Burden of Coronary Artery Disease and Peripheral Artery Disease: A Literature Review
Bibliographic record
Abstract
BACKGROUND: Atherothrombotic disease, including coronary artery disease (CAD) and peripheral artery disease (PAD), can lead to cardiovascular (CV) events, such as myocardial infarction, stroke, limb ischemia, heart failure, and CV death. AIM: Evaluate the humanistic and economic burden of CAD and PAD and identify unmet needs through a comprehensive literature review. METHODS: Relevant search terms were applied across online publication databases. Studies published between January 2010 and August 2017 meeting the inclusion/exclusion criteria were selected; guidelines were also included. Two rounds of screening were applied to select studies of relevance. RESULTS: Worldwide data showed approximately 5-8% prevalence of CAD and 10-20% prevalence of PAD, dependent on the study design, average age, gender, and geographical location. Data from the REACH registry indicated that 18-35% of patients with CAD and 46-68% of patients with PAD had disease in one or more vascular beds. Use of medication to control modifiable CV risk factors was variable by country (lower in France than in Canada); statins and aspirin were the most widely used therapies in patients with chronic disease. Survival rates have improved with medical advancements, but there is an additional need to improve the humanistic burden of disease (i.e., associated disability and quality of life). The economic burden of atherothrombotic disease is high and expected to increase with increased survival and the aging population. CONCLUSION: CAD and PAD represent a substantial humanistic and economic burden worldwide, highlighting a need for new interventions to reduce the incidence of atherothrombotic disease.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.021 | 0.023 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".