Patterns of comorbidities in patients with atrial fibrillation and impact on management and long-term prognosis: an analysis from the Prospective Global GLORIA-AF Registry

• Published in: BMC medicine Vol. 22; no. 1; pp. 151 - 12
• Main Authors: Romiti, Giulio Francesco, Corica, Bernadette, Mei, Davide Antonio, Bisson, Arnaud, Boriani, Giuseppe, Olshansky, Brian, Chao, Tze-Fan, Huisman, Menno V, Proietti, Marco, Lip, Gregory Y H
• Format: Journal Article
• Language: English
• Published: England BioMed Central 08-04-2024; BMC
• Subjects: Aged; Aged, 80 and over; Aging; Anticoagulants; Arteriosclerosis; Atherosclerosis; Atrial fibrillation; Atrial Fibrillation - drug therapy; Atrial Fibrillation - epidemiology; Cardiac arrhythmia; Cardiovascular disease; Cardiovascular diseases; Chronic obstructive pulmonary disease; Clinical complexity; Comorbidities; Comorbidity; Complexity; Diabetes; Diltiazem; Drugs; Female; Fibrillation; Humans; Hypertension; Latent class analysis; Male; Medical prognosis; Middle Aged; Mortality; Multimorbidity; Phenotypes; Prognosis; Prospective Studies; Registries; Regression analysis; Risk Factors; Stroke; Stroke - epidemiology; Thromboembolism; Transient ischemic attack; Treatment Outcome; Vein & artery diseases; Verapamil; Comorbidities; Atrial fibrillation; Clinical complexity; Multimorbidity
• ISSN: 1741-7015; 1741-7015
• DOI: 10.1186/s12916-024-03373-4

Clinical complexity, as the interaction between ageing, frailty, multimorbidity and polypharmacy, is an increasing concern in patients with AF. There remains uncertainty regarding how combinations of comorbidities influence management and prognosis of patients with atrial fibrillation (AF). We aimed to identify phenotypes of AF patients according to comorbidities and to assess associations between comorbidity patterns, drug use and risk of major outcomes.
From the prospective GLORIA-AF Registry, we performed a latent class analysis based on 18 diseases, encompassing cardiovascular, metabolic, respiratory and other conditions; we then analysed the association between phenotypes of patients and (i) treatments received and (ii) the risk of major outcomes. Primary outcome was the composite of all-cause death and major adverse cardiovascular events (MACE). Secondary exploratory outcomes were also analysed.
32,560 AF patients (mean age 70.0 ± 10.5 years, 45.4% females) were included. We identified 6 phenotypes: (i) low complexity (39.2% of patients); (ii) cardiovascular (CV) risk factors (28.2%); (iii) atherosclerotic (10.2%); (iv) thromboembolic (8.1%); (v) cardiometabolic (7.6%) and (vi) high complexity (6.6%). Higher use of oral anticoagulants was found in more complex groups, with highest magnitude observed for the cardiometabolic and high complexity phenotypes (odds ratio and 95% confidence interval CI): 1.76 [1.49-2.09] and 1.57 [1.35-1.81], respectively); similar results were observed for beta-blockers and verapamil or diltiazem. We found higher risk of the primary outcome in all phenotypes, except the CV risk factor one, with highest risk observed for the cardiometabolic and high complexity groups (hazard ratio and 95%CI: 1.37 [1.13-1.67] and 1.47 [1.24-1.75], respectively).
Comorbidities influence management and long-term prognosis of patients with AF. Patients with complex phenotypes may require comprehensive and holistic approaches to improve their prognosis.