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FRI0548 Responsiveness of A New MRI Scoring Method Based on The Canada-Denmark Definitions of Lesions in The Spine and The SPARCC MRI Spine Inflammation Index in Patients with Axial Spondyloarthritis

2016· article· en· W2554268613 on OpenAlexaboutno aff
Simon Krabbe, Mikkel Østergaard, Inge Juul Sørensen, Bo Jensen, Jakob Møllenbach Møller, Lone Balding, Ole Rintek Madsen, Karsten Asmussen, Grith Eng, Susanne Juhl Pedersen

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2016
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAxial spondyloarthritisSagittal planeAdalimumabAnkylosisSpondylarthritisMagnetic resonance imagingRadiologyAnkylosing spondylitisSurgeryPathologyDisease

Abstract

fetched live from OpenAlex

Background The Spondyloarthritis Research Consortium of Canada (SPARCC) Spine Inflammation Index is a well-established MRI scoring system for vertebral body inflammation.(1) It does not take the exact anatomical location of lesions into account. The Canada-Denmark (CanDen) MRI definitions were developed to allow detailed anatomical evaluation of inflammatory and structural lesions of the vertebral bodies as well as the posterior segments in patients with axial spondyloarthritis (axSpA).(2–3) Objectives The aim of this study was to assess the distribution of scores and the responsiveness of this new method, which combines the CanDen MRI definitions into a scoring system, as compared with the SPARCC Spine Inflammation Index in an axSpA randomized controlled trial. Methods For each disco-vertebral unit, inflammatory lesions of vertebral bodies (VB) in the anterior and posterior corners on central sagittal slices were scored as 1 (small) or 2 (large). Non-corner lesions were scored as 2 (small) or 4 (large). Antero-lateral and postero-lateral inflammatory corner lesions in lateral sagittal slices were scored as 1. Inflammatory lesions in the posterior segments (PS) were each scored as 1. Fat (4), erosion and new bone formation were scored in a comparable way (details not shown due to length restrictions). 49 patients with axSpA and indication for TNFα inhibitor were randomized to placebo or adalimumab 40 mg sc. eow for 6 weeks. MRI of the spine was scored according to CanDen definitions and SPARCC by an experienced reader blinded to the clinical data. Responsiveness was assessed by standardized response mean (SRM) and Guyatt9s responsiveness index (GRI). Values ≥0.8 represent a large degree of responsiveness. Results Conclusions A new anatomy-based scoring system for spine inflammatory and structural lesions was described, demonstrating similar responsiveness as the SPARCC method. Further studies are needed to investigate the additional value of assessing posterior segments. References Maksymowych et al. Arthritis Rheum 2005;53:502–9; Lambert et al. J Rheumatol 2009;36-S84:3–17; Østergaard et al. J Rheumatol 2009;36-S84:18–34; Pedersen et al. Arthritis Res Ther 2013;15:R216 Disclosure of Interest None declared

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)0.008
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.275
Teacher spread0.245 · 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
Published2016
Admission routes1
Has abstractyes

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