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Record W3036598699 · doi:10.1002/art.41408

Do Smoking and Socioeconomic Factors Influence Imaging Outcomes in Axial Spondyloarthritis? Five‐Year Data From the DESIR Cohort

2020· article· en· W3036598699 on OpenAlexaboutno aff
Elena Nikiphorou, Sofía Ramiro, Alexandre Sepriano, Adeline Ruyssen‐Witrand, Robert Landewé, Désirée van der Heijde

Bibliographic record

VenueArthritis & Rheumatology · 2020
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
FundersSanofiEli Lilly and Company
KeywordsMedicineAnkylosing spondylitisSocioeconomic statusCohortConfidence intervalAxial spondyloarthritisConfoundingDemographyCohort studyPhysical therapyInternal medicineSacroiliitisPopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the relationship between smoking and imaging outcomes over 5 years in axial spondyloarthritis (SpA) and to assess whether socioeconomic factors influence these relationships. METHODS: Axial SpA patients from the Devenir des Spondylarthropathies Indifferérenciées Récentes cohort were included. The following 4 imaging outcomes were assessed by 3 central readers at baseline, 2 years, and 5 years: spine radiographs (using the modified Stoke Ankylosing Spondylitis Spine Score [mSASSS]), sacroiliac (SI) joint radiographs (using the modified New York criteria), magnetic resonance imaging (MRI) of the spine (using the Spondyloarthritis Research Consortium of Canada [SPARCC] score), and MRI of the SI joint (using the SPARCC score). The explanatory variable of interest was smoking status at baseline. Interactions between smoking and socioeconomic factors (i.e., job type [blue-collar or manual work versus white-collar or nonmanual work] and education [low versus high]) were first tested, and if significant, analyses were run using separate strata. Generalized estimating equations models were used, with adjustments for confounders. RESULTS: In total, 406 axial SpA patients were included (52% male, 40% smokers, and 18% blue collar). Smoking was independently associated with more MRI-detected SI joint inflammation at each visit over the 5 years, an effect that was seen only in patients with blue-collar professions (β = 5.41 [95% confidence interval (95% CI) 1.35, 9.48]) and in patients with low education levels (β = 2.65 [95% CI 0.42,4.88]), using separate models. Smoking was also significantly associated with spinal inflammation (β = 1.69 [95% CI 0.45, 2.93]) and SI joint damage (β = 0.57 [95% CI 0.18, 0.96]) across all patients, irrespective of socioeconomic factors and other potential confounders. CONCLUSION: Strong associations were found between smoking at baseline and MRI-detected SI joint inflammation at each visit over a time period of 5 years in axial SpA patients with a blue-collar job or low education level. These findings suggest a possible role for mechanical stress amplifying the effect of smoking on axial inflammation in 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.273
Teacher spread0.249 · 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 teacher head, not a consensus.

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

Citations28
Published2020
Admission routes1
Has abstractyes

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