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Record W4411846614 · doi:10.3899/jrheum.2025-0314.81

Baseline Power Doppler Positivity Predicts Response to Advanced Therapies in Rheumatoid Arthritis

2025· article· en· W4411846614 on OpenAlexaffvenueabout
Ümmügülsüm Gazel, Ricardo Sabido-Sauri, Sylvia Sangwa, O. Bayindir Tsechelidis, Elliot Hepworth, Sibel Zehra Aydın

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineRheumatoid arthritisPower dopplerInternal medicineBaseline (sea)Physical therapySurgeryUltrasonography

Abstract

fetched live from OpenAlex

Objectives Our recent systematic literature review highlighted the controversies regarding the predictive value of baseline power Doppler (PD) positivity on ultrasound (US) for treatment response in rheumatoid arthritis (RA), likely due to the heterogeneity of the trials and outcome measures.[1] In this study, we aimed to explore the predictive factors of response to advanced therapies in RA and whether baseline PD positivity is an independent predictor of response, by testing different response measures. Methods RA patients were recruited from the ORCHESTRA (Ottawa Rheumatology CompreHEnSive Treatment and Assessment) Clinic, where all patients with RA about to initiate a new advanced therapy are assessed following a standardized protocol, including a protocolized US of 36 joints, at baseline and three-month intervals until clinical remission is achieved. The US scoring is based on the OMERACT-EULAR definitions, where grayscale synovitis and Doppler findings in each joint are scored on a scale of 0-3. For the analysis, having at least 1 joint with a Doppler score ≥2 was classified as the Doppler-positive group, and the rest was defined as the Doppler-negative group. The groups were compared for their Delta (D) DAS28CRP (baseline minus month-3), achieving Minimal clinically important difference (MCID) (DDAS28CRP ≥0.6) and DAS28CRP remission at follow-up. A multivariate analysis was performed to understand whether baseline PD positivity is an independent predictor of achieving MCID. Results Baseline: Of 101 patients, 80 (79.2%) were classified as Doppler-positive, and 21 (20.8%) were Doppler-negative. Demographics were similar between the groups (Table). There was a trend toward baseline DAS28CRP scores being higher in the Doppler-positive group and significantly more frequent erosions on x-rays. Follow-up: In the 3-month follow-up, the Doppler-positive group had significant reductions in their DAS28CRP scores (p<0.001); but not the Doppler-negative group (p= 0.22). DDAS28CRP was numerically higher and achieving MCID was significantly more common in Doppler-positive group (Table). The percentage of patients in DAS28CRP remission at follow-up was similar between Doppler-positive and negative patients. In multivariate analysis, baseline DAS28CRP and Doppler positivity were the only predictors of achieving MCID (Table). Table. Comparison of Doppler positive and negative groups and Predictors of treatment response during follow-up in RA patients Conclusion The baseline Doppler positivity independently predicts a better response to advanced therapies in RA. However, the response may not be enough to remission due to higher baseline disease activity. The Doppler-positive patients achieved MCID 3.8 more often than the Doppler negatives. Our data encourages conducting a prospective trial using US positivity in the decision-making process for advanced therapies in RA. [1.] Gazel U. Rheumatol Adv Pract (under review).

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)0.006
metaresearch head score (Gemma)0.018
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.280
Teacher spread0.272 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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