Abstract P009: Risk of Mortality According to Burden of Atrial Fibrillation: Results From a 60-year Cohort Study
Bibliographic record
Abstract
Introduction: Atrial Fibrillation (AF) is the most common serious cardiac arrhythmia and is associated with an increased risk of stroke and mortality. These risks can be modified with oral anticoagulation therapy. Clinically, the arrhythmia can be permanent or intermittent. Prior studies that have used time-constant, categorical covariates to examine the relationship between the pattern of AF and the occurrence of adverse events have produced conflicting results. We hypothesized that the amount of time that patients spend in AF, hereinafter termed arrhythmia “burden”, may be important in predicting adverse events. Objective: To examine the effects of the burden of AF on all-cause mortality. Methods: The Manitoba Follow-Up Study is a longitudinal, prospective study of 3983 originally healthy young men (mean age at entry 30 years) who have been followed with routine medical and electrocardiographic examinations since 1948. After 60 years of follow-up to July 1, 2008, AF had been documented on the electrocardiograms of 581 men (15% of the cohort) and 3182 (80%) of the original cohort had died. We created a Cox proportional hazards model with time-dependent covariates to estimate relative risks for mortality according to AF burden. AF status during each follow-up visit was classified as persistent when the patient was in AF on consecutive examinations, transient when the patient reverted to sinus rhythm after being in AF and incident when the patient developed AF after a period in sinus rhythm. Results: Results of the Cox proportional hazards regression model are displayed in the Table. Age, persistent AF and incident AF were all significant variables in the model. Holding all the other variables constant, persistent AF increased the risk of death by two times and incident AF increased the risk of death by 87%. Conclusions: Persistent AF and incident AF are associated with increased all-cause mortality. Estimating AF burden may have implications for risk stratification in patients with AF.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".