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. 2024 Nov 12;8(21):5625-5638.
doi: 10.1182/bloodadvances.2024013208.

Atrial arrhythmia in adults with sickle cell anemia: a missing link toward understanding and preventing strokes

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Atrial arrhythmia in adults with sickle cell anemia: a missing link toward understanding and preventing strokes

Thomas d'Humières et al. Blood Adv. .

Abstract

Although patients with homozygous sickle cell anemia (SCA) carry both significant left atrial (LA) remodeling and an increased risk of stroke, the prevalence of atrial arrhythmia (AA) has never been prospectively evaluated. The aim of this study was to identify the prevalence and predictors of atrial arrhythmia in SCA. From 2018 to 2022, consecutive adult patients with SCA were included in the DREPACOEUR prospective registry and referred to the physiology department for cardiac evaluation, including a 24-hour electrocardiogram monitoring (ECG-Holter). The primary endpoint was the occurrence of AA, defined by the presence of excessive supraventricular ectopic activity (ESVEA) on ECG-Holter (ie >720 premature atrial contractions [PACs] or any run ≥ 20 PACs) or any recent history of atrial fibrillation. Overall, 130 patients with SCA (mean age: 45±12 years, 48% of male) were included. AA was found in 34 (26%) patients. Age (52±9 vs. 42±12 years, P=0,002), LA dilation (LAVi, 71±24 vs. 52±14 mL/m², P<0.001) and history of stroke without underlying cerebral vasculopathy (26% vs. 5%, P=0.009, OR=6.6 (95%CI 1.4-30.3]) were independently associated with AA. Age and LAVi correlated with PAC load per 24 hours on ECG-Holter. An age over 47 years or a LAVi >55mL/m² could predict AA with a PPV of 33% and a NPV of 92%. AAs are frequent in middle-aged patients with SCA and increase with age and LA remodeling, leading to a major additional risk factor for ischemic stroke. This study provides arguments and means to early screen for AA and potentially prevent cerebral complications.

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Conflict of interest statement

Conflict-of-interest disclosure: P. Bartolucci. received grants from Addmedica, Fabre Foundation, Novartis, and Bluebird in the past 36 months; consulting fees from Addmedica, Novartis, Roche, GBT, Bluebird, Emmaus, Hemanext, and Agios; received honoraria for lectures from Novartis, Addmedica, Jazz Pharmaceuticals; and reports being a member of the Novartis steering committee and cofounder of Innovhem. The remaining authors declare no competing financial interests.

Figures

None
Graphical abstract
Figure 1.
Figure 1.
Continuous variables associated with AA. A biplot representation of the relationship between continuous variables (lines) associated with AA while simultaneously displaying the patients (dots) based on their individual characteristics. Results are projected onto the 2 first dimensions yielded by component analysis. Green dots represent patients without AA and red dots represent patients with AA.
Figure 2.
Figure 2.
Independant variables associated with AA. Correlation observed between PACs (logarithmic scale) and age (A) and indexed LA volume (B). Receiver operating characteristic curves of age and LAVi for identifying AA and determination of the optimal thresholds (with the best sensitivity and specificity) (C).
Figure 3.
Figure 3.
Proposal for AA screening in patients with SCA. ∗If 1 criterion among age or LAVi is present and ∗∗ESVEA.

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