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Atrial cardiopathy biomarkers and atrial fibrillation in the ARCADIA trial
Hooman Kamel1, Mitchell Sv Elkind2,3, Richard A Kronmal4
1Clinical and Translational Neuroscience Unit, Department of Neurology and Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
Insights
Biomarkers for atrial cardiopathy moderately predicted atrial fibrillation (AF) in cryptogenic stroke patients. This finding offers insights into the ARCADIA trial
Area of Science:
- Cardiology
- Neurology
- Biomarker Research
Background:
- The ARCADIA trial investigated apixaban versus aspirin for secondary stroke prevention in patients with cryptogenic stroke and atrial cardiopathy.
- A neutral trial result may stem from suboptimal atrial cardiopathy identification using biomarkers.
- This study evaluates biomarker associations with subsequent atrial fibrillation (AF) detection, a key indicator of atrial cardiopathy.
Purpose of the Study:
- To assess the predictive value of established atrial cardiopathy biomarkers for subsequent AF detection in cryptogenic stroke patients.
- To examine the relationship between specific biomarker levels and the occurrence of AF.
- To inform future trial design and patient selection for secondary stroke prevention.
Main Methods:
- Patients meeting atrial cardiopathy criteria (P-wave terminal force in lead V1 [PTFV1], NT-proBNP, or left atrial diameter index [LADI]) were included.
- AF detection via routine care served as the primary outcome.
- Multivariable regression analyses assessed the association of biomarkers, demographics, and risk factors with AF detection.
Main Results:
- Of 3745 screened patients, 254 were diagnosed with AF. Biomarkers including NT-proBNP, PTFV1, and LADI were associated with AF in unadjusted analyses.
- In multivariable models, age, NT-proBNP, and LADI remained significantly associated with AF.
- The combined biomarker model demonstrated moderate predictive ability (c-statistic 0.82) but had modest calibration.
Conclusions:
- Biomarkers used to define atrial cardiopathy in the ARCADIA trial showed moderate predictive capability for subsequent AF detection.
- These findings suggest that while useful, current biomarkers may require refinement for optimal identification of patients at high risk for AF-related stroke.
- Further research is warranted to enhance the diagnostic accuracy of biomarkers for atrial cardiopathy.
Background:
ARCADIA compared apixaban to aspirin for secondary stroke prevention in patients with cryptogenic stroke and atrial cardiopathy. One possible explanation for the neutral result is that biomarkers used did not optimally identify atrial cardiopathy. We examined the relationship between biomarker levels and subsequent detection of AF, the hallmark of atrial cardiopathy.
Methods:
Patients were randomized if they met criteria for atrial cardiopathy, defined as P-wave terminal force >5000 μV*ms in ECG lead V1 (PTFV1), NT-proBNP >250 pg/mL, or left atrial diameter index (LADI) ⩾3 cm/m2. For this analysis, the outcome was AF detected per routine care.
Results:
Of 3745 patients who consented to screening for atrial cardiopathy, 254 were subsequently diagnosed with AF; 96 before they could be randomized and 158 after randomization. In unadjusted analyses, ln(NT-proBNP) (RR per SD, 1.99; 95% CI, 1.85-2.13), PTFV1 (RR per SD, 1.15; 95% CI, 1.03-1.28) and LADI (RR per SD, 1.34; 95% CI, 1.20-1.50) were associated with AF. In a model containing all 3 biomarkers, demographics, and AF risk factors, age (RR per 10 years, 1.24; 95% CI, 1.09-1.41), ln(NT-proBNP) (RR per SD, 1.88; 95% CI, 1.67-2.11) and LADI (RR per SD, 1.25; 95% CI, 1.14-1.37) were associated with AF. These three variables together had a c-statistic of 0.82 (95% CI, 0.79-0.85) but only modest calibration. Discrimination was attenuated in sensitivity analyses of patients eligible for randomization who may have been more closely followed for AF.
Conclusions:
Biomarkers used to identify atrial cardiopathy in ARCADIA were moderately predictive of subsequent AF.
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