The State of Affairs for Cardiovascular Health Research in Indigenous Women in Canada: A Scoping Review
Bibliographic record
Abstract
Cardiovascular disease (CVD) is the leading cause of death among Indigenous peoples in Canada. As rates of CVD rise, the impacts among the growing population of Indigenous women will emerge as an important health issue. The objective of this scoping review was to advance the state of knowledge about cardiovascular health research in Indigenous women in Canada. Five databases and grey literature (non-peer reviewed works) were searched to identify all studies that reported on the prevalence, pathophysiology, diagnosis, treatment, or interventions for CVD among adult Indigenous women in Canada, including First Nations, Métis, and Inuit. Searching identified 3194 potential articles; 61 of which were included. The most commonly researched topics were the prevalence of CVD, hypertension, and dyslipidemia. Rates of CVD and associated mortality among Indigenous women appear to have surpassed those of their nonindigenous counterparts. Very little research has examined the pathophysiology, diagnosis, and treatment of CVD. Gaps in the research identified the need for sex-based analyses, comparison with nonindigenous women, comprehensive longitudinal data, assessment of diagnosis criteria, development and evaluation of cardiovascular health interventions, and a better understanding of the role of culture and traditions in the prevention and treatment of CVD among Indigenous women. Although comprehensive CVD data are lacking, rates of CVD among Indigenous women in Canada are rising and are nearing or surpassing those of nonindigenous women. This review serves as a call to action to seek further research on the pathophysiology, diagnosis, and treatment of CVD among Indigenous women from across Canada.
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 | 0.022 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.019 | 0.028 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".