The Prevalence of Cardiovascular Risk Factors in Individuals with Hemophilia
Bibliographic record
Abstract
Abstract Abstract 4319 Background: Increasing life expectancy in individuals with hemophilia has lead to a higher prevalence of cardiovascular risk (CV) factors and disease in this aging population. Clinical guidelines recommend screening patients as early as age 35 for hypertension, dyslipidemia, diabetes, obesity and smoking and intervention to modify these risk factors. Antithrombotic agents (antiplatelet or anticoagulants) are beneficial in secondary prevention of CV events but no randomized controlled trials have studied these drugs in patients with hemophilia. The goal of this study was to identify the prevalence of CV risk factors and disease in patients with hemophilia over the age of 35, the use of antiplatelet agents and other drugs in the management of risk factors. Method: Retrospective chart review was conducted on all patients age 35 and older with Hemophilia A or B who attended the Southwestern Ontario Regional Hemophilia Program. This clinic services a population of approximately 1.5 million patients, following 139 patients with hemophilia A or B. Demographic information, severity of bleeding disorder, and CV risk factor and events were extracted from patient records as well therapeutic interventions and frequency of bleeding events. Result: A total of 46 out of 139 patients (33%), 37 with hemophilia A and 9 with hemophilia B, met inclusion criteria of age over 35. The majority of patients in this age group were classified as mild or moderate severity (40/46) based on factor levels (Factor VIII <0.01 = 4, Factor VIII >0.01–0.05 = 6, Factor VIII>0.06 = 27; Factor IX<0.01 = 2, Factor IX>0.01–0.05 = 6, Factor IX>0.06=1). Two patients had inhibitors, and 2 were on prophylaxis. Hypertension was identified in 22/46 (48%), dyslipidemia in 16/46 (35%), smoking in 16/46 (35%), and diabetes in 6/46 (13%). CV disease potentially requiring antithrombotic therapy for secondary prevention was identified in 5/46 patients (11%). Two had coronary artery disease, 1 had a transient ischemic attack, and 2 had atrial fibrillation. Of these patients, 2 patients underwent cardiovascular surgery for which they received factor replacement. One had an aortic valve replacement and coronary artery bypass graft. This patient did not receive any long-term antiplatelet treatment, but received heparin during surgery. The other patient underwent percutaneous coronary intervention with anticoagulation during the procedure, and received ASA and clopidogrel post-operatively, followed by ongoing ASA for 28 months. Of the remaining 3 patients with CV disease, 2 received ASA for 24 and 67 months. One patient received ASA after experiencing chest pain, but was discontinued after no underlying CV disease was found. No patients were given vitamin K antagonists. All 4 patients receiving antiplatelet agents were classified as mild (2) or moderate (2) hemophilia and no observed bleeding events were reported following the addition of these agents (median follow-up time 26 months, range 1–67 months). No factor prophylaxis was given while on long-term ASA. Conclusion: CV risk factors are prevalent in individuals with hemophilia and similar or higher to that reported in general population over age 35. Given the limited number of patients with CV disease in this study on antiplatelet agents, the safety of these drugs in patients with bleeding disorders cannot be determined. Although CV risk factors are prevalent in patients with hemophilia, the rarity, clinical heterogeneity and infrequent use of antithrombotic therapy suggest the need to develop a national or international registry to address the safety of these treatments for this population. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".