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Record W2261014925

Atherosclerotic vascular events in a single large lupus cohort: prevalence and risk factors.

2007· article· en· W2261014925 on OpenAlexaffabout
Murray B. Urowitz, Dominique Ibañez, Dafna D. Gladman

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineSystemic lupus erythematosusCohortMcNemar's testInternal medicineLogistic regressionRisk factorCohort studyDisease
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine prevalence and type of atherosclerotic vascular events (AVE) occurring after entry to the University of Toronto Lupus Clinic; and to compare risk factors in patients with systemic lupus erythematosus (SLE) with AVE to matched SLE controls without AVE. METHODS: Patients with SLE attending the University of Toronto Lupus Clinic who did not have AVE prior to clinic entry were included. Patients have been followed at 2-6 months since 1970 according to a standard protocol. Cases with AVE were matched for sex, era at first clinic visit (1970s, 1980s, 1990s +), inception status, age at first visit, and duration of followup. Chi-square, Fisher's exact, paired T test, and McNemar test were used. Comparison of risk factors for the development of AVE was done using a stepwise conditional logistic regression model for matched pairs. RESULTS: In a total cohort of 1087 SLE patients followed from 1970 until 2004, the prevalence of AVE was 10.9%, and in 561 inception patients it was 9.6%. In multivariate analyses, neuropsychiatric involvement was significantly associated with AVE in both the total and inception cohorts. Smoking was also associated with AVE in the inception cohort, whereas the number of coronary artery disease (CAD) risk factors and vasculitis were significant in the total cohort. CONCLUSION: AVE are major contributors to the clinical presentation of late-stage lupus. A combination of lupus related factors and classic CAD risk factors contributed to the development of AVE.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.260
Teacher spread0.234 · 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.

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

Citations140
Published2007
Admission routes2
Has abstractyes

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