Real-world cardiovascular disease burden in patients with atherosclerotic cardiovascular disease: a comprehensive systematic literature review
Bibliographic record
Abstract
OBJECTIVE: Based on randomized controlled trials (RCTs), non-fatal myocardial infarction (MI) rates range between 9 and 15 events per 1000 person-years, ischemic stroke between 4 and 6 per 1000 person-years, CHD death rates between 5 and 7 events per 1000 person-years, and any major vascular event between 28 and 53 per 1000 person-years in patients with atherosclerotic cardiovascular disease (ASCVD). We reviewed global literature on the topic to determine whether the real-world burden of secondary major adverse cardiovascular events (MACEs) is higher among ASCVD patients. METHODS: We searched PubMed and Embase using MeSH/keywords including cardiovascular disease, secondary prevention and observational studies. Studies published in the last 5 years, in English, with ≥50 subjects with elevated low-density lipoprotein cholesterol (LDL-C) or on statins, and reporting secondary MACEs were included. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of each included study. RESULTS: Of 4663 identified articles, 14 studies that reported MACE incidence rates per 1000 person-years were included in the review (NOS grades ranged from 8 to 9; 2 were prospective and 12 were retrospective studies). Reported incidence rates per 1000 person-years had a range (median) of 12.01-39.9 (26.8) for MI, 13.8-57.2 (41.5) for ischemic stroke, 1.0-94.5 (21.1) for CV-related mortality and 9.7-486 (52.6) for all-cause mortality. Rates were 25.8-211 (81.1) for composite of MACEs. Multiple event rates had a range (median) of 60-391 (183) events per 1000 person-years. CONCLUSIONS: Our review indicates that MACE rates observed in real-world studies are substantially higher than those reported in RCTs, suggesting that the secondary MACE burden and potential benefits of effective CVD management in ASCVD patients may be underestimated if real-world data are not taken into consideration.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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".