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Contemporary Yield of 24-hour Holter Monitoring: Role of Inter-Atrial Block Recognition


Background: The diagnostic yield of 24-hour ECG Holter monitoring (24H) is currently overcome by alternative ECG monitoring techniques and it needs to be optimized. The recognition of inter-atrial block (IAB) has emerged as a reliable indicator of patients at risk of atrial fibrillation relapses, and its role enhancing the yield of 24H is yet to be determined. We hypothesized that a presumably low yield of 24H may be ameliorated by means of incorporating the assessment for IAB and . Methods: We retrospectively analyzed 1017 consecutive 24H registers performed in a Multidisciplinary Integrated Health Care Institution, in which a restrictive definition of diagnostic 24H findings was used. A univariate and multivariate regression analysis served to determine the variables associated with a higher 24H’s yield, including the requesting medical specialty, type of indication and a number of clinical, echocardiographic and ECG variables, including IAB. Results: The mean age of our population was 62 ± 17 years (55% males). The majority of 24H were indicated from the Cardiology department (48%). The overall yield was 12.8%, higher for the assessment of the integrity of the electrical conduction system (26.1%) and poorer for the assessment of syncope (3.2%) and cryptogenic stroke (4.6%). The variables associated with higher diagnostic performance were indication from Cardiology (p < 0.001), IAB (p = 0.004), structural heart disease (p = 0.008) and chronic renal failure (p = 0.009). Patients ≤ 50 years old only retrieved a 7% yield. In the multivariate analysis, indication from Cardiology and IAB remained significant predictors of higher 24H’s yield. In a secondary analysis including echocardiographic data, only identification of IAB remained statistically significant. Conclusions: The recognition of IAB and the type of indication are major determinants of a higher 24H’s diagnostic yield and may help to optimize the selection of candidates.

Credits: Victor Bazan , German Cediel, Cinta Llibre , Axel Sarrias, Isabel Romeo , Snia Ibars , Francisco Escudero , Sandra Valdivielso , Felipe Bisbal , Roger Villuendas, Antoni Bayes-Genis, Ferran Padilla.


Biosense Webster
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Introduction to AFib
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