Prognostic Capacity of Oxidative Biomarkers in Paroxysmal Atrial Fibrillation
Mariya Negreva1, Krasimira Prodanova2, Katerina Vitlianova3, Albena Alexandrova4

1Mariya Negreva, MD, PhD, working as Asst. Prof., in Intensive Care Unit at University hospital of Varna, Bulgaria.
2Krasimira Prodanova, B.Sc (Faculty of Mathematics, Informatics and Mechanics) University of Sofia, Bulgaria.
3Katerina Vitlianova, PhD, DSc, Master of Phylosophy degree in Epidemiology and Biostatistics – Cambridge University, UK.
4Albena Alexandrova, PhD, DSc, Master of Phylosophy degree in Epidemiology and Biostatistics – Cambridge University, UK.
Manuscript received on May 01, 2015. | Manuscript Received on May 07, 2015. | Manuscript published on May 20, 2015. | PP: 1-5 | Volume-1 Issue-6, May 2015
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Abstract: Background: In our previous studies on the oxidative status of patients with paroxysmal atrial fibrillation (PAF) we found eight oxidative biomarkers – plasma malondialdehyde (Pl-MDA), erythrocyte malondialdehyde (Er-MDA), plasma glutathione (Pl-GSH), erythrocyte glutathione (Er-GSH), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px) and glucose-6-phosphate dehydrogenase (Glu-6-PhD) – that changed significantly still in the first twenty-four hours of the arrhythmia clinical presentation. It is exactly their early changes that suggest a correlation of these biomarkers with the trigger mechanisms of the rhythm disorder which then raise the question of how efficiently they can predict PAF occurrence. Aim: To analyse the changes in these oxidative biomarkers as predictive for PAF development. Place and duration of study: The participants were recruited in 1st Cardiology Clinic of St Marina University Hospital, Varna, Bulgaria, between October 2010 and May 2012. Patients and methods: The oxidative indicators were measured in 51 patients (26 men; mean age 59.84 ± 1.60) and 52 controls (26 men; mean age 59.50 ± 1.46) matched in age, sex, concomitant diseases, harmful habits and body mass index. Blood samples were collected once. A dichotomous logistic regression analysis was performed to identify the oxidative biomarkers (explanatory variables) independently associated with PAF appearance. Eight logistic models with a single explanatory variable were considered to find statistically significant predictors for PAF. A multiple logistic model was used to assess simultaneously the predictive value of all statistically significant explanatory variables. Results: The logistic regression models with a single explanatory variable showed that six of the eight indicators were associated with PAF development: Pl-MDA (P=0.03), Er-MDA (P<0.001), Pl-GSH (P< 0.001), SOD (P< 0.001), CAT (P< 0.001), GSH-Px (P< 0.001). The multiple logistic model using all six explanatory variables confirmed the results (P=0.006). Constructed models were used to obtain adjusted estimate of odds and a prediction success matrix. It was found that the multiple logistic model could measure the PAF probability using values of these six markers. Conclusion: Pl-MDA, Er-MDA, Pl-GSH, SOD, CAT and GSH-Px were found to be oxidative biomarkers with predictive value for PAF occurrence. In clinical practice for each measured value of these biomarkers, the probability of the arrhythmia manifestation could be calculated.
Keywords: Atrial fibrillation, oxidative markers, prediction, occurrence.