Prevalence of selected bleeding and thrombotic events in persons with hemophilia versus the general population: A scoping review
Bibliographic record
Abstract
Life expectancy for persons with hemophilia has increased over recent decades due to advances in treatment practice and patient care. Those with hemophilia are now more likely to be affected by conditions associated with aging, such as myocardial infarction, hemorrhagic/ischemic stroke, deep vein thrombosis, pulmonary embolism, and intracranial hemorrhage. Here, we describe the results of a literature search designed to summarize current data on the prevalence of the above selected bleeding and thrombotic events in persons with hemophilia vs the general population. A total of 912 articles published between 2005 and 2022 were identified in a search of BIOSIS Previews, Embase, and MEDLINE databases conducted in July 2022. Case studies, conference abstracts, review articles, studies focusing on hemophilia treatments or surgical outcomes, and studies examining patients with inhibitors only were excluded. After screening, 83 relevant publications were identified. The prevalence of bleeding events was consistently higher in hemophilia populations vs reference populations (hemorrhagic stroke, 1.4%-5.31% vs 0.2%-0.97%; intracranial hemorrhage, 1.1%-10.8% vs 0.04%-0.4%). Serious bleeding events showed a high rate of mortality with standardized mortality ratios for intracranial hemorrhage ranging from 3.5 to 14.88. Although 9 studies reported lower prevalence of arterial thrombosis (myocardial infarction/stroke) in hemophilia vs general populations, 5 studies reported higher or comparable prevalence in hemophilia. Prospective studies are therefore needed to understand the prevalence of bleeding and thrombotic events in hemophilia populations, particularly with the observed increases in life expectancy and availability of novel treatments.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.027 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".