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Record W2887265391 · doi:10.1016/j.ekir.2018.07.021

Clinical Characteristics and Treatment Patterns of Children and Adults With IgA Nephropathy or IgA Vasculitis: Findings From the CureGN Study

2018· article· en· W2887265391 on OpenAlexafffund
David T. Selewski, Josephine M. Ambruzs, Gerald B. Appel, Andrew S. Bomback, Raed Bou Matar, Yi Cai, Daniel C. Cattran, Aftab S. Chishti, Vivette D. D’Agati, Cynthia D’Alessandri-Silva, Rasheed Gbadegesin, Jonathan Hogan, Sandra Iragorri, J. Charles Jennette, Bruce A. Julian, Myda Khalid, Richard Lafayette, Helen Liapis, Francesca Lugani, Sarah Mansfield, Sherene Mason, Patrick H. Nachman, Cynthia C. Nast, Carla Nester, Damien Noone, Jan Novák, Michelle M. O’Shaughnessy, Heather N. Reich, Michelle N. Rheault, Dana V. Rizk, Manish K. Saha, Neil Sanghani, C. John Sperati, Rajasree Sreedharan, Tarak Srivastava, Agnieszka Swiatecka‐Urban, Katherine Twombley, Tetyana L. Vasylyeva, Donald J. Weaver, Hong Yin, Jarcy Zee, Ronald J. Falk, Ali G. Gharavi, Brenda W. Gillespie, Debbie S. Gipson, Larry A. Greenbaum, Lawrence B. Holzman, Matthias Kretzler, Bruce Robinson, William E. Smoyer, Michael F. Flessner, Lisa M. Guay‐Woodford, Krzysztof Kiryluk, Wooin Ahn, Rupali S. Avasare, Revekka Babayev, Ibrahim Batal, Eric J. Brown, Eric S. Campenot, Pietro A. Canetta, Brenda Chan, Hilda Fernández, Bartosz Foroncewicz, Gian Marco Ghiggeri, William H. Hines, Namrata G. Jain, Fangming Lin, Maddalena Marasà, Glen S. Markowitz, Sumit Mohan, Krzysztof Mucha, Thomas L. Nickolas, Jai Radhakrishnan, Maya K. Rao, Renu Regunathan-Shenk, Simone Sanna‐Cherchi, Dominick Santoriello, Michael B. Stokes, Natalie Yu, Anthony M. Valeri, Ronald Zviti, Amira Al‐Uzri, Isa Ashoor, Diego Avilés, Rossana Baracco, John Barcia, Sharon Bartosh, Craig W. Belsha, Michael Braun, Donna Claes, Carl H. Cramer, Keefe Davis, Elif Erkan, Daniel I. Feig, Michael Freundlich, Melisha Hanna, Guillermo Hidalgo, Amrish Jain, Mahmoud Kallash, Jerome C. Lane, John D. Mahan, Nisha Mathews, Cynthia G. Pan, Hiren Patel, Adelaide Revell, Julia Steinke, Scott E. Wenderfer, Craig S. Wong, W. James Cook, Vimal K. Derebail, Agnes B. Fogo, Adil Gasim, Todd W.B. Gehr, Raymond C. Harris, Jason M. Kidd, Louis‐Philippe Laurin, Will Pendergraft, Vincent Pichette, Thomas Brian Powell, Matthew B. Renfrow, Virginie Royal, Sharon G. Adler, Charles E. Alpers, Elizabeth Brown, Michael Choi, Katherine M. Dell, Ram Dukkipati, Fernando C. Fervenza, Alessia Fornoni, Crystal A. Gadegbeku, Patrick E. Gipson, Leah Hasely, Sangeeta Hingorani, Michelle Hladunewich, J. Ashley Jefferson, Kenar D. Jhaveri, Duncan B. Johnstone, Frederick J. Kaskel, Amy Kogan, Jeffrey B. Kopp, Kevin V. Lemley, Laura Malaga- Dieguez, Kevin Meyers, Alicia M. Neu, John F. O’Toole, Rulan S. Parekh, Kimberly J. Reidy, Helbert Rondon‐Berrios, Kamalanathan K. Sambandam, John R. Sedor, Christine B. Sethna, Jeffrey R. Schelling, Howard Trachtman, Katherine R. Tuttle, Joseph Weisstuch, Olga Zhdanova, Laura Barisoni, Laura Mariani, Matthew Wladkowski

Bibliographic record

VenueKidney International Reports · 2018
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of TorontoUniversity Health Network
FundersChildren's Hospital of PittsburghFeinberg School of MedicineMedical Center, University of PittsburghUniversity of California, Los AngelesUniversity of OklahomaNorthwell HealthCedars-Sinai Medical CenterNephcure FoundationChildren's National HospitalJohns Hopkins UniversityUniversity of WashingtonUniversity of Oklahoma Health Sciences CenterHospital for Sick ChildrenUniversity of MiamiYork UniversityNorthwestern UniversityUniversity of PittsburghNationwide Children's HospitalChildren's Hospital of PhiladelphiaUniversity of TorontoCleveland ClinicNational Institute of Diabetes and Digestive and Kidney DiseasesTemple UniversityVirginia Commonwealth UniversityVanderbilt UniversitySeattle Children's Research InstituteUniversity of PennsylvaniaTexas Children's Hospital
KeywordsMedicineNephropathyCohortInternal medicineFocal segmental glomerulosclerosisGlomerulonephritisKidney diseaseBiopsyRenal functionGastroenterologyCohort studyKidneyEndocrinologyDiabetes mellitus

Abstract

fetched live from OpenAlex

IntroductionThe Cure Glomerulonephropathy Network (CureGN) is a 66-center longitudinal observational study of patients with biopsy-confirmed minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, or IgA nephropathy (IgAN), including IgA vasculitis (IgAV). This study describes the clinical characteristics and treatment patterns in the IgA cohort, including comparisons between IgAN versus IgAV and adult versus pediatric patients.MethodsPatients with a diagnostic kidney biopsy within 5 years of screening were eligible to join CureGN. This is a descriptive analysis of clinical and treatment data collected at the time of enrollment.ResultsA total of 667 patients (506 IgAN, 161 IgAV) constitute the IgAN/IgAV cohort (382 adults, 285 children). At biopsy, those with IgAV were younger (13.0 years vs. 29.6 years, P < 0.001), more frequently white (89.7% vs. 78.9%, P = 0.003), had a higher estimated glomerular filtration rate (103.5 vs. 70.6 ml/min per 1.73 m2, P < 0.001), and lower serum albumin (3.4 vs. 3.8 g/dl, P < 0.001) than those with IgAN. Adult and pediatric individuals with IgAV were more likely than those with IgAN to have been treated with immunosuppressive therapy at or prior to enrollment (79.5% vs. 54.0%, P < 0.001).ConclusionThis report highlights clinical differences between IgAV and IgAN and between children and adults with these diagnoses. We identified differences in treatment with immunosuppressive therapies by disease type. This description of baseline characteristics will serve as a foundation for future CureGN studies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.014
GPT teacher head0.297
Teacher spread0.283 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations79
Published2018
Admission routes2
Has abstractyes

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