Biomarkers predictive of atrial fibrillation in patients with cryptogenic stroke. Insights from the Nordic Atrial Fibrillation and Stroke (NOR-FIB) study.
atrial fibrillation
biomarkers
cardiac rhythm monitoring
cryptogenic stroke
insertable cardiac monitors
Journal
European journal of neurology
ISSN: 1468-1331
Titre abrégé: Eur J Neurol
Pays: England
ID NLM: 9506311
Informations de publication
Date de publication:
05 2023
05 2023
Historique:
revised:
31
01
2023
received:
10
11
2022
accepted:
09
02
2023
medline:
6
4
2023
pubmed:
15
2
2023
entrez:
14
2
2023
Statut:
ppublish
Résumé
There are currently no biomarkers 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. Eligible CS and cryptogenic transient ischaemic attack 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 curves were created. Biomarkers reaching area under the receiver operating characteristic curve ≥ 0.7 were dichotomized by finding optimal cut-off values and were used in logistic regression establishing their predictive value for increased risk of AF in unadjusted and adjusted models. B-type natriuretic peptide (BNP), N-terminal pro-brain natriuretic peptide (NT-proBNP), creatine kinase, D-dimer and high-sensitivity cardiac troponin I and T were significantly higher in the AF than non-AF group. BNP and NT-proBNP reached the predefined area under the curve 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 7.72, 95% confidence interval 3.16-18.87) and age- and sex-adjusted models (odds ratio 4.82, 95% confidence interval 1.79-12.96). 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.
Sections du résumé
BACKGROUND AND PURPOSE
There are currently no biomarkers 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 ischaemic attack 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 curves were created. Biomarkers reaching area under the receiver operating characteristic curve ≥ 0.7 were dichotomized by finding optimal cut-off values and were 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 and high-sensitivity cardiac troponin I and T were significantly higher in the AF than non-AF group. BNP and NT-proBNP reached the predefined area under the curve 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 7.72, 95% confidence interval 3.16-18.87) and age- and sex-adjusted models (odds ratio 4.82, 95% confidence interval 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.
Substances chimiques
Biomarkers
0
Natriuretic Peptide, Brain
114471-18-0
Peptide Fragments
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1352-1363Informations de copyright
© 2023 European Academy of Neurology.
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