Risk factors, stroke rates and aspirin prescribing trends in the Canadian Fabry disease initiative cohort
Bibliographic record
Abstract
BACKGROUND: Fabry disease (FD) is an X-linked disorder caused by deleterious variants in GLA. Cardiovascular disease (CVD) causes premature mortality in FD. Hope for aspirin (acetylsalicylic acid, ASA) to reduce CVD risks in FD as primary prevention may have been tempered by the 2018 ARRIVE, ASCEND, and ASPREE clinical trials. It is unclear how new ASA guidance applies to FD patients, who have a high rate of young-onset, small vessel stroke compared with the general population. METHODS: Longitudinal data spanning 2007-2023 from patients in the Canadian Fabry Disease Initiative (CFDI) were analyzed retrospectively. Incident stroke and transient ischemic attack (TIA), other CVD events, FD-specific risk factors, and ASA/antiplatelet ("ASA/AP") prescription before and after 2018 were compared between groups who never had an event ("primary prevention group") to those who had incident stroke/TIA during the study. Stroke/TIA rates were compared within CFDI by sex and GLA variant severity, and in the CFDI compared to Canadian statistics by sex. Ten-year atherosclerotic CVD (ASCVD) risk was calculated using the 2013 ACC/AHA risk calculator. ASA/AP prescription rate was compared before and after 2018. RESULTS: Out of 641 patients, 57 had an incident stroke/TIA during the study, and 193 with complete data remained in the primary prevention group. Stroke/TIA rates were significantly higher among male patients (0.026 events per patient-year) than females (0.0098 events per patient-year), and higher among patients with severe GLA variants (males: 0.031 events per patient-year, females: 0.0096 events per patient-year) compared to those with attenuated variants (males: 0.011 events per patient-year, females: 0.0088 events per patient-year). No patients under 60 years at their incident stroke/TIA had high (≥ 10%) calculated 10-year ASCVD risk. Fewer patients were prescribed ASA/AP for primary prevention after 2018. CONCLUSIONS: There was a high incidence of stroke/TIA in the younger CFDI cohort compared to the general Canadian population, despite low levels of traditional vascular risk factors as represented in 10-year estimated ASCVD risk. Primary prevention use of ASA has declined.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".