Abstract T MP46: Stroke Occurrence in Hereditary Hemorrhagic Telangiectasia
Bibliographic record
Abstract
Purpose: Stroke is an important manifestation of Hereditary Hemorrhagic Telangiectasia (HHT). Many individuals may be unaware they have HHT, even after a stroke, due to its rarity. Our goal was to assess the occurrence of stroke among patients with HHT compared to the general population. Methods: Population-based administrative health data on inpatient and ambulatory admissions were extracted for the period 1997 to 2012 in Alberta using ICD-9 and ICD-10 codes. We observed overall occurrence of strokes in the HHT population and subsequently analyzed the data by gender, specific age groups, and stroke subtypes. Then we compared our findings to stroke occurrence among the general population. Results: The age-standardized occurrence rate of stroke in HHT was about 450 [95% CI 276.4, 622.6] per 100,000 PY compared to 260 [95% CI 259.3, 262.1] per 100,000 PY in the general population. Less than 3% of strokes occurred under 30 years old in both groups. Although the majority of strokes occurred after 60 years of age, 23% of strokes in the general population occurred in the middle-aged group (31-60). The prevalence of HHT in Alberta is 1 in 3,800 and three times as many women were diagnosed with HHT than men by 2012. Conclusion: The prevalence of HHT in Alberta was considerably higher than the North American estimate (1 in 5,000). Individuals diagnosed with HHT were 1.73 times more likely to have a stroke than average, a statistically significant difference. Among the general population, a substantial number of strokes occurred in the middle-aged group. There is a higher probability of an underlying genetic component in strokes occurring before 60 years. For patients who have a stroke before 60 without a clear etiology, clinicians should consider evaluation for genetic disorders such as HHT. This is particularly true for males in whom there may be underdiagnosis of HHT.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".