<p>Managing atrial fibrillation (AF) patients with multiple comorbidities and complex medications is challenging. This study aimed to identify different patient profiles of AF based on comorbidities and medicines combinations and to explore their associations with the risk of adverse outcomes. This cohort study included patients with AF from the anticoagulant outpatient clinic at a hospital in Italy, undergoing follow-ups every 6&#xa0;months. Comorbidity and medication patterns were identified using latent class analysis. Cox regression was used to explore associations with thromboembolism, major bleeding, falls, and death—separately and composite. A total of 633 patients with AF (mean age 80.5 ± 6.9&#xa0;years, 52.5% women) treated with direct oral anticoagulants were followed for a median of 24.2 (IQR 12.1–35.5) months. Four patterns were identified: unspecific pattern (39.0%), diabetes and liver pattern (14.8%), neurocognitive and psychiatric pattern (14.1%), and musculoskeletal, immunologic and dermatologic pattern (32.1%). After adjustments, the neurocognitive and psychiatric pattern was associated with a higher risk of the composite outcome (hazard ratio [HR] [95% CI]: 1.75 [1.56–3.82]), thromboembolism (HR: 3.04 [1.28–7.22]) and major bleeding (HR: 2.55 [1.05–6.22]) compared to the non-specific pattern. The musculoskeletal, immunologic, and dermatologic pattern was also associated with a higher bleeding risk (HR: 2.21 [1.05–4.65]). Stratified analyses showed that these links were stronger in patients without cancer, and there was significant interaction in bleeding risk based on cancer status (<i>p</i> = 0.014). Anticoagulated AF patients with the neurocognitive and psychiatric profile are at higher risk, emphasizing the need for holistic AF management.</p>

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Comorbidity and medication patterns in atrial fibrillation patients: association with adverse clinical outcomes

  • Dilek Celik,
  • Cheima Amrouch,
  • Søren Paaske Johnsen,
  • Gregory Y. H. Lip,
  • Davide Liborio Vetrano,
  • Mirko Petrovic,
  • Bruno Micael Zanforlini,
  • Giuseppe Sergi,
  • Nicola Ferri,
  • Caterina Trevisan,
  • Søren Paaske Johnsen,
  • Riccardo Proietti,
  • Pia Cordsen,
  • Gregory Lip,
  • Deirdre Lane,
  • Martin O’Flaherty,
  • Carrol Gamble,
  • Iain Buchan,
  • Christodoulos Kypridemos,
  • Brendan Collins,
  • Donato Leo,
  • Mirko Petrovic,
  • Delphine De Smedt,
  • Stefanie De Buyser,
  • Cheima Amrouch,
  • Davide Liborio Vetrano,
  • Amaia Calderón-Larrañaga,
  • Lu Dai,
  • Stefania Maggi,
  • Marianna Noale,
  • Gheorghe-Andrei Dan,
  • Anca Rodica Dan,
  • Elisabeta Badila,
  • Nicola Ferri,
  • Alessandra Buja,
  • Giuseppe Sergi,
  • Vincenzo Stefano Rebba,
  • Caterina Trevisan,
  • Tatjana Potpara,
  • Laura Vivani,
  • Silvia Ananstasia,
  • Alessandro Ferri,
  • Gehad Shehata,
  • Nadia Rosso,
  • Marco Cicerone,
  • Jacek Marczyk,
  • Trudie Lobban,
  • Georg Ruppe,
  • Graziano Onder,
  • Federica Censi,
  • Roberto Da Cas,
  • Cecilia Damiano,
  • Guendalina Graffigna,
  • Caterina Bosio,
  • Lorenzo Palamenghi,
  • Serena Barello,
  • Aldo Pietro Maggioni,
  • Andrea Lorimer,
  • Donata Lucci,
  • Dipak Kalra,
  • Nathan Lea,
  • John Ainsworth,
  • Charlotte Stockton-Powdrell,
  • Alam Sanaullah,
  • Francisco Marín Ortuño,
  • José Miguel Rivera-Caravaca,
  • Mariya Tokmakova

摘要

Managing atrial fibrillation (AF) patients with multiple comorbidities and complex medications is challenging. This study aimed to identify different patient profiles of AF based on comorbidities and medicines combinations and to explore their associations with the risk of adverse outcomes. This cohort study included patients with AF from the anticoagulant outpatient clinic at a hospital in Italy, undergoing follow-ups every 6 months. Comorbidity and medication patterns were identified using latent class analysis. Cox regression was used to explore associations with thromboembolism, major bleeding, falls, and death—separately and composite. A total of 633 patients with AF (mean age 80.5 ± 6.9 years, 52.5% women) treated with direct oral anticoagulants were followed for a median of 24.2 (IQR 12.1–35.5) months. Four patterns were identified: unspecific pattern (39.0%), diabetes and liver pattern (14.8%), neurocognitive and psychiatric pattern (14.1%), and musculoskeletal, immunologic and dermatologic pattern (32.1%). After adjustments, the neurocognitive and psychiatric pattern was associated with a higher risk of the composite outcome (hazard ratio [HR] [95% CI]: 1.75 [1.56–3.82]), thromboembolism (HR: 3.04 [1.28–7.22]) and major bleeding (HR: 2.55 [1.05–6.22]) compared to the non-specific pattern. The musculoskeletal, immunologic, and dermatologic pattern was also associated with a higher bleeding risk (HR: 2.21 [1.05–4.65]). Stratified analyses showed that these links were stronger in patients without cancer, and there was significant interaction in bleeding risk based on cancer status (p = 0.014). Anticoagulated AF patients with the neurocognitive and psychiatric profile are at higher risk, emphasizing the need for holistic AF management.