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Record W2028519033 · doi:10.3899/jrheum.130526

Late-onset Neutropenia in Patients with Rheumatoid Arthritis after Treatment with Rituximab

2014· article· en· W2028519033 on OpenAlexvenueno aff
Rita Abdulkader, Chethana Dharmapalaiah, Ginny Rose, L Shand, Gavin Clunie, Richard A. Watts

Bibliographic record

VenueThe Journal of Rheumatology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRituximabNeutropeniaRheumatoid arthritisInternal medicineIncidence (geometry)PneumoniaRheumatologyArthritisSurgeryAdverse effectGastroenterologyChemotherapyLymphoma

Abstract

fetched live from OpenAlex

OBJECTIVE: Late-onset neutropenia (LON) is an adverse effect of rituximab (RTX) in hematological malignancies, a finding that was recently reported in rheumatoid arthritis (RA). The aim of our study was to estimate its incidence in RA. METHODS: We retrospectively reviewed complete blood (cell) count of patients with RA who received RTX between October 2007 and July 2011 to identify neutropenia (≤ 1.5 × 10(9)) up to 12 months following RTX. RESULTS: One hundred eight patients received RTX, median age 64 years (range 25-86). A total of 237 cycles were given. Five patients developed LON after a median of 151 days (71-184). Two developed pneumonia. CONCLUSION: LON occurs infrequently after RTX, but can present with infection.

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)0.000
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 score0.102
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.002
GPT teacher head0.183
Teacher spread0.181 · 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

Citations38
Published2014
Admission routes1
Has abstractyes

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