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Brain & Heart Post-stroke atrial fibrillation and predictive scores

and NIHSS scoring. A diagnostic work-up that adopts a 3. Diener HC, Sacco RL, Easton JD, et al., 2019, Dabigatran for
stepwise approach involving increasing durations of ECG prevention of stroke after embolic stroke of undetermined
monitoring and relies on risk prioritization estimated by source. N Engl J Med, 380: 1906–1917.
clinical predictive scores (e.g., starting with external ECG https://doi.org/10.1056/nejmoa1813959
monitoring and progressing to implantable monitoring 4. Diener HC, Hankey GJ, Easton JD, et al., 2020, Non-
devices for selected patients) may find practical application vitamin K oral anticoagulants for secondary stroke
in real-world clinical practice. Consequently, clinical prevention in patients with atrial fibrillation. Eur Heart J
predictive scores could play a pivotal role in defining Suppl, 22: I13–I21.
the risk of SAF and ECG monitoring priority. Recently,
a position paper by the European Society of Cardiology https://doi.org/10.1093/eurheartj/suaa104
has suggested the use of HAVOC or Brown ESUS-AF as 5. Schnabel RB, Haeusler KG, Healey JS, et al., 2019, Searching
clinical predictive scores for SAF detection . However, for atrial fibrillation poststroke: A white paper of the
[27]
this recommendation lacks the support of a randomized AF-SCREEN international collaboration. Circulation,
clinical trial aimed at validation. Therefore, large, 140: 1834–1850.
prospective, and multicentric trials are warranted. https://doi.org/10.1161/circulationaha.119.040267

Acknowledgments 6. Rubiera M, Aires A, Antonenko K, et al., 2022, European
Stroke Organisation (ESO) guideline on screening for
None. subclinical atrial fibrillation after stroke or transient
ischaemic attack of undetermined origin. Eur Stroke J, 7: VI.
Funding https://doi.org/10.1177/23969873221099478
None. 7. Bugnicourt JM, Flament M, Guillaumont MP, et al., 2013,

Conflict of interest Predictors of newly diagnosed atrial fibrillation in cryptogenic
stroke: A cohort study. Eur J Neurol, 20: 1352–1359.
The authors declare they have no competing interest. https://doi.org/10.1111/ene.12017

Author contributions 8. Sudacevschi V, Bertrand C, Chadenat ML, et al., 2016,
Predictors of occult atrial fibrillation in one hundred
Conceptualization: All authors seventy-one patients with cryptogenic transient ischemic
Investigation: All authors attack and minor stroke. J Stroke Cerebrovasc Dis,
Writing – original draft: All authors 25: 2673–2677.
Writing – review & editing: All authors https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.07.014
Ethics approval and consent to participate 9. Kwong C, Ling AY, Crawford MH, et al., 2017, A clinical
score for predicting atrial fibrillation in patients with
Not applicable. cryptogenic stroke or transient ischemic attack. Cardiology,
138: 133–140.
Consent for publication
https://doi.org/10.1159/000476030
Not applicable.
10. Uphaus T, Weber-Krüger M, Grond M, et al., 2019,
Availability of data Development and validation of a score to detect paroxysmal
atrial fibrillation after stroke. Neurology, 92: e115–e124.
Data can be requested from the corresponding author
following formal request. https://doi.org/10.1212/wnl.0000000000006727
11. Muscari A, Barone P, Faccioli L, et al., 2020, Usefulness of
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Volume 1 Issue 2 (2023) 9 https://doi.org/10.36922/bh.0955