Literature DB >> 32951957

Predicting spontaneous conversion to sinus rhythm in symptomatic atrial fibrillation: The ReSinus score.

Jan Niederdöckl1, Alexander Simon2, Filippo Cacioppo1, Nina Buchtele3, Anne Merrelaar1, Nikola Schütz1, Sebastian Schnaubelt1, Alexander O Spiel4, Dominik Roth1, Christian Schörgenhofer5, Harald Herkner6, Hans Domanovits1, Michael Schwameis1.   

Abstract

BACKGROUND: The optimal management of patients presenting to the Emergency Department with hemodynamically stable symptomatic atrial fibrillation remains unclear. We aimed to develop and validate an easy-to-use score to predict the individual probability of spontaneous conversion to sinus rhythm in these patients
METHODS: This retrospective cohort study analyzed 2426 cases of first-detected or recurrent hemodynamically stable non-permanent symptomatic atrial fibrillation documented between January 2011 and January 2019 in an Austrian academic Emergency Department atrial fibrillation registry. Multivariable analysis was used to develop and validate a prediction score for spontaneous conversion to sinus rhythm during Emergency Department visit. Clinical usefulness of the score was assessed using decision curve analysis
RESULTS: 1420 cases were included in the derivation cohort (68years, 57-76; 43% female), 1006 cases were included in the validation cohort (69years, 58-76; 47% female). Six variables independently predicted spontaneous conversion. These included: duration of atrial fibrillation symptoms (<24hours), lack of prior cardioversion history, heart rate at admission (>125bpm), potassium replacement at K+ level ≤3.9mmol/l, NT-proBNP (<1300pg/ml) and lactate dehydrogenase level (<200U/l). A risk score weight was assigned to each variable allowing classification into low (0-2), medium (3-5) and moderate (6-8) probability of spontaneous conversion. The final score showed good calibration (p=0.44 and 0.40) and discrimination in both cohorts (c-indices: 0.74 and 0.67) and clinical net benefit
CONCLUSION: The ReSinus score, which predicts spontaneous conversion to sinus rhythm, was developed and validated in a large cohort of patients with hemodynamically stable non-permanent symptomatic atrial fibrillation and showed good calibration, discrimination and usefulness REGISTRATION: NCT03272620.
Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  derivation; prediction score; spontaneous conversion; symptomatic atrial fibrillation; validation

Mesh:

Year:  2020        PMID: 32951957     DOI: 10.1016/j.ejim.2020.07.022

Source DB:  PubMed          Journal:  Eur J Intern Med        ISSN: 0953-6205            Impact factor:   4.487


  4 in total

1.  The ABC-Stroke Score Refines Stroke Risk Stratification in Patients With Atrial Fibrillation at the Emergency Department.

Authors:  Jan Niederdöckl; Julia Oppenauer; Sebastian Schnaubelt; Filippo Cacioppo; Nina Buchtele; Alexandra-Maria Warenits; Roberta Laggner; Nikola Schütz; Magdalena S Bögl; Gerhard Ruzicka; Sophie Gupta; Martin Lutnik; Safoura Sheikh Rezaei; Michael Wolzt; Harald Herkner; Hans Domanovits; Anton N Laggner; Michael Schwameis; Ziad Hijazi
Journal:  Front Med (Lausanne)       Date:  2022-06-27

2.  From Bench to Bedside-Implementing the New ABC Approach for Atrial Fibrillation in an Emergency Department Setting.

Authors:  Sophie Gupta; Martin Lutnik; Jan Niederdöckl; Sebastian Schnaubelt
Journal:  Int J Environ Res Public Health       Date:  2022-04-15       Impact factor: 4.614

3.  Prediction of Successful Pharmacological Cardioversion in Acute Symptomatic Atrial Fibrillation: The Successful Intravenous Cardioversion for Atrial Fibrillation (SIC-AF) Score.

Authors:  Jan Daniel Niederdöckl; Alexander Simon; Nina Buchtele; Nikola Schütz; Filippo Cacioppo; Julia Oppenauer; Sophie Gupta; Martin Lutnik; Sebastian Schnaubelt; Alexander Spiel; Dominik Roth; Fritz Wimbauer; Isabel Fegers-Wustrow; Katrin Esefeld; Martin Halle; Jürgen Scharhag; Thomas Laschitz; Harald Herkner; Hans Domanovits; Michael Schwameis
Journal:  J Pers Med       Date:  2022-03-30

Review 4.  Computational models of atrial fibrillation: achievements, challenges, and perspectives for improving clinical care.

Authors:  Jordi Heijman; Henry Sutanto; Harry J G M Crijns; Stanley Nattel; Natalia A Trayanova
Journal:  Cardiovasc Res       Date:  2021-06-16       Impact factor: 10.787

  4 in total

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