A Comprehensive Model to Predict Atrial Fibrillation in Cryptogenic Stroke: The Decryptoring Score



      Cryptogenic stroke (CS) represents up to 30% of ischemic strokes (IS). Since atrial fibrillation (AF) can be detected in up to 30% of CS, there is a clinical need for estimating the probability of underlying AF in CS to guide the optimal secondary prevention strategy. The aim of the study was to develop the first comprehensive predictive score including clinical conditions, biomarkers, and left atrial strain (LAS), to predict AF detection in this setting.


      Sixty-three consecutive patients with IS or transient ischemic attack with ABCD2 scale ≥ 4 of unknown etiology were prospectively recruited. Clinical, laboratory, and echocardiographic variables were collected. All patients underwent 15 days wearable Holter-ECG monitoring. Main objective was the Decryptoring score creation to predict AF in CS. Score variables were selected by a univariate analysis and, thereafter, score points were derived according to a multivariant analysis.


      AF was detected in 15 patients (24%). Age > 75 (9 points), hypertension (1 point), Troponin T > 40 ng/L (8.5 points), NTproBNP > 200 pg/ml (0.5 points), LAS reservoir < 25.3% (24.5 points) and LAS conduct < 10.4% (0.5 points) were included in the score. The rate of AF detection was 0% among patients with a score of < 10 and 80% among patients with a score > 35. The comparison of the predictive validity between the proposed score and AF-ESUS score resulted in an AUC of 0.94 for Decryptoring score and of 0.65 for the AF-ESUS score(p < 0.001).


      This novel score offers an accurate AF prediction in patients with CS; however these results will require validation in an independent cohort using this model before they may be translated into clinical practice

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        • Adams H.P.
        • Bendixen B.H.
        • Kappelle L.J.
        • et al.
        Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in acute stroke treatment.
        Stroke. 1993; 24: 35-41
        • Ay H.
        • Furie K.L.
        • Singhal A.
        • Smith W.S.
        • Sorensen A.G.
        • Koroshetz WJ.
        An evidence-based causative classification system for acute ischemic stroke.
        Ann Neurol. 2005; 58: 688-697
        • Arboix A.
        • Alvarez-Sabín J.
        • Soler L.
        Stroke. Classification and diagnostic criteria. Ad hoc editorial committee of the task force on cerebrovascular diseases of SEN.
        Neurologia. 1998; 13 (Spanish. PMID: 9889525): 3-10
        • Ustrell-Roig X.
        • Serena-Leal J.
        Stroke. Diagnosis and therapeutic management of cerebrovascular disease.
        Rev Esp Cardiol. 2007; 60: 753-769
        • Sanna T.
        • Diener H.C.
        • Passman R.S.
        • et al.
        Cryptogenic stroke and underlying atrial fibrillation.
        N Engl J Med. 2014; 370: 2478-2486
        • Jordan K.
        • Yaghi S.
        • Poppas A.
        • et al.
        Left atrial volume index is associated with cardioembolic stroke and atrial fibrillation detection after embolic stroke of unde-termined source.
        Stroke. 2019; 50: 1997-2001
        • Pagola J.
        • González-Alujas T.
        • Flores A.
        • et al.
        Left atrial strain is a surrogate marker for detection of atrial fibrillation in cryptogenic strokes.
        Stroke. 2014; : 164-166
        • Rodriguez-Yanez M.
        • Arias-Rivas S.
        • Santamaria-Cadavid M.
        • Sobrino T.
        • Castillo J.
        • Blanco M.
        High pro-BNP levels predict the occurrence of atrial fibrillation after cryptogenic stroke.
        Neurology. 2013; 81: 444-447
        • Ntaios G.
        • Perlepe K.
        • Lambrou D.
        • et al.
        Identification of patients with embolic stroke of undetermined source and low risk of new incident atrial fibrillation: the AF-ESUS score.
        Int J Stroke. 2020; : 29-38
        • Johnston S.C.
        • Rothwell P.M.
        • Nguyen-Huynh M.N.
        • et al.
        Validation and refinement of scores to predict very early stroke risk after transient ischaemic attack.
        Lancet. 2007; 369: 283-292
        • Ringelstein E.B.
        • Chamorro A.
        • Kaste M.
        • et al.
        ESO stroke unit certification committee. European stroke organisation recommendations to establish a stroke unit and stroke center.
        Stroke. 2013; 44: 828-840
        • Lang R.M.
        • Badano L.
        • Mor-Avi V.
        • et al.
        Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American society of echocardiography and the European association of cardiovascular imaging.
        J Am Soc Echocardiogr. 2015; 28: 1-39
        • Badano L.
        • Kolias T.
        • Muraru D.
        Standardization of left atrial, right ventricular and right atrial deformation imaging using two-dimensional speckle tracking echocardiography: a consensus document of the EACVI/ASE/Industry task force to standardize deformation imaging.
        Eur Heart J Cardiovasc Imaging. 2018; 19: 591-600
        • Hindricks G.
        • Potpara T.
        • Dagres N.
        ESC guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European association for cardio-thoracic surgery (EACTS): the task force for the diagnosis and management of atrial fibrillation of the European society of cardiology (ESC) developed with the special contribution of the European heart rhythm association (EHRA) of the ESC.
        Eur Heart J. 2020; 42: 373-498
        • Pagola J.
        • Juega J.
        • Francisco-Pascual J.
        • et al.
        Predicting atrial fibrillation with high risk of embolization with atrial strain and NT-proBNP.
        Transl Stroke Res. 2020; : 735-741
        • Scheitz J.F.
        • Erdur H.
        • Haeusler K.G.
        • et al.
        Insular cortex lesions, cardiac troponin, and detection of previously unknown atrial fibrillation in acute ischemic stroke: insights from the troponin elevation in acute ischemic stroke study.
        Stroke. 2015; 46: 1196-1201
        • Scheitz J.F.
        • Pare G.
        • Pearce L.A.
        • et al.
        High-sensitivity cardiac troponin T for risk stratification in patients with embolic stroke of undetermined source.
        Stroke. 2020; 51: 2386-2394
        • Castilla-Guerra L.
        • Fernández-Moreno M.D.C.
        • De La Vega-Sánchez J.M.
        • Leon Jimenez D.
        Bleeding risk assessment for stroke patients on antithrombotic therapy.
        Clin Investig Arterioscler. 2019; 31: 282-288
        • Nakou E.S.
        • Parthenakis F.I.
        • Kallergis E.M.
        • Marketou M.E.
        • Nakos K.S.
        • Vardas P.E.
        Healthy aging and myocardium: a complicated process with various effects in cardiac structure and physiology.
        Int J Cardiol. 2016; 209: 167-175
        • De Weerd M.
        • Greving J.P.
        • De Jong A.
        • Buskens E.
        • Bots M.
        Prevalence of asymptomatic carotid artery stenosis according to age and sex: systematic review and meta regression analysis.
        Stroke. 2009; (PMID: 19246704 Review): 2366-2371