Towards an understanding of the biopsychosocial determinants of CVD in SLE: a scoping review
Bibliographic record
Abstract
OBJECTIVE: Systemic lupus erythematosus (SLE) is a chronic autoimmune condition with significant physical, mental, psychosocial and economic impacts. A main driver of SLE morbidity and mortality is cardiovascular disease (CVD). Both SLE and CVD exhibit disparities related to gender, race and other social dimensions linked with biological outcomes and health trajectories. However, the biospsychosocial dimensions of CVD in SLE populations remain poorly understood. The objective of this study was to systematically investigate the existing literature around known social factors influencing the development of CVD in SLE. METHODS: A scoping review protocol was developed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping reviews guidelines. The search strategy encompassed three main concepts: SLE, CVD and social factors. Four databases were searched (PubMed, SCOPUS, PsychINFO and CINAHL). 682 studies were identified for screening. Articles were screened in two phases (title/abstract and full text) to determine whether they fulfilled the selection criteria. RESULTS: Nine studies were included after screening. All were conducted in the USA between 2009 and 2017. Six studies (67%) were cross-sectional and three (33%) were longitudinal. Most employed SLE cohorts (n=7, 78%) and two drew from healthcare databases (n=2; 22%). We identified five main themes encompassing social factors: socioeconomic status and education (n=5; 56%), race and/or ethnicity (n=7; 78%), mental health (n=2; 22%), gender (n=3; 33%) and healthcare quality and/or insurance (n=2; 22%). Overall, low income, fewer years of education, black race and/or ethnicity, depression, male gender, lack of insurance and healthcare fragmentation were all associated with CVD risk factors and outcomes in SLE. CONCLUSIONS: While several social factors contribute to CVD in SLE populations, considerable gaps remain as many social determinants remain un(der)explored. There is rich opportunity to integrate social theory, advance conceptualisations of race and/or ethnicity and gender, expand investigations of mental health and explore novel geographical contexts. In healthcare policy and practice, identified social factors should be considered for SLE populations during decision-making and treatment, and education resources should be targeted for these groups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".