Effect of Increased Level of Lipoprotein(a) on Cardiovascular Outcomes in Patients With Ischemic Heart Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Lipoprotein(a) (Lp(a)) has emerged as a significant cardiovascular risk factor, particularly in patients with ischemic heart disease (IHD). This systematic review and meta-analysis aimed to synthesize evidence on the impact of Lp(a) levels on cardiovascular outcomes in IHD patients. A comprehensive literature search was conducted across multiple databases, covering publications from January 2016 to October 2024. Studies assessing the relationship between Lp(a) levels and cardiovascular outcomes in IHD patients were included. The primary outcomes were major adverse cardiovascular events (MACE), all-cause mortality, myocardial infarction, and revascularization. Quality assessment was performed using the Newcastle-Ottawa Scale. Fourteen studies (five prospective, nine retrospective) met the inclusion criteria, with sample sizes ranging from 350 to 18,544 participants. Pooled analysis revealed that elevated Lp(a) levels were significantly associated with increased risk of MACE (HR: 1.31, 95% CI: 1.19-1.45), all-cause mortality (HR: 1.23, 95% CI: 1.15-1.31), myocardial infarction (HR: 1.20, 95% CI: 1.06-1.35), and revascularization (HR: 1.23, 95% CI: 1.08-1.39) in IHD patients. Sensitivity analyses confirmed the robustness of these findings. This meta-analysis provides strong evidence that elevated Lp(a) levels are associated with adverse cardiovascular outcomes in IHD patients. The findings underscore the potential role of Lp(a) as an important prognostic marker and suggest that incorporating Lp(a) assessment into clinical practice could enhance risk stratification. Future research should focus on establishing optimal Lp(a) cutoff values and evaluating the impact of Lp(a)-lowering therapies on cardiovascular outcomes in this high-risk population.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".