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Record W2951296555 · doi:10.3899/jrheum.190238

Testing the Model for Predicting Effectiveness of Anakinra in Systemic Juvenile Idiopathic Arthritis

2019· letter· en· W2951296555 on OpenAlexvenueno aff
Seza Özen, Selcan Demir, Ezgi Deniz Batu

Bibliographic record

VenueThe Journal of Rheumatology · 2019
Typeletter
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsnot available
FundersHacettepe Üniversitesi
KeywordsMedicineAnakinraRheumatologyInternal medicineArthritisCohortJuvenilePhysical therapyPediatricsDisease

Abstract

fetched live from OpenAlex

To the Editor: We read the article by Saccomanno, et al , “Predictors of effectiveness of anakinra in systemic juvenile idiopathic arthritis,” with great interest1. They reported that shorter disease duration, fewer active joints, higher ferritin levels, and greater activity of systemic manifestations were independently correlated with achievement of complete clinical response at 1 year (CCR1) in systemic juvenile idiopathic arthritis (sJIA). They proposed a model with 4 variables (disease duration ≤ 3.9 yrs, active joint count ≤ 10, ferritin > 444 ng/ml, systemic manifestation score > 3) to predict response to anakinra in sJIA1. We have analyzed these variables and tested this model in our cohort of patients with sJIA. The patients (0–18 yrs old) treated with anakinra at Hacettepe University Pediatric Rheumatology Department between January 2006 and January 2018 were included. The patients were classified with sJIA according to the International League of Associations for Rheumatology criteria2. Demographic data, … Address correspondence to Dr. S. Ozen, Department of Pediatrics, Division of Rheumatology, Hacettepe University Faculty of Medicine, Ankara 06100, Turkey. E-mail: sezaozen{at}gmail.com

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.030
GPT teacher head0.284
Teacher spread0.255 · 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.

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

Citations3
Published2019
Admission routes1
Has abstractyes

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