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Record W1993626611 · doi:10.3899/jrheum.130206

Experiences with Rituximab for the Treatment of Autoimmune Diseases with Ocular Involvement

2013· article· en· W1993626611 on OpenAlexvenueno aff
Laura Pelegrín, Eva Jakob, Annette Schmidt-Bacher, Vedat Schwenger, Matthias Becker, Regina Max, Hans Martin Lorenz, Friederike Mackensen

Bibliographic record

VenueThe Journal of Rheumatology · 2013
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRituximabConcomitantRefractory (planetary science)Visual acuitySurgeryInternal medicineInflammationComplete remissionChemotherapyGastroenterologyLymphoma

Abstract

fetched live from OpenAlex

OBJECTIVE: To report the efficacy of rituximab (RTX) in the treatment of ocular or orbital inflammation accompanying autoimmune diseases refractory to previous standard immunosuppressive therapy. METHODS: We reviewed medical records of 9 consecutive patients with noninfectious ocular or orbital inflammation treated with RTX. RESULTS: Over a mean followup of 42 months, 7 patients were in clinical remission, 1 had partial response to treatment, and 1 did not respond. Best corrected visual acuity improved ≥ 1 line in 4 patients, was stable in another 4 patients, and worsened in 1. Concomitant immunosuppressive therapy was tapered in 6 cases. Systemic corticosteroids were tapered or kept below 7.5 mg a day in 5 patients 1 year after the first RTX cycle. CONCLUSION: RTX therapy, in patients who are refractory to standard immunosuppressive therapy, was effective and showed a beneficial response to treatment including induction of clinical remission of inflammation in most patients.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.235
Teacher spread0.226 · 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".

Quick stats

Citations26
Published2013
Admission routes1
Has abstractyes

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