Pulmonary Embolism and ABO Blood Type: A Systematic Review
Bibliographic record
Abstract
Background: Pulmonary embolism (PE) remains a major cause of cardiovascular morbidity and mortality. Classical risk factors explain only part of the interindividual variability in thrombotic risk. Non-O blood groups are associated with higher plasma levels of von Willebrand factor and factor VIII, suggesting a potential prothrombotic mechanism. This systematic review and limited meta-analysis examined the relationship between ABO blood group and PE risk. Methods: Following PRISMA 2020 guidelines, PubMed, Embase, and Web of Science were searched through August 2025 for observational studies reporting ABO blood group and objectively confirmed PE in adults. Eligible designs included cohort, case–control, and registry-based studies. Two reviewers independently extracted data and assessed risk of bias using the Newcastle–Ottawa Scale. Comparable effect estimates were pooled using a random-effects model (DerSimonian–Laird method, inverse-variance weighting). Results: Four studies met inclusion criteria, comprising more than 300,000 participants from North America, Europe, and Asia. All reported a higher incidence of PE among non-O compared with O blood groups. Pooled analysis of two large population-based cohorts yielded a summary relative risk of 1.36 (95% CI 1.20–1.54; I2 = 2.6%), indicating a modest but consistent association. Data on recurrence, severity, and mortality were limited and heterogeneous. Conclusions: Non-O blood groups are associated with an approximately 30–40% higher risk of PE across diverse populations. While evidence is insufficient for causal inference, ABO phenotype represents a biologically plausible and readily available marker that may complement multifactorial models of thromboembolic risk.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".