Prediction of underlying atrial fibrillation in patients with a cryptogenic stroke: results from the NOR-FIB Study

Background - Atrial fibrillation (AF) detection and treatment are key elements to reduce recurrence risk in cryptogenic stroke (CS) with underlying arrhythmia. The purpose of the present study was to assess the predictors of AF in CS and the utility of existing AF-predicting scores in The Nordic Atrial Fibrillation and Stroke (NOR-FIB) Study. Method - The NOR-FIB study was an international prospective observational multicenter study designed to detect and quantify AF in CS and cryptogenic transient ischaemic attack (TIA) patients monitored by the insertable cardiac monitor (ICM), and to identify AF-predicting biomarkers. The utility of the following AF-predicting scores was tested: AS5F, Brown ESUS-AF, CHA2DS2-VASc, CHASE-LESS, HATCH, HAVOC, STAF and SURF. Results - In univariate analyses increasing age, hypertension, left ventricle hypertrophy, dyslipidaemia, antiarrhythmic drugs usage, valvular heart disease, and neuroimaging findings of stroke due to intracranial vessel occlusions and previous ischemic lesions were associated with a higher likelihood of detected AF. In multivariate analysis, age was the only independent predictor of AF. All the AF-predicting scores showed significantly higher score levels for AF than non-AF patients. The STAF and the SURF scores provided the highest sensitivity and negative predictive values, while the AS5F and SURF reached an area under the receiver operating curve (AUC) > 0.7. Conclusion - Clinical risk scores may guide a personalized evaluation approach in CS patients. Increasing awareness of the usage of available AF-predicting scores may optimize the arrhythmia detection pathway in stroke units

Biomarkers Predictive of Atrial Fibrillation in Patients with Cryptogenic Stroke. Insights from The Nordic Atrial Fibrillation and Stroke (NOR-FIB) Study

BACKGROUND: There are currently no biomarkers used to select cryptogenic stroke (CS) patients for monitoring with insertable cardiac monitors (ICMs), the most effective tool for diagnosing atrial fibrillation (AF) in CS. The purpose of this study was to assess clinically available biomarkers as predictors of AF.METHODS: Eligible CS and cryptogenic transient ischemic attack (TIA) patients underwent 12-month monitoring with ICMs, clinical follow-up, and biomarker sampling. Levels of cardiac and thromboembolic biomarkers, taken within 14 days from symptom onset, were compared between patients diagnosed with AF (n=74) during monitoring and those without AF (n=185). Receiver operating characteristic (ROC) curves were created. Biomarkers reaching area under ROC curve (AUC) ≥ 0.7 were dichotomized by finding optimal cut-off values and used in logistic regression establishing their predictive value for increased risk of AF in unadjusted and adjusted models.RESULTS: B-type natriuretic peptide (BNP), N-terminal pro-brain natriuretic peptide (NT-proBNP), creatine kinase, D-dimer, high-sensitivity cardiac Troponin I and T were significantly higher in the AF than non-AF group. BNP and NT-proBNP reached predefined AUC level, 0.755 and 0.725 respectively. Optimal cut-off values were 33.5 ng/L for BNP, and 87 ng/L for NT-proBNP. Regression analysis showed that NT-proBNP was a predictor of AF in both unadjusted, odds ratio (OR) 7.72 (95% confidence interval [CI] 3.16-18.87), and age and sex adjusted models, OR 4.82 (95% CI 1.79-12.96).CONCLUSION: Several clinically established biomarkers were associated with AF. NT-proBNP performed best as AF predictor and could be used for selecting patients for long-term monitoring with ICMs