Predictors of Atrial Fibrillation Development in Patients With Embolic Stroke of Undetermined Source: An Analysis of the RE-SPECT ESUS Trial
Bibliographic record
Abstract
Background: A proportion of patients with embolic stroke of undetermined source have silent atrial fibrillation (AF) or develop AF after the initial evaluation. Better understanding of the risk for development of AF is critical to implement optimal monitoring strategies with the goal of preventing recurrent stroke attributable to underlying AF. The RE-SPECT ESUS trial (Randomized, Double-Blind Evaluation in Secondary Stroke Prevention Comparing the Efficacy and Safety of the Oral Thrombin Inhibitor Dabigatran Etexilate Versus Acetylsalicylic Acid in Patients With Embolic Stroke of Undetermined Source) provides an opportunity to assess predictors for developing AF and associated recurrent stroke. Methods: RE-SPECT ESUS was a randomized, controlled trial (564 sites, 42 countries) assessing dabigatran versus aspirin for the prevention of recurrent stroke in patients with embolic stroke of undetermined source. Of 5390 patients enrolled and followed for a median of 19 months, 403 (7.5%) were found to develop AF reported as an adverse event or using cardiac monitoring per standard clinical care. Univariable and multivariable regression analyses were performed to define predictors of AF. Results: In the multivariable model, older age (odds ratio for 10-year increase, 1.99 [95% CI, 1.78–2.23]; P <0.001), hypertension (odds ratio, 1.36 [95% CI, 1.03–1.79]; P =0.0304), diabetes (odds ratio, 0.74 [95% CI, 0.56–0.96]; P =0.022), and body mass index (odds ratio for 5-U increase, 1.29 [95% CI, 1.16–1.43]; P <0.001) were independent predictors of AF during the study. In a sensitivity analysis restricted to 1117 patients with baseline NT-proBNP (N-terminal prohormone of brain natriuretic peptide) measurements, only older age and higher NT-proBNP were significant independent predictors of AF. Performance of several published predictive models was assessed, including HAVOC (AF risk score based on hypertension, age ≥75 years, valvular heart disease, peripheral vascular disease, obesity, congestive heart failure, and coronary artery disease) and CHA 2 DS 2 -VASc (stroke risk score based on congestive heart failure, hypertension, age ≥75 years [doubled], diabetes, previous stroke, transient ischemic attack or thromboembolism [doubled], vascular disease, age 65 to 74 years, and sex category [female]) scores, and higher scores were associated with higher rates of developing AF. Conclusions: Besides age, the most important variable, several other factors, including hypertension, higher body mass index, and lack of diabetes, are independent predictors of AF after embolic stroke of undetermined source. When baseline NT-proBNP was available, only older age and elevation of this biomarker were predictive of subsequent AF. Understanding who is at higher risk of developing AF will assist in identifying patients who may benefit from more intense, long-term cardiac monitoring. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02239120.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".