Untangling the Complex Multidimensionality of the Social Determinants of Cardiovascular Health: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The cardiovascular literature is limited by the lack of consensus on what are the best metrics for reporting social determinants of health (SDH) or social deprivation, and if they should be reported as a single metric or separately by their domains. METHODS: A systematic review of the literature on cardiovascular surgeries and procedures was conducted, identifying articles from January 1, 2010, to December 31, 2023, that studied the relationship between health outcomes after cardiovascular procedures or surgeries and SDH/social deprivation. The cardiovascular procedures/surgeries of interest were coronary and valve surgeries and procedures including coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), valve replacement or repair, and transcatheter aortic valve intervention. RESULTS: After screening 638 articles, we identified 47 papers that met our inclusion and exclusion criteria. The most common procedure evaluated was CABG and PCI; 46 of the studies focused on these 2 procedures. Almost all of the articles reported a different metric for SDH/social deprivation (41 different metrics); despite this, all of the metrics showed a consistent relationship with worse outcomes associated with greater degrees of SDH/deprivation. Only 9 reported on the individual domains of SDH/social deprivation; 3 studies showed a discordant relationship. CONCLUSIONS: Although our systematic review identified numerous articles evaluating the relationship between SDH/social deprivation in cardiovascular disease, there was substantial heterogeneity in which metric was used and how it was reported. This reinforces the need for standards as to the best metrics for SDH/social deprivation as well as best practices for reporting.
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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 | 0.064 | 0.203 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".