In:
Stroke, Ovid Technologies (Wolters Kluwer Health), Vol. 50, No. Suppl_1 ( 2019-02)
Abstract:
Background: Detecting concealed paroxysmal atrial fibrillation (pAF) is a major focus of the workup of ischemic-stroke-patients, but requires elaborate ECG-monitoring. We aimed to evaluate pre-specified predictors to determine stroke patients with an increased probability of underlying pAF. We applied cut-off-levels recently suggested by the German Stroke Society 1 . Methods: The Find-AF RANDOMISED -trial (NCT01855035) evaluated 3x10-day Holter-ECG vs. standard-care in 398 patients 〉 60 years with acute ischemic strokes. The primary endpoint was novel pAF after 6 months. 27 patients in the intervention arm (13.5 %) and 9 patients in the control arm (9.0 %) met the primary endpoint (p=0.002). We used Pearson’s Chi 2 -test and the Mann-Whitney-U-test, as applicable. In variables with p 〈 0.05 we calculated the number-needed-to-screen (NNS). We also performed ROC-analyses to determine the areas-under-the-curve (AUC). Results: Table 1 shows known pAF-risk-factors in relation to whether patients had pAF. The absence of a clinical lacunar syndrome (p=0.007) or lacunar lesions (p=0.018), increased NIHSS-Score (p=0.003), frequent atrial premature beats (APB, p=0.003), prolonged supraventricular runs (p=0.01), enlarged left atria (p=0.07) and increased brain-natriuretic-peptide-levels (p=0.001) were associated with underlying pAF. Frequent APB differentiated best between those with and without pAF (area under the curve, AUC: 0.71). Conclusions: Several of the evaluated markers are useful to preselect stroke patients for enhanced ECG-monitoring. APB and comprehensive measures of both left atrial size and function (LAVI/a’) showed the highest AUC and should be used when preselecting stroke patients for prolonged ECG-monitoring.
Type of Medium:
Online Resource
ISSN:
0039-2499
,
1524-4628
DOI:
10.1161/str.50.suppl_1.124
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2019
detail.hit.zdb_id:
1467823-8
