Links Between Strokes and Hereditary Hemorrhagic Telangiectasia: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Hereditary hemorrhagic telangiectasia (HHT) is a disease of abnormal vasculature where patients are predisposed to strokes of multiple etiologies. We assessed yearly stroke incidence among Albertans with HHT and compared with the general population. Given the tendency for stroke in HHT patients, we expected HHT patients to have higher stroke incidence, in particular at younger ages. METHODS: Population-based administrative health data on inpatient and ambulatory admissions were extracted over a 16-year period using International Classification of Diseases (ICD)-9 and ICD-10, Canada codes. We analyzed overall occurrence of strokes in Alberta by age, gender, stroke subtype, and diagnosis of HHT. RESULTS: The age-standardized incidence rate of stroke in HHT was 450 per 100,000 compared with 260 per 100,000 in the general population with a rate ratio of 1.73 (95% confidence interval (CI) [1.046-2.842]). This study found a higher HHT prevalence in Alberta (1 in 3800) compared to the world average of 1 in 5000. Women were also more likely to be diagnosed with HHT, with a 3.25:1 female gender preponderance in the yearly incidence.InterpretationThis study not only shows that HHT patients are at higher risk of having a stroke but also quantifies that risk using an age-adjusted metric in Alberta. This province has a higher than expected disease burden of HHT, with the majority of cases affecting women. Our study found that acute ischemic strokes and transient ischemic attacks are far more common than hemorrhage in HHT. As HHT is a rare, multi-system, chronic disease, these patients should be referred to an HHT Centre of Excellence.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".