Awareness and perceived risk of cardiovascular disease among individuals living with rheumatoid arthritis is low: results of a systematic literature review
Bibliographic record
Abstract
BACKGROUND: Individuals with rheumatoid arthritis (RA) are at risk of developing cardiovascular disease (CVD), but patient perceptions of CVD are not routinely assessed. We performed a systematic literature review to evaluate awareness of the association between RA and CVD, and perceived risk of CVD among individuals with RA. METHODS: Three electronic databases (MEDLINE, EMBASE, and PubMed) were searched for English language articles between the years of 1990-2018. Search terms pertained to RA, CVD, knowledge, awareness, or perceptions of CVD risk. Abstracts were screened for inclusion/exclusion by two independent reviewers. RESULTS: A total of 33 abstracts were screened and 6 underwent full review. The overall sample size was 478 subjects and included patients with established RA who were predominantly female with a mean age range of 53 to 64 years. RA disease characteristics relevant to CVD were not uniformly reported, including the use of DMARDs, corticosteroids, or NSAIDs. A high proportion of subjects (range 73 to 97%) were unaware of an increased risk of developing CVD in relation to their RA, and this frequently occurred in those with a greater number of traditional CVD risk factors. Misperceptions about CVD were common, and the majority of subjects misestimated their actual CVD risk. CONCLUSION: Individuals with RA at highest risk for CVD report low awareness and perceived risk of this comorbidity. This represents a knowledge gap in need of intervention but must be tailored to patients' needs. An understanding of the system- and individual-level barriers preventing CVD awareness is needed. Only then will approaches to improve CVD screening and management in RA be successful.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".