Incidence of Atrial Fibrillation in Persons with Very High Serum Levels of N-Terminal Pro-B-Type Natriuretic Peptide: The Multi-Ethnic Study of Atherosclerosis
Bibliographic record
Abstract
OBJECTIVE: While persons in the upper fourth or fifth of the distribution of serum levels of N-terminal pro-B type natriuretic peptide (NT-proBNP) are at a sharply increased risk of developing atrial fibrillation, their absolute risk of this condition (about 20 per 1000 per year) is not clearly high enough to justify prevention or early detection measures. We sought to determine whether the incidence of atrial fibrillation among persons with VERY high levels of NT-proBNP might be sufficiently high to warrant further action. DESIGN AND SETTING: Among persons enrolled in the Multi-Ethnic Study of Atherosclerosis, we documented rates of new onset atrial fibrillation in those with increasingly high serum levels of NT-proBNP. RESULTS: There was a monotonic increase in the incidence of atrial fibrillation with increasing serum level of NT-proBNP, reaching rates of about 50-70 cases per 1000 person-years among those in the upper 3.1% of the distribution (above 422 pg/mL). In this group the incidence tended to be somewhat higher still among persons who were at increased risk of atrial fibrillation for other reasons (eg older age), but in no subgroup did the incidence reach 100 per 1000 person-years. CONCLUSION: Serum levels of NT-proBNP have a considerable ability to predict the development of atrial fibrillation. However, the value of screening middle aged and older adults for these levels hinges largely on the ability of interventions in screen-positive people to lead to a reduced incidence of atrial fibrillation and its complications.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".