A comprehensive model to estimate underlying atrial fibrillation in cryptogenic stroke: the decrypting score. (14th October 2021)

• Record Type: Journal Article
• Authors: Cecconi, A; Vera, A; Ximenez-Carrillo, A; Ramos, C; Martinez-Vives, P; Lopez Melgar, C; Roquero Gimenez, P; Martinez-Avial Silva, M; Sanz-Garcia, A; Ortega, G; Aguirre, C; Vivancos, J; Alfonso, F; Jimenez-Borreguero, L.J
• Is Part Of: European heart journal. Volume 42(2021)Supplement 1
• Publication Date: 2021-10-14
• Subjects: Tissue Doppler, Speckle Tracking and Strain Imaging; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.12005
• DOI: 10.1093/eurheartj/ehab724.009
• Languages: English
• ISSNs: 0195-668X

Abstract

Abstract: Introduction: Cryptogenic stroke (CS) represents up to 30% of ischemic strokes. Since atrial fibrillation (AF) can be detected in up to one-third of CS, there is a clinical need for estimating the probability of underlying AF in CS to guide the optimal secondary prevention strategy. Surrogate markers of left atrial dysfunction such as left atrial size, left atrial strain (LAS) and NTproBNP has been described as predictors of AF in patients with CS. However the evidence about AF markers in comprehensive and prospective studies in CS is still limited. Purpose: The present study was designed to develop the first score to predict underlying AF in CS patients that includes markers of atrial dysfunction. To reach our aim we developed a comprehensive analysis including clinical, laboratory, electrocardiografic and advanced echocardiographic variables in patients with CS. Methods: Sixty-three consecutive patients with ischemic stroke or transient ischemic attack with ABCD2 scale ≥4 of unknown etiology were prospectively recruited. Clinical, laboratory, electrocardiografic and echocardiographic variables were collected. All patients underwent 15 days wearable Holter monitoring. Main objective was the Decryptoring score creation to predict AF in CS. Score variables were initially selected by a univariate logistic regression and, thereafter, the score points were derived according to a multivariant analysis. Results: AF was detected in 15 patients (24%). Patients in the AF group were older (81.4±6.9 vs 76.5±7.8 years; p=0.035. There was no difference in sex between groups. Regarding cardiovascular risk factors patients who developed AF had more often hypertension (87% vs 52%; p=0.018) without differences in diabetes, dyslipidemia and tobacco consumption. T troponin and NTproBNP were higher in the AF group (47±55.9 vs 16.8±12.4 ng/L; p=0.018 and 1379±1650 vs 317±496 ng/ml; p=0.001 respectively). There were no differences in ECG parameters such as p wave voltage, interatrial block, PR interval or QRS. LAS reservoir, LAS conduct and LAS contraction were lower in patients with AF (18.6±4.6 vs 32.1±10.9%; 8±4.3 vs 15.6±8%; 10.5±3.4 vs 16.6±7 respectively, all p<0.001). 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. Conclusion: The proposed score offers an accurate AF prediction in patients with CS providing a new clinical tool to orient the optimal treatment in these patients. Funding Acknowledgement: Type of funding sources: Other. Main funding source(s): Spanish Society of Cardiology