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Record W3178844981 · doi:10.1002/acr.24751

Bridging the Gap Between Symptom Onset and Diagnosis in Axial Spondyloarthritis

2021· article· en· W3178844981 on OpenAlexaff
Laura Passalent, Kala Sundararajan, Anthony V. Perruccio, Christopher Hawke, Peter C. Coyte, Claire Bombardier, Jeff A. Bloom, Nigil Haroon, Robert D. Inman, Y. Raja Rampersaud

Bibliographic record

VenueArthritis Care & Research · 2021
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsToronto General HospitalPublic Health OntarioArthritis SocietyUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineAxial spondyloarthritisRheumatologyInternal medicineCohortPrimary careBack painPhysical therapyLow back painAnkylosing spondylitisPathologyFamily medicineSacroiliitisAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate a stratified screening process for the early identification of axial spondyloarthritis (SpA) with consideration of the following: 1) wait times from primary care to rheumatology screen, 2) incremental precision and accuracy from primary care to rheumatology screening, and 3) diagnostic delay. METHODS: Adults with low back pain attending primary care at low back pain clinics prospectively underwent a primary standardized clinical screening. Patients with low back pain of >3 months who experienced symptom onset at age <50 years were referred for a comprehensive secondary screening by a physical therapist with advanced rheumatology training. At secondary screening, patients with features of inflammation were classified as being at a low, medium, or high risk for axial SpA versus no risk for axial SpA. Precision and accuracy of this screening strata were measured against a rheumatologist with expertise in axial SpA. RESULTS: Overall, 405 patients underwent primary and secondary screening in the present study. The study cohort had a mean ± SD age of 36.9 ± 9.9 years, and 55% were women. HLA-B27 was present in 14.4% of patients. Median wait time from primary screening to secondary screening was 15 days. Axial SpA risk assignment by rheumatologist was 64.9% for no risk or low risk for axial SpA and 35.1% for medium risk or high risk for axial SpA. The best combination of sensitivity (68%), specificity (90%), positive predictive values (80%), and negative predictive values (84%) was evident in the secondary screening. In this cohort, 15.6% of patients received a final diagnosis of axial SpA. Median low back pain duration from symptom onset to diagnosis was 2 years for nonradiographic axial SpA and 7 years for ankylosing spondylitis. CONCLUSION: A stratified interprofessional screening process can facilitate rapid diagnosis of persistent low back pain with high precision and accuracy in patients who have axial SpA.

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)0.013
metaresearch head score (Gemma)0.056
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 score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.056
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.366
Teacher spread0.307 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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