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1110 Overview of the childhood systemic lupus erythematosus (cSLE) cohort in the CARRA registry

2021· article· en· W3213144847 on OpenAlexaff
Christine Bacha, Andrea Knight, Laura E. Schanberg, Mary Beth F. Son, Emily von Scheven, Aimee O. Hersh

Bibliographic record

VenueAbstracts · 2021
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineCohortSystemic lupus erythematosusRheumatologyInterquartile rangePediatricsRetrospective cohort studyLupus nephritisInternal medicineDisease

Abstract

fetched live from OpenAlex

Background The Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry is a multi-center, observational registry that collects demographic, clinical, and provider- and patient-reported data from patients with pediatric-onset rheumatic diseases in North America, Israel and Italy. This study aimed to describe the demographic features, cumulative clinical manifestations, and treatments of the childhood systemic lupus erythematosus (cSLE) cohort within the CARRA Registry. Methods Since 2015, the CARRA Registry has enrolled 10,411 patients at 70 centers. Childhood-onset SLE enrollment began in March 2017. We performed a retrospective cohort study of patients with cSLE enrolled in the US between March 2017 to December 2020. Inclusion criteria for participants in the CARRA cSLE Registry include: 1) diagnosis of cSLE at <18 years based on American College of Rheumatology (ACR) or Systemic Lupus Erythematosus International Collaborating Clinics (SLICC) ; 2) enrollment within two years of cSLE diagnosis or at the time of a flare of lupus nephritis; and 3) enrollment prior to 21 years of age. Sociodemographic and clinical data were summarized using descriptive statistics. Results The current registry cohort includes 671 participants with cSLE. The majority are female (85%) with mean age at enrollment of 14.3 (SD 2.9) years. The cohort is both ethnically and racially diverse (table 1). Socioeconomic status varies widely, noting 12.5% having a household income below $25,000/year. The median time from symptom onset to diagnosis was two months (interquartile range (IQR) 25 days to 6 months), from diagnosis to enrollment was 5 (IQR 1-15) months, and from enrollment to end of follow up was 14 (IQR 6 to 23) months. At the end of the follow-up period, more than 60% of participants developed nephritis as defined by ACR or SLICC criteria. 6.1% and 10% had neurological manifestations per ACR and SLICC criteria, respectively (table 2). Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) at enrollment was a median of 4 (IQR 2-10). Most patients were prescribed hydroxychloroquine. In the first 2-3 years of disease, participants received a variety of immunosuppressive therapies including Mycophenolate Mofetil, Cyclophosphamide, Azathioprine, Rituximab, Belimumab and disease modifying anti-rheumatic drugs such as Leflunomide and Methotrexate. 84% of patients were prescribed either oral or intravenous glucocorticoids during their disease course (table 3). Conclusions The CARRA Registry has enrolled a racially and ethnically diverse cohort of cSLE patients in the early course of their disease. These participants exhibit moderate disease activity and although the use of hydroxychloroquine in this cohort is high, a significant proportion of patients are utilizing glucocorticoids at the last study visit. We anticipate enrolling a minimum of 1000 participants with more than ten years of follow-up. This cohort, which is one of the Centers for Disease Control (CDC) funded SLE registries, provides a unique opportunity to describe the natural history, treatments, and outcomes in patients with cSLE.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.025
GPT teacher head0.291
Teacher spread0.266 · 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 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".

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Citations1
Published2021
Admission routes1
Has abstractyes

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