Status of Maternal Cardiovascular Health in American Indian and Alaska Native Individuals: A Scientific Statement From the American Heart Association
Bibliographic record
Abstract
Cardiovascular disease is the leading cause of pregnancy-related death in the United States. American Indian and Alaska Native individuals have some of the highest maternal death and morbidity rates. Data on the causes of cardiovascular disease-related death in American Indian and Alaska Native individuals are limited, and there are several challenges and opportunities to improve maternal cardiovascular health in this population. This scientific statement provides an overview of the current status of cardiovascular health among American Indian and Alaska Native birthing individuals and causes of maternal death and morbidity and describes a stepwise multidisciplinary framework for addressing cardiovascular disease and cerebrovascular disease during the preconception, pregnancy, and postpartum time frame. This scientific statement highlights the American Heart Association's factors for cardiovascular health assessment known collectively as Life's Essential 8 as they pertain to American Indian and Alaska Native birthing individuals. It summarizes the impact of substance use, adverse mental health conditions, and lifestyle and cardiovascular disease risk factors, as well as the cascading effects of institutional and structural racism and the historical trauma faced by American Indian and Alaska Native individuals. It recognizes the possible impact of systematic acts of colonization and dominance on their social determinants of health, ultimately translating into worse health care outcomes. It focuses on the underreporting of American Indian and Alaska Native disaggregated data in pregnancy and postpartum outcomes and the importance of engaging key stakeholders, designing culturally appropriate care, building trust among communities and health care professionals, and expanding the American Indian and Alaska Native workforce in biomedical research and health care settings to optimize the cardiovascular health of American Indian and Alaska Native birthing individuals.
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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 | 0.028 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".