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P001 The patient journey to diagnosis for axial Spondyloarthritis - The challenges in primary care and the positive impact of specialist axial SpA services

2024· article· en· W4405595657 on OpenAlexaff
Joe Eddison, Sian Bamford, Antoni Chan, Marian Chan, Dhivya Das, Jane Freeston, William J Gregory, Tania Gudu, Kristi Hutton, Arumugam Moorthy, Raj Sengupta, Hasan Tahir, Dale Webb

Bibliographic record

VenueLara D. Veeken · 2024
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsArthritis Society
Fundersnot available
KeywordsAxial spondyloarthritisPrimary careMedicineMedical physicsFamily medicineAnkylosing spondylitisInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background and aims The mean average time to diagnosis (TTD) in the UK for axial SpA is currently 8.29 yearsi. However, it should be possible to ensure diagnosis within 12 months of symptom onset to optimise clinical outcomesii. Current evidence suggests significant variability in the patient journey, particularly within primary care, where patients have repeat consultations for axial SpA related symptoms before being referred onward to rheumatologyiii. The National Axial Spondyloarthritis Society (NASS) TTD patient survey assesses where in the pathway patients experience most delays and the factors that may be driving these pinch points. Methods We developed a patient self-administered post-diagnosis axial SpA online survey form, and analysed the results along the pathway. Data were collected from 534 patients diagnosed since January 2021. Results The average time from first GP appointment to rheumatology referral was the longest wait, at 4.33 years (53% of the total delay). Other elements of the pathway were (mean): • 2.49 years (31%) from experiencing symptoms to seeking help from a GP, • 0.39 years (5%) waiting for a first rheumatology appointment following referral, • 0.88 years (11%) for the time from first appointment in rheumatology to formal diagnosis. Patients also reported seeing healthcare practitioners multiple times pre diagnosis. Physiotherapists (66%, n = 353) and GPs (63%, n = 337) were seen most frequently, with chiropractors (19%, n = 103) and osteopaths (17%, n = 93) seeing around a fifth of patients repeatedly. P001 Figure 1.Proportional split of average (mean) time to diagnosis by pathway. P001 Figure 2.Number of visits to other Health Care Professionals (HCPs) before receiving a formal diagnosis. Whilst specialist clinics are not possible everywhere, patients in these settings get a swifter diagnosis due to increased expertise, greater access to co-located MSK radiology services and expedited triage out of general rheumatology pools. References 1. Eddison J, et al. www.actonaxialspa.com; Webb D, et al. Act on axial SpA: A Gold Standard time for the diagnosis of axial SpA (2021); Al-Attar M, et al. Ann Rheum Dis 2021;80(Suppl 1):757.

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)0.002
metaresearch head score (Gemma)0.022
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 score0.125
Threshold uncertainty score0.419

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1250.007

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 head0.020
GPT teacher head0.285
Teacher spread0.265 · 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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Citations1
Published2024
Admission routes1
Has abstractyes

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