Original Article
A novel association of adenosine deaminase with paroxysmal atrial fibrillation: a propensity score analysis from a case-control study
Abstract
Introduction: Prior work has indentified age, body mass index, underlying heart disease, and other comorbidities as risk factors for atrial fibrillation. To date, studies have examined single baseline measures of traditional risk factors, and data on biomarker associations are lacking. Aim: We sought to explore novel biochemical measures possibly associated with incident PAF after balancing the traditional risk factors.
Methods: Men or women aged ≥18 years that were hospitalized between 1st Jan. 2010 and 31st Dec. 2013 for paroxysmal atrial fibrillation (PAF) and for health checkup (non-PAF) were included. We used propensity score methods to mitigate the influence of the nonrandom selection of PAF and non-PAF patients. Logistic regression was applied for analysis of risk factors for PAF.
Results: A total of 1,802 eligible patients were identified, in whom, 895 patients had at least one exclusion criterion. After excluding these patients, the total analytic cohort numbered 907 patients. Of these, 779 patients were for control group and 128 patients were for PAF group. Propensity score matching was used to obtain a balanced cohort of 124 patients per group. The PAF and non-PAF groups were well matched on demographic and clinical characteristics after propensity matching. Risk factors for PAF on multivariate stepwise logistic regression model included adenosine deaminase (ADA) [odds ratio (OR) =0.9160, P=0.015, 95% confidence interval (CI): 0.8536-0.9829], mitral valvular regurgitation (OR =3.4611, P=0.001, 95% CI: 1.7000-7.0467) and left atrial diameter (OR =1.0913, P=0.001, 95% CI: 1.0387-1.1465). Only the ADA was a protective factor for the occurrence of PAF.
Conclusions: The ADA seems to be associated with PAF. The current study provides new insights into the prevention and treatment of PAF.
Methods: Men or women aged ≥18 years that were hospitalized between 1st Jan. 2010 and 31st Dec. 2013 for paroxysmal atrial fibrillation (PAF) and for health checkup (non-PAF) were included. We used propensity score methods to mitigate the influence of the nonrandom selection of PAF and non-PAF patients. Logistic regression was applied for analysis of risk factors for PAF.
Results: A total of 1,802 eligible patients were identified, in whom, 895 patients had at least one exclusion criterion. After excluding these patients, the total analytic cohort numbered 907 patients. Of these, 779 patients were for control group and 128 patients were for PAF group. Propensity score matching was used to obtain a balanced cohort of 124 patients per group. The PAF and non-PAF groups were well matched on demographic and clinical characteristics after propensity matching. Risk factors for PAF on multivariate stepwise logistic regression model included adenosine deaminase (ADA) [odds ratio (OR) =0.9160, P=0.015, 95% confidence interval (CI): 0.8536-0.9829], mitral valvular regurgitation (OR =3.4611, P=0.001, 95% CI: 1.7000-7.0467) and left atrial diameter (OR =1.0913, P=0.001, 95% CI: 1.0387-1.1465). Only the ADA was a protective factor for the occurrence of PAF.
Conclusions: The ADA seems to be associated with PAF. The current study provides new insights into the prevention and treatment of PAF.
