| Autor: |
Yang Chen, Bi Huang, Peter Calvert, Yang Liu, Ying Gue, Dhiraj Gupta, Garry McDowell, Jinbert Lordson Azariah, Narayanan Namboodiri, Govindan Unni, Jayagopal Pathiyil Balagopalan, Gregory Yoke Hong Lip, Bahuleyan Charantharayil Gopalan, A. Jabir, A. George Koshy, Geevar Zachariah, M. Shifas Babu, K. Venugopal, Eapen Punnose, K.U. Natarajan, Johny Joseph, C. Ashokan Nambiar, P.B. Jayagopal, P.P. Mohanan, Raju George, C.G. Sajeev, N. Syam, Anil Roby, Rachel Daniel, V.V. Krishnakumar, Anand M. Pillai, Stigi Joseph, G.K. Mini, Shaffi Fazaludeen Koya, Koshy Eapen, Raghu Ram, Cibu Mathew, Ali Faizal, Biju Issac, Sujay Renga, Jaideep Menon, D. Harikrishna, K. Suresh, Tiny Nair, S.S. Susanth, R.Anil Kumar, T.P. Abilash, P. Sreekala, E. Rajeev, Arun Raj, Ramdas Naik, S. Rajalekshmi, Anoop Gopinath, R. Binu, Jossy Chacko, P.T. Iqbal, N.M. Sudhir, Madhu Sreedharan, N. Balakrishnan, Muhammed Musthaffa, B. Jayakumar, Sheeba George, Anand Kumar, Thomas Mathew, V.K. Pramod, Muhammed Shaloob, Madhu Paulose Chandy, K.R. Vinod, Karuana Das, Z.Sajan Ahamad, Pramod Mathew |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
The Lancet Regional Health - Southeast Asia, Vol 31, Iss , Pp 100507- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2772-3682 |
| DOI: |
10.1016/j.lansea.2024.100507 |
| Popis: |
Summary: Background: Patients with atrial fibrillation (AF) frequently experience multimorbidity. Cluster analysis, a machine learning method for classifying patients with similar phenotypes, has not yet been used in South Asian AF patients. Methods: The Kerala Atrial Fibrillation Registry is a prospective multicentre cohort study in Kerala, India, and the largest prospective AF registry in South Asia. Hierarchical clustering was used to identify different phenotypic clusters. Outcomes were all-cause mortality, major adverse cardiovascular events (MACE), and composite bleeding events within one-year follow-up. Findings: 3348 patients were included (median age 65.0 [56.0–74.0] years; 48.8% male; median CHA2DS2-VASc 3.0 [2.0–4.0]). Five clusters were identified. Cluster 1: patients aged ≤65 years with rheumatic conditions; Cluster 2: patients aged >65 years with multi-comorbidities, suggestive of cardiovascular-kidney-metabolic syndrome; Cluster 3: patients aged ≤65 years with fewer comorbidities; Cluster 4: heart failure patients with multiple comorbidities; Cluster 5: male patients with lifestyle-related risk factors. Cluster 1, 2 and 4 had significantly higher MACE risk compared to Cluster 3 (Cluster 1: OR 1.36, 95% CI 1.08–1.71; Cluster 2: OR 1.79, 95% CI 1.42–2.25; Cluster 4: OR 1.76, 95% CI 1.31–2.36). The results for other outcomes were similar. Atrial fibrillation Better Care (ABC) pathway in the whole cohort was low (10.1%), especially in Cluster 4 (1.9%). Overall adherence to the ABC pathway was associated with reduced all-cause mortality (OR 0.26, 95% CI 0.15–0.46) and MACE (OR 0.45, 95% CI 0.31–0.46), similar trends were evident in different clusters. Interpretation: Cluster analysis identified distinct phenotypes with implications for outcomes. There was poor ABC pathway adherence overall, but adherence to such integrated care was associated with improved outcomes. Funding: Kerala Chapter of Cardiological Society of India. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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