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Record W2514202827 · doi:10.3899/jrheum.160012

Safety of Biologic Agents in Elderly Patients with Rheumatoid Arthritis

2016· article· en· W2514202827 on OpenAlexvenueno aff
Atsuko Murota, Yuko Kaneko, Kunihiro Yamaoka, Tsutomu Takeuchi

Bibliographic record

VenueThe Journal of Rheumatology · 2016
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRheumatoid arthritisIncidence (geometry)Adverse effectInternal medicineElderly peopleArthritisSurgeryPediatricsGerontology

Abstract

fetched live from OpenAlex

OBJECTIVE: To clarify the safety of biologics in elderly patients with rheumatoid arthritis. METHODS: Biologics were analyzed for safety in relation to age in 309 patients. RESULTS: Young (< 65 yrs old, n = 174), elderly (65-74 yrs old, n = 86), and older elderly patients (≥ 75 yrs old, n = 49) were enrolled. Although the incidence of adverse events causing treatment withdrawal was significantly higher in elderly and old elderly compared with young patients, no difference was found between elderly and older elderly patients. Pulmonary complications were independent risk factors. CONCLUSION: Old patients require special attention, although the safety of biologics in those ≥ 75 years old and 65-74 was comparable.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0010.000

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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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

Citations37
Published2016
Admission routes1
Has abstractyes

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