Publications by authors named "J Azariah"

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.

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Background: There is ongoing debate around rate versus rhythm control strategies for managing atrial fibrillation (AF), however, much of the data comes from Western cohorts. Kerala-AF represents the largest prospective AF cohort study from the Indian subcontinent.

Objectives: To compare 12-month outcomes between rate and rhythm control strategies.

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Atrial fibrillation (AF) is a significant risk factor for stroke. Based on the higher stroke associated with AF in the South Asian population, we constructed a one-year stroke prediction model using machine learning (ML) methods in KERALA-AF South Asian cohort. External validation was performed in the prospective APHRS-AF registry.

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Background: On September 5, 2020, India reported the second highest COVID-19 cases globally. Given India's unique disease burden including both infectious and chronic diseases, there is a need to study the survival patterns of COVID-19. We aimed to describe the factors associated with COVID-19 deaths in the State of Tamil Nadu that has the highest COVID-19 case burden among the Indian states, and to compare deaths among COVID patients with and without comorbidities.

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Purpose: Limited published data exist on the clinical epidemiology of atrial fibrillation (AF) in South Asia including India. Most of the published data are from the Western countries and the Far East. The Kerala AF registry was initiated to collect systematic, prospective data on clinical characteristics, risk factors, treatment pattern and outcomes of consecutive AF patients who consulted cardiologists across the state of Kerala, India.

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