of Allergy and Infectious DiseasesLeonard M. Miller School of Medicine, University of MiamiLeonard M. Miller School of MedicineUniversity of California, San FranciscoSorbonne UniversitéLietuvos Sveikatos Mokslų UniversitetasParacelsus Medizinische PrivatuniversitätLékařská fakulta, Masarykova univerzitaMasarykova UniverzitaAssistance publique-Hôpitaux de ParisNational Taiwan University HospitalSyddansk UniversitetNational Taiwan UniversityUniversité Paris DiderotUniversity of MiamiOdense UniversitetshospitalInstitut National de la Santé et de la Recherche MédicaleCentro de Investigación Biomédica en Red de Salud MentalHelsingin ja Uudenmaan SairaanhoitopiiriHelsingin YliopistoNara Medical UniversityInselspital, Universitätsspital BernUniversitatea de Medicină şi Farmacie "Carol Davila" BucureştiDebreceni EgyetemTechnion-Israel Institute of TechnologyUniversity of PennsylvaniaRijksuniversiteit GroningenSingapore General HospitalPerelman School of Medicine, University of PennsylvaniaVanderbilt University Medical CenterUniversity of BernVanderbilt UniversityOhio State UniversityUniversitair Medisch Centrum GroningenBrigham and Women's Hospital
KeywordsMedicineEosinophiliaDermatologyDrugSystemic reactionIntensive care medicineInternal medicineImmunologyPharmacologyAllergy

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.005
GPT teacher head0.221
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations64
Published2023
Admission routes1
Has abstractyes

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