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P119 The patient journey and monitoring for interstitial lung disease in patients with rheumatoid arthritis in the UK

2025· article· en· W4409898830 on OpenAlexaff
Ailsa Bosworth, Sally Matthews, Ben Doostdar, Barbara Brown Taylor, P. Emery

Bibliographic record

VenueLara D. Veeken · 2025
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsArthritis Society
Fundersnot available
KeywordsRheumatoid arthritisInterstitial lung diseaseMedicineDiseaseLungIntensive care medicineInternal medicineDisease monitoringPhysical therapy

Abstract

fetched live from OpenAlex

Abstract Background/Aims Interstitial lung disease (ILD) is a common feature in connective tissue diseases (CTDs), including rheumatoid arthritis (RA). We conducted a global survey of patients with CTDs to understand the patient journey, awareness and experience of monitoring for ILD, and how patients understand their care regarding lung involvement. Here, we present data for UK-based patients with RA. Methods This was a cross-sectional online survey of patients living in the UK, aged ≥18 years with CTD, including RA, with or without ILD. Participants had a self-reported medical diagnosis of ≥ 1 CTD and were seeing a specialist doctor (e.g., rheumatologist, respiratory physician) who led care for their first diagnosed CTD. Recruitment was carried out via patient organisations sharing the survey link with their patient community, links shared on Boehringer Ingelheim social and local media channels, and QR codes on posters/flyers in clinical settings. The survey ran from 26 February to 15 March 2024. Results A total of 184 participants with RA completed the survey, with a mean (standard deviation [SD]) age of 58 years (11.7), and 96% were female. The primary physician for all participants was a rheumatologist, with 95% usually attending a hospital care setting. On average, there were 1.7 years (SD 4.6) between first symptom of RA and RA diagnosis. Initial symptoms experienced included joint pain (83%) and swollen joints (63%). Approximately 30% of participants had also been diagnosed with a lung condition: asthma (20%), and ILD or pulmonary fibrosis (7%). A total of 63% reported that their lungs were screened/checked since diagnosis with RA, most frequently as a check before starting a new medication (45%). The most common test received was a chest X-ray (56%), typically as a one-off, requested by a primary care physician or rheumatologist. A small number (7%) reported that their lung function had been screened, but did not know why, and 37% had not been screened or could not remember being screened. Only 28% had received a pulmonary function test, while 79% reported that they had not had a doctor listening to their breathing with a stethoscope, and 85% had never had any type of computed tomography imaging of their chest. Most participants (85%) considered it to be extremely important for lung function to be monitored; for 93%, this was because action could be taken if changes were found, and for 78%, so that they could learn how to deal with any changes. Conclusion Patients with RA had a mixed experience of monitoring for lung manifestations. There remains a need for a change in practice to improve the diagnostics and monitoring of lung involvement in patients with RA, and for patient education on the reasons for monitoring for lung health. Disclosure A. Bosworth: Honoraria; AbbVie Ltd (paid to National Rheumatoid Arthritis Society), Biogen Idec Limited (paid to National Rheumatoid Arthritis Society), Boehringer Ingelheim Ltd (paid to National Rheumatoid Arthritis Society), Eli Lilly and Company Limited (paid to National Rheumatoid Arthritis Society), Fresenius Kabi Limited (paid to National Rheumatoid Arthritis Society), Galapagos Biotech Limited (paid to National Rheumatoid Arthritis Society), Inmedix Inc. (paid to National Rheumatoid Arthritis Society), Medac Pharma LLP (paid to National Rheumatoid Arthritis Society), Pfizer Limited (paid to National Rheumatoid Arthritis Society), Sandoz Limited (paid to National Rheumatoid Arthritis Society), UCB Pharma Ltd (paid to National Rheumatoid Arthritis Society). S. Matthews: None. B. Doostdar: Corporate appointments; Employee of Boehringer Ingelheim. B. Taylor: Corporate appointments; Employee of Boehringer Ingelheim. P. Emery: Consultancies; Consulting fees from AbbVie, AstraZeneca, Bristol Myers Squibb, Boehringer Ingelheim, Galapagos, Gilead, Janssen, MSD, Lilly, Novartis, Pfizer, Roche and Samsung. Honoraria; AbbVie (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events), AstraZeneca (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events), Bristol Myers Squibb (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events), Boehringer Ingelheim (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events), Galapagos (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events), Gilead (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events), Lilly (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events), Novartis (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events), Pfizer (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events), Roche (payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events). Other; Support for attending meetings and/or travel from Lilly and Novartis.

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)0.007
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 score0.019
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.006
GPT teacher head0.242
Teacher spread0.236 · 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".

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Citations0
Published2025
Admission routes1
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