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Record W4403303293 · doi:10.1016/j.kint.2024.09.012

Outcomes from the International Society of Nephrology Hemolytic Uremic Syndromes International Forum

2024· article· en· W4403303293 on OpenAlexaff
David Kavanagh, Gianluigi Ardissino, Vicky Brocklebank, Romy N. Bouwmeester, Arvind Bagga, Rob ter Heine, Sally Johnson, Christoph Licht, Alison Lap‐tak, Marina Noris, Manuel Praga, Éric Rondeau, Aditi Sinha, Richard J. Smith, Neil Sheerin, H. Trimarchi, Jack F.M. Wetzels, Marina Vivarelli, Nicole C. A. J. van de Kar, Larry A. Greenbaum, Adrian Lungu, Aleksandra Żurowska, Alexandra Gerogianni, Anne M. Durkan, Anne M. Schijvens, Anne-Laure Lapeyraque, Anuja Java, Atif Awan, Bianca Covella, Bradley P. Dixon, Carine El Sissy, Caroline Duinevel, Christine Maville, Daniel Turudić, Diana Karpman, Dieter Haffner, Elżbieta Trembecka-Dubel, Fatih Özaltın, Francesco Emma, Franz Schaefer, Hee Gyung Kang, Hernán Trimarchi, Hernando Trujillo, Ifeoma Ulasi, Alex Ekwueme, Jan Menne, Jeffrey Laurence, Joaquim Calado, Johannes Hofer, Julien Zuber, Jun Oh, Karmila Abu Bakar, Danko Milošević, Gema Ariceta, Kathleen Claes, Kati Kaartinen, Khalid Alhasan, Kioa L. Wijnsma, Lambertus P. van den Heuvel, Laura Alconcher, Maria Izabel de Holanda, Maria Szczepańska, Marie-Sophie Meuleman, Mathieu Lemaire, Meredith Harris, Michael G. Michalopulos, Michal Malina, Mihály Józsi, Nataša Stajić, Nicole M. Isbel, Patrick R. Walsh, Paula Coccia, Raja Ramachandran, Rezan Topaloğlu, Sjoerd A.M.E.G. Timmermans, Sophie Chauvet, Tanja Kersnik Levart, Tomáš Seeman, Velibor Tasić, Vladimı́r Tesař, Wen‐Chao Song, Yuzhou Zhang, Zoltán Prohászka

Bibliographic record

VenueKidney International · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesMedical Research CouncilNational Institutes of HealthIdorsia PharmaceuticalsSamsungAkershus UniversitetssykehusSwedish Orphan BiovitrumApellis PharmaceuticalsOmeros CorporationTherakosBioCrystAlnylam PharmaceuticalsAlexion PharmaceuticalsSanofiGlaxoSmithKlineBristol-Myers SquibbAstraZenecaPfizer
KeywordsNephrologyMedicineInternal medicineHaemolytic-uraemic syndromeIntensive care medicineChemistryBiochemistry

Abstract

fetched live from OpenAlex

Hemolytic uremic syndromes (HUSs) are a heterogeneous group of conditions, only some of which are mediated by complement (complement-mediated HUS). We report the outcome of the 2023 International Society of Nephrology HUS International Forum where a global panel of experts considered the current state of the art, identified areas of uncertainty, and proposed optimal solutions. Areas of uncertainty and areas for future research included the nomenclature of HUS, novel complement testing strategies, identification of biomarkers, genetic predisposition to atypical HUS, optimal dosing and withdrawal strategies for C5 inhibitors, treatment of kidney transplant recipients, disparity of access to treatment, and the next generation of complement inhibitors in complement-mediated HUS. The current rationale for optimal patient management is described.

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)0.003
metaresearch head score (Gemma)0.012
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: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.002

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 head0.021
GPT teacher head0.280
Teacher spread0.259 · 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
GenreOther

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".

Quick stats

Citations21
Published2024
Admission routes1
Has abstractyes

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