Blood group and ischemic stroke, myocardial infarction, and peripheral vascular disease: A meta-analysis of over 145,000 cases and 2,000,000 controls
Bibliographic record
Abstract
OBJECTIVE: Cardiovascular illnesses have been associated to ABO blood types, specifically through an effect on von Willebrand factor and factor FVIII levels. We conducted a meta-analysis to comprehensively explore the relationship between blood groups and ischemic stroke, myocardial infarction, and peripheral vascular disease. MATERIALS AND METHODS: A comprehensive meta-analysis was undertaken to investigate blood groups and ischemic stroke (IS), myocardial infarction (MI) and peripheral vascular disease (PVD). Odds ratios (OR) were used to assess the relationship between blood groups and disease. RevMan v5,4 was used to statistically analyse the results. Risk of bias was assessed using the Newcastle-Ottawa scale. RESULTS: A total of 72 studies (18 ischemic stroke, 37 myocardial infarction, 17 peripheral vascular disease) met our search criteria, totalling 145,499 cases and 2,113,736 controls. Mean age ranged between 18 and 90 years. Compared to blood group-O, non-O blood group had an increased association with IS (OR=1.13, 95%Cl: 1.07-1.21, P < 0.001), MI (OR=1.17, 95%Cl: 1.11-1.24, P < 0.001) and PVD (OR=1.15, 95%Cl: 1.04-1.28, P=0.005). Compared to blood group-O, blood group A had a stronger statistically significant association to IS (OR=1.19, P=0.001), MI (OR=1.22, P < 0.001) and PVD (OR=1.15, P=0.03). Blood group-B has the lowest risk associated with MI (OR=1.09, P=0.01). In addition, blood groups AB had a stronger statistically significant association to IS (OR=1.24, P=0.01), and MI (OR=1.20, P < 0.001) compared with the other blood groups. CONCLUSIONS: Compared to blood group-O, groups A and AB are strongly associated to ischemic stroke, myocardial infarction, and peripheral vascular disease.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.042 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".