.Left atrial area index provides the best prediction of atrial fibrillation in ischemic stroke patients: results from the LAETITIA observational study

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Left atrial area index provides the best prediction of atrial fibrillation in ischemic stroke patients: results from the LAETITIA observational study

Angelika Alonso¹ Josephine Kraus¹ Anne Ebert¹ Valeriya Nikolayenko² Mathieu Kruska³ Vesile Sandikci¹ Hendrik Lesch¹ Daniel Duerschmied³ Michael Platten¹ Stefan Baumann³ Kristina Szabo¹ Ibrahim Akin³ Christian Fastner^3,4*

• ¹Department of Neurology, University Medical Centre Mannheim and Mannheim Centre for Translational Neurosciences, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
• ²Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
• ³Department of Cardiology, Angiology, Haemostaseology and Medical Intensive Care, University Medical Centre Mannheim, Medical Faculty Mannheim, Heidelberg University, European Center for AngioScience (ECAS), German Center for Cardiovascular Research (DZHK) Partner Site Heidelberg/Mannheim, Mannheim, Germany
• ⁴Department of Geriatrics, University Medical Centre Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

Background and aims: Left atrial (LA) enlargement has been repeatedly shown to be associated with the diagnosis of atrial fibrillation (AF). In clinical practice, several parameters are available to determine LA enlargement: LA diameter index (LADI), LA area index (LAAI), or LA volume index (LAVI). We investigated the predictive power of these individual LA parameters for AF in patients with acute ischemic stroke or transient ischemic attack (TIA).

Methods: LAETITIA is a retrospective observational study that reflects the clinical reality of acute stroke care in Germany. Consecutive patient cases with acute ischemic cerebrovascular event (CVE) in 2019 and 2020 were identified from the Mannheim stroke database. Predictive power of each LA parameter was determined by the area under the curve (AUC) of receiver operating characteristic curves. A cutoff value was determined. A multiple logistic regression analysis was performed to confirm the strongest LA parameter as an independent predictor of AF in patients with acute ischemic CVE.

Results: A total of 1,910 patient cases were included. In all, 82.0% of patients had suffered a stroke and 18.0% had a TIA. Patients presented with a distinct cardiovascular risk profile (reflected by a CHA₂DS₂-VASc score ≥2 prior to hospital admission in 85.3% of patients) and were moderately affected on admission [median NIHSS score 3 (1; 8)]. In total, 19.5% of patients had pre-existing AF, and 8.0% were newly diagnosed with AF. LAAI had the greatest AUC of 0.748, LADI of 0.706, and LAVI of 0.719 (each p < 0.001 vs. diagonal line; AUC-LAAI vs. AUC-LADI p = 0.030, AUC-LAAI vs. AUC-LAVI p = 0.004). LAAI, increasing NIHSS score on admission, and systolic heart failure were identified as independent predictors of AF in patients with acute ischemic CVE. To achieve a clinically relevant specificity of 70%, a cutoff value of ≥10.3 cm²/m² was determined for LAAI (sensitivity of 69.8%).

Conclusion: LAAI revealed the best prediction of AF in patients with acute ischemic CVE and was confirmed as an independent risk factor. An LAAI cutoff value of 10.3 cm²/m² could serve as an inclusion criterion for intensified AF screening in patients with embolic stroke of undetermined source in subsequent studies.

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