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Record W2898976193 · doi:10.3899/jrheum.180226

Does Rheumatoid Arthritis Really Improve During Pregnancy? A Systematic Review and Metaanalysis

2018· review· en· W2898976193 on OpenAlex
Hannah Jethwa, Suzanne Lam, Colette Smith, Ian Giles

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Journal of Rheumatology · 2018
Typereview
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRheumatoid arthritisPregnancyMEDLINEMeta-analysisSystematic reviewDiseasePhysical therapyPostpartum periodArthritisInternal medicineObstetrics

Abstract

fetched live from OpenAlex

OBJECTIVE: We performed a systematic review and metaanalysis to assess rheumatoid arthritis (RA) disease activity during pregnancy using objective disease activity scoring systems. METHODS: A systematic review of PubMed, EMBASE/Medline, Cochrane, and LactMed databases was performed. Our inclusion criteria for analysis were prospective studies, more than 5 patients per study, and data on RA using an objective scoring system conducted by a clinician/health professional. RESULTS: Ten studies were eligible for final analysis, which included 237 patients, of which prepartum data were available for 204 patients. Postpartum disease activity was recorded in 135 pregnancies. CONCLUSION: Disease activity improved in 60% of patients with RA in pregnancy and flared in 46.7% postpartum.

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.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.102
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.308
Teacher spread0.290 · 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