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Record W2083048683 · doi:10.3899/jrheum.120570

Low Socioeconomic Status (Measured by Education) and Outcomes in Systemic Sclerosis: Data from the Canadian Scleroderma Research Group

2013· article· en· W2083048683 on OpenAlexafffundvenueabout
Samah Mansour, Ashley Bonner, Chayawee Muangchan, Marie Hudson, Murray Baron, Janet Pope

Bibliographic record

VenueThe Journal of Rheumatology · 2013
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsJewish General HospitalMcMaster UniversitySt Joseph's Health CareWestern University
FundersCanadian Institutes of Health ResearchAmgen CanadaAmgen
KeywordsMedicineErythrocyte sedimentation rateInternal medicineSocioeconomic statusScleroderma (fungus)CohortConfoundingRheumatologyDemographyProteinuriaPopulationImmunology

Abstract

fetched live from OpenAlex

OBJECTIVE: In systemic lupus erythematosus, socioeconomic status (SES) affects outcomes. SES can modify outcomes by altering timing of access to care and adherence. It is unknown whether SES affects systemic sclerosis (SSc) outcomes. Disease can affect income and cause work disability, thus education (completed long before SSc onset) may be a proxy for SES. METHODS: The Canadian Scleroderma Research Group collects annual data on patients with SSc. Baseline data were used from a prevalent cohort. Education was stratified by whether participants completed high school. Regression models assessed effects of education on organ complications and survival. RESULTS: In our study, 1145 patients with SSc had 11.0 ± 9.5 years' disease duration; 86% were women, with a mean age of 55.4 ± 12.1 years. About one-quarter did not complete high school; this was more common in older patients (p < 0.0001), men (p = 0.017), those with lower income (p < 0.0001), the unemployed (p < 0.054), smokers (p < 0.001), where DLCO was < 70% predicted (p = 0.009), in those with arthritis (p = 0.047), higher Health Assessment Questionnaire-Disability Index (p = 0.017), elevated erythrocyte sedimentation rate (p = 0.019), median C-reactive protein (p = 0.002), proteinuria (p = 0.016), steroid use ever (p = 0.039), and those more likely to have died in followup (12.7% vs 8.0%; p = 0.024). However, adjusting for confounders, there was no effect of education on mortality; whereas mortality was related to age, diffuse cutaneous SSc (dcSSc) subset, elevated pulmonary arterial (PA) pressure on echocardiography, low forced vital capacity expressed as percentage of predicted, and proteinuria (similar in the dcSSc subset and in limited cutaneous SSc), mortality was increased in older patients, those with elevated PA pressure, and those with low DLCO. CONCLUSION: Completing less education than high school was not associated with a worse prognosis in SSc after adjustment for confounding characteristics.

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)0.004
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 score0.023
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.007
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.306
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 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

Citations20
Published2013
Admission routes4
Has abstractyes

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