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Record W2068985697 · doi:10.1186/ar2383

Cardiovascular disease in patients with rheumatoid arthritis: results from the QUEST-RA study

2008· article· en· W2068985697 on OpenAlexfundno aff
Antonio Naranjo, Tuulikki Sokka, M.Á. Descalzo, Jaime Calvo‐Alén, Kim Hørslev‐Petersen, Reijo Luukkainen, Bernard Combe, Gerd R Burmester, Joe Devlin, Gianfranco Ferraccioli, Alessia Morelli, Monique Hoekstra, Maria Majdan, S Sadkiewicz, Miguel Ángel Belmonte, Ann‐Carin Holmqvist, Ernest Choy, Recep Tunç, Aleksander Dimić, Martin Bergman, Sergio Toloza, Theodore Pincus

Bibliographic record

VenueArthritis Research & Therapy · 2008
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
FundersYork UniversityAbbott Laboratories
KeywordsMedicineRheumatoid arthritisRheumatologyInternal medicineDiseasePhysical therapyArthritis

Abstract

fetched live from OpenAlex

INTRODUCTION: We analyzed the prevalence of cardiovascular (CV) disease in patients with rheumatoid arthritis (RA) and its association with traditional CV risk factors, clinical features of RA, and the use of disease-modifying antirheumatic drugs (DMARDs) in a multinational cross-sectional cohort of nonselected consecutive outpatients with RA (The Questionnaires in Standard Monitoring of Patients with Rheumatoid Arthritis Program, or QUEST-RA) who were receiving regular clinical care. METHODS: The study involved a clinical assessment by a rheumatologist and a self-report questionnaire by patients. The clinical assessment included a review of clinical features of RA and exposure to DMARDs over the course of RA. Comorbidities were recorded; CV morbidity included myocardial infarction, angina, coronary disease, coronary bypass surgery, and stroke. Traditional risk factors recorded were hypertension, hyperlipidemia, diabetes mellitus, smoking, physical inactivity, and body mass index. Unadjusted and adjusted hazard ratios (HRs) (95% confidence interval [CI]) for CV morbidity were calculated using Cox proportional hazard regression models. RESULTS: Between January 2005 and October 2006, the QUEST-RA project included 4,363 patients from 48 sites in 15 countries; 78% were female, more than 90% were Caucasian, and the mean age was 57 years. The prevalence for lifetime CV events in the entire sample was 3.2% for myocardial infarction, 1.9% for stroke, and 9.3% for any CV event. The prevalence for CV risk factors was 32% for hypertension, 14% for hyperlipidemia, 8% for diabetes, 43% for ever-smoking, 73% for physical inactivity, and 18% for obesity. Traditional risk factors except obesity and physical inactivity were significantly associated with CV morbidity. There was an association between any CV event and age and male gender and between extra-articular disease and myocardial infarction. Prolonged exposure to methotrexate (HR 0.85; 95% CI 0.81 to 0.89), leflunomide (HR 0.59; 95% CI 0.43 to 0.79), sulfasalazine (HR 0.92; 95% CI 0.87 to 0.98), glucocorticoids (HR 0.95; 95% CI 0.92 to 0.98), and biologic agents (HR 0.42; 95% CI 0.21 to 0.81; P < 0.05) was associated with a reduction of the risk of CV morbidity; analyses were adjusted for traditional risk factors and countries. CONCLUSION: In conclusion, prolonged use of treatments such as methotrexate, sulfasalazine, leflunomide, glucocorticoids, and tumor necrosis factor-alpha blockers appears to be associated with a reduced risk of CV disease. In addition to traditional risk factors, extra-articular disease was associated with the occurrence of myocardial infarction in patients with RA.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.032
GPT teacher head0.288
Teacher spread0.256 · 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

Citations469
Published2008
Admission routes1
Has abstractyes

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