Association Between Apolipoprotein B and Coronary Artery Disease Among Hypertensive Patients: A Systematic Review of the Prospective and Retrospective Studies
Bibliographic record
Abstract
The predictive value of apolipoprotein B (apo B) has been proven in the development of coronary artery disease (CAD) among normotensives only, but it has not been directly studied in hypertensive patients. The objective of this study is to explore the association between apo B and CAD among patients with hypertension. Search strategies were conducted on September 24, 2022, and involved the databases PubMed, Web of Science, and Scopus. The current systematic review included observational case-control and cohort study design involving adult humans, both hypertensives and normotensives. The selected studies were restricted to those written in the English language and published after 2000. Reviews, interventional, animal, and overlapping studies, grey literature, and articles without full text were excluded from the current study. The modified Newcastle-Ottawa Scale was used to assess the risk of bias for the screened studies after data extraction. Out of 3644 publications, only five studies were included in the review, including 5222 participants. Of those, 2335 were hypertensive, 733 of them developed CAD, and 296 normotensive subjects developed CAD. The average apo B was 1.09 g/l and 1.07 g/l for hypertensives and normotensives, respectively. The risk of developing CAD is higher in patients with hypertension, or those with higher apo B. Moreover, the risk of CAD was exacerbated in hypertensive participants with elevated apo B. This systematic review highlights the independent power of apo B on the development of CAD among both hypertensive and normotensive subjects.
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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 | 0.009 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".