Parental Atrial Fibrillation and Stroke or Atrial Fibrillation in Young Adults
Bibliographic record
Abstract
Background and Purpose- Cryptogenic strokes are often the first clinical manifestation of undiagnosed atrial fibrillation (AF). We designed this study to test whether parental AF is a risk factor for stroke in young adults. Methods- Population-based cohort study using linked administrative databases from April 1, 1972 to March 31, 2016 in Manitoba, Canada for 325 333 offspring (age ≥18 years) with at least 1 linked parent (total 582 195 parents). We examined the association between parental history of AF and stroke or transient ischemic attack (TIA) in the offspring using multivariable Cox proportional hazards models. Results- Offspring median age at study entry was 18 years. During 5.533 million person-years of follow-up (mean 17 years), 8678 offspring had an incident stroke or TIA (5.2% of the 24 583 offspring with a parental history of AF compared with 2.5% of the 300 750 offspring with no parental history of AF), and 1430 were diagnosed with AF (1.9% versus 0.3%). Incidence rates for stroke/TIA were higher in offspring with a parental history of AF (195.0 versus 156.6 per 100 000 person-years). Parental AF was associated with elevated risk in offspring of stroke/TIA (hazard ratio 1.11; 95% CI, 1.04-1.18) or AF (hazard ratio 1.75; 95% CI, 1.55-1.97) and a higher frequency of other cardiovascular risk factors. After adjusting for demographics, region of residence, socioeconomic status, and other stroke risk factors in offspring, parental AF was associated with AF in their offspring in young adulthood (adjusted hazard ratio 1.61; 95% CI, 1.43-1.82); the association of parental AF with offspring stroke/TIA was attenuated (adjusted hazard ratio 1.05; 95% CI, 0.99-1.12) after adjusting for the other cardiovascular risk factors. Conclusions- Parental AF is associated with increased risk of AF and other cardiovascular risk factors in their offspring during early adulthood, resulting in increased stroke risk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".