RESUMEN
Cardiac rhythm monitoring is performed to search for atrial fibrillation (AF) after ischaemic stroke or transient ischaemic attack (TIA). Prolonged cardiac rhythm monitoring increases AF detection but is challenging to implement in many healthcare settings and is not needed for all people after ischaemic stroke/TIA. We aimed to develop and validate a model that includes clinical, electrocardiogram (ECG), blood-based, and genetic biomarkers to identify people with a low probability of AF detection after ischaemic stroke or TIA. We will recruit 675 consenting participants who are aged over 18 years, who were admitted with ischaemic stroke or TIA in the 5 days prior, who are not known to have AF, and who would be suitable for anticoagulation if AF is found. We will collect baseline demographic and clinical data, a 12-lead ECG, and a venous blood sample for blood biomarkers (including midregional pro-atrial natriuretic peptide, MRproANP) and genetic data. We will perform up to 28 days of cardiac rhythm monitoring using an R-test or patch device to search for AF in all participants. The sample size of 675 participants is based on true sensitivity of 92.5%, null hypothesis sensitivity of 80%, 80% power, and 5% significance. The primary outcome is AF detection ≥30 s duration during 28 days of cardiac rhythm monitoring. Secondary outcomes are AF detection at 1-year, recurrent cardiovascular events, and mortality and will be identified by electronic linkage and telephone follow-up. The results will guide the development of a more personalized care pathway to search for AF after ischaemic stroke or TIA. This could help to reduce cardiac rhythm monitoring for people with a low probability of AF detection and allow more intensive cardiac monitoring to be focused on people who are more likely to have AF and benefit. Participants will be consented for their data to be used in future research studies, providing a rich resource for stroke and cardiovascular research communities.
Asunto(s)
Fibrilación Atrial , Isquemia Encefálica , Accidente Cerebrovascular Embólico , Ataque Isquémico Transitorio , Accidente Cerebrovascular Isquémico , Accidente Cerebrovascular , Humanos , Adulto , Persona de Mediana Edad , Accidente Cerebrovascular/diagnóstico , Ataque Isquémico Transitorio/diagnóstico , Isquemia Encefálica/diagnóstico , Fibrilación Atrial/diagnóstico , Accidente Cerebrovascular Isquémico/complicacionesRESUMEN
BACKGROUND AND OBJECTIVES: Prolonged cardiac monitoring (PCM) increases atrial fibrillation (AF) detection after ischemic stroke, but access is limited, and it is burdensome for patients. Our objective was to assess whether midregional proatrial natriuretic peptide (MR-proANP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) could classify people who are unlikely to have AF after ischemic stroke and allow better targeting of PCM. METHODS: We analyzed people from the Biomarker Signature of Stroke Aetiology (BIOSIGNAL) study with ischemic stroke, no known AF, and ≥3 days cardiac monitoring. External validation was performed in the Preventing Recurrent Cardioembolic Stroke: Right Approach, Right Patient (PRECISE) study of 28 days of cardiac monitoring in people with ischemic stroke or transient ischemic attack and no known AF. The main outcome is no AF detection. We assessed the discriminatory value of MR-proANP and NT-proBNP combined with clinical variables to identify people with no AF. A decision curve analysis was performed with combined data to determine the net reduction in people who would undergo PCM using the models based on a 15% threshold probability for AF detection. RESULTS: We included 621 people from the BIOSIGNAL study. The clinical multivariable prediction model included age, NIH Stroke Scale score, lipid-lowering therapy, creatinine, and smoking status. The area under the receiver-operating characteristic curve (AUROC) for clinical variables was 0.68 (95% CI 0.62-0.74), which improved with the addition of log10MR-proANP (0.72, 0.66-0.78; p = 0.001) or log10NT-proBNP (0.71, 0.65-0.77; p = 0.009). Performance was similar for the models with log10MR-proANP vs log10NT-proBNP (p = 0.28). In 239 people from the PRECISE study, the AUROC for clinical variables was 0.68 (0.59-0.76), which improved with the addition of log10NT-proBNP (0.73, 0.65-0.82; p < 0.001) or log10MR-proANP (0.79, 0.72-0.86; p < 0.001). Performance was better for the model with log10MR-proANP vs log10NT-proBNP (p = 0.03). The models could reduce the number of people who would undergo PCM by 30% (clinical and log10MR-proANP), 27% (clinical and log10NT-proBNP), or 20% (clinical only). DISCUSSION: MR-proANP and NT-proBNP help classify people who are unlikely to have AF after ischemic stroke. Measuring MR-proANP or NT-proBNP could reduce the number of people who need PCM by 30%, without reducing the amount of AF detected. TRIAL REGISTRATION INFORMATION: NCT02274727; clinicaltrials.gov/study/NCT02274727.