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Record W4377940237 · doi:10.1136/rmdopen-2023-003110

Grip strength reduction in clinically suspect arthralgia: natural trajectories and improvement after treatment

2023· letter· en· W4377940237 on OpenAlexfundno aff
Doortje I Krijbolder, Fenne Wouters, Ellis Niemantsverdriet, Annette H M van der Helm–van Mil

Bibliographic record

VenueRMD Open · 2023
Typeletter
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
FundersZonMwEuropean CommissionArthritis SocietyDutch Arthritis Society
KeywordsMedicineSuspectReduction (mathematics)Grip strengthPhysical medicine and rehabilitationPhysical therapy

Abstract

fetched live from OpenAlex

Decreased hand function is a major contributor to disease burden in rheumatoid arthritis (RA) and is present in most patients with RA at diagnosis.1 2 Recent research showed that hand function is reduced in the symptomatic prearthritis phase of clinically suspect arthralgia (CSA) and is a reflection of subclinical tenosynovitis.3 Grip strength (GS) measured with a dynamometer had the highest sensitivity for decreased hand function and underlying tenosynovitis, compared with other assessment methods of hand function.3 Although this may suggest that the dynamometer could be a practical assessment in CSA to objectify functional impairments originating from subclinical joint inflammation, it needs to be determined if dynamometer-based GS assessments in CSA are sensitive to change and mirror the disease course of CSA. To our best knowledge, longitudinal studies on GS in the phases preceding RA diagnosis are lacking. We hypothesised that GS follows distinct natural trajectories in patients with CSA who have contrasting disease courses (RA development, persistent CSA symptoms without RA development and spontaneous resolution of arthralgia). Second, since it was recently shown that a temporary methotrexate treatment in CSA resulted in sustained improvements of subclinical joint inflammation, we hypothesised that GS is responsive to treatment in the CSA phase.4

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.025
GPT teacher head0.328
Teacher spread0.303 · 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 designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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