Table of Contents Author Guidelines Submit a Manuscript
Parkinson’s Disease
Volume 2018, Article ID 2916905, 5 pages
https://doi.org/10.1155/2018/2916905
Research Article

Assessment of Atrial Conduction Times in Patients with Newly Diagnosed Parkinson’s Disease

1Department of Cardiology, Dr. Siyami Ersek Cardiovascular and Thoracic Surgery Center, Istanbul, Turkey
2Department of Neurology, Haydarpasa Numune Training and Research Hospital, Istanbul, Turkey

Correspondence should be addressed to Yiğit Çanga; moc.liamtoh@18agnac

Received 3 March 2018; Accepted 12 June 2018; Published 16 July 2018

Academic Editor: Jan Aasly

Copyright © 2018 Yiğit Çanga et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background. An increased risk of ischemic stroke has been reported in patients with Parkinson’s disease (PD). Atrial fibrillation (AF) is strongly associated with ischemic stroke. Prolonged atrial electromechanical delay (EMD) is an independent predictor for the development of AF. Aims. The aim of the present study was to evaluate the atrial conduction parameters in patients with PD and to assess their relation with the severity of PD. Study design. We prospectively enrolled 51 consecutive patients with newly diagnosed PD and 31 age- and sex-matched non-PD subjects. Methods. To assess atrial electromechanical coupling (PA), the time intervals from the onset of p wave on ECG to the late diastolic wave at the septal (PAs) and lateral (PAl) mitral annulus and lateral tricuspid annulus (PAt) were measured on Tissue Doppler Echocardiography (TDE). The difference between PAs-PAl, PAs-PAt, and PAl-PAt were defined as left intra-atrial, right intra-atrial, and interatrial EMD, respectively. P-wave dispersion (PWD) was calculated from the 12-lead ECG. Results. PWD, PAs, PAl, and PAt durations were significantly prolonged in the PD group (all ). Interatrial, right, and left intra-atrial EMD were also significantly longer in PD patients (, and , resp.). There were significant positive correlations between disease severity (UPDRS score) and PWD (, ), left intra-atrial (, ), and interatrial EMD (, ). By multivariate analysis, PWD (OR: 1.13, 95% CI: 1.02–1.25; ), LA volume index (OR: 1.19, 95% CI: 1.02–1.37; ), left intra-atrial (OR: 1.12, 95% CI: 1.01–1.24; ), and interatrial EMD (OR: 1.08, 95% CI: 1.01–1.16; ) were found as independent predictors of PD. Conclusion. Atrial conduction times were longer and correlated with the severity of disease in PD patients. Prolonged inter- and intra-atrial-EMD intervals were also found as independent correlates of PD. These findings may suggest an increased predisposition to atrial fibrillation in PD.

1. Introduction

Parkinson’s disease (PD) has been associated with an increased risk of ischemic stroke and stroke-related mortality [13]. A recent population-based, propensity score-matched longitudinal follow-up study demonstrated that newly diagnosed PD was related with an increased risk of developing ischemic stroke [4]. Patients with atrial fibrillation have about 3- to 5-fold higher risk of stroke even after adjustment for risk factors [5]. Atrial fibrillation has been associated with stroke in different patient populations [6]. Prediction of atrial fibrillation may be crucial for risk stratification of PD patients with regard to ischemic stroke.

Prolonged atrial conduction times have been related to both onset and recurrence of atrial fibrillation [7, 8]. Tissue Doppler Echocardiography (TDE) has been used to determine atrial electromechanical coupling and electromechanical delay (EMD) intervals between different regions as indicators of electrical and/or structural remodeling of atria and as predictors of atrial fibrillation [9]. Regional changes in atrial conduction times might have a different influence on surface p waves leading to an interlead variation in p-wave duration called p-wave dispersion (PWD) [10]. In the present study, we investigated atrial conduction parameters in patients with newly diagnosed PD and also evaluated their relationship with the severity of PD.

2. Methods

2.1. Study Population

Fifty-one consecutive patients with newly diagnosed PD and 31 age- and sex-matched non-PD subjects were prospectively enrolled between January 1st, 2015 and December 31, 2015. Patients with PD were diagnosed according to the UK Parkinson’s Disease Society Brain Bank Criteria [11]. The severity of PD was assessed by Unified Parkinson’s Disease Rating Scale (UPDRS) [12]. Patients with a previous diagnosis of PD, stroke, other extrapyramidal disease, abnormal movement disorder, cerebral degeneration, cardiac arrhythmia, valvular heart disease, heart failure, coronary artery disease, chronic obstructive pulmonary disease, chronic renal failure, thyroid disease, active infectious disease, poor echocardiographic image quality, and a history of cardiac surgery or implanted device were excluded from the study. Baseline history, medication, and electrocardiography were recorded at the beginning of enrollment. PWD was defined as the difference between the maximum and minimum p-wave duration from multiple surface ECG leads [10]. The study was approved by the local ethics committee. Written informed consents were obtained from all participants.

2.2. Echocardiography

All patients were evaluated by transthoracic M mode, two dimensional, pulsed wave, continuous wave, colour flow, and TDE using the GE Vivid 3 system (GE Vingmed, Horten, Norway) with a 2.5–3.5 MHz transducer. Continuous single lead ECG was obtained from each participant during echocardiography.

LV diameter and wall thickness were measured by M-mode echocardiography. LV ejection fraction was calculated by Simpson’s method according to the American Society of Echocardiography guidelines [13]. The mitral valve inflow pattern (E wave, A wave, E-wave deceleration time, E/A ratio, and isovolumic relaxation time) was measured by pulsed wave Doppler. LA volume was obtained from apical four and two chamber views by a disc method and indexed to body surface area [13].

TDE was performed by adjusting the pulsed Doppler signal filters to acquire the Nyquist limit of 15–20 cm/s and using the minimal optimal gain. Motions were recorded simultaneously with electrocardiogram in lead II to assess the relation between atrial electrical phases and myocardial motion. To assess atrial electromechanical coupling (PA), the time intervals from the onset of p wave on ECG to the late diastolic wave at the septal (PAs), and lateral (PAl) mitral annulus and lateral tricuspid annulus (PAt) were measured on TDE. The difference between PAs-PAl, PAs-PAt, and PAl-PAt were defined as left intra-atrial, right intra-atrial and interatrial EMD, respectively [7, 9]. Echocardiographic measurements were performed by two cardiologists. Patients with a > 5% difference between the measurements of two cardiologists were not included.

2.3. Statistical Analysis

Statistical analysis was performed using SPSS 16.0 (SPSS, Inc. Chicago, Illinois). A two-tailed  value < 0.05 was considered statistically significant. Categorical variables were expressed as frequencies (percentages). Continuous variables were presented as mean ± standard deviation (tested for normality with Shapiro–Wilk test). Categorical variables were compared using the chi-square or Fischer’s exact tests. Group means for continuous variables were compared using independent sample t-test. Pearson’s correlation test was performed to assess the correlation between atrial conduction times and the severity of PD. Multivariate regression analysis was used to identify independent predictors of PD. Age, gender, hypertension, diabetes, LA volume index, PWD, and EMD intervals were included in the multivariate models.

3. Results

Fifty-one consecutive PD patients (mean age: 66.3 ± 12.4 years and 71% men) and 31 non-PD subjects (mean age: 69.8 ± 12.7 years and 52% men) entered the study. Mean UPDRS score of the PD group was 35.3 ± 17.9 (range, 10 to 75). Baseline demographic and clinical characteristics of the PD and non-PD groups are provided in Table 1. There was no statistically significant difference in all the baseline characteristics between the PD and non-PD groups.

Table 1: Baseline demographic and clinical data of the study patients.

Echocardiographic parameters are provided in Table 2. LA volume index was significantly higher in the PD group (). Mitral E/A was lower and mitral E-wave deceleration time was higher in the PD group, but both failed to reach statistical significance ( and , resp.). The remaining standard echocardiographic parameters were comparable between the two groups.

Table 2: Echocardiographic data and atrial conduction time intervals of the study patients.

Atrial conduction time intervals are shown in Table 2. PWD, PAs, PAl, and PAt durations were significantly prolonged in the PD group (all ). Left intra-atrial, right intra-atrial, and interatrial EMD were significantly longer in PD patients (, , and , resp.). PWD showed significant correlations with left intra-atrial (, ) and interatrial EMD (, ).

There were significant positive correlations between disease severity (UPDRS score) and PWD (, ), left intra-atrial (, ), and interatrial EMD (, ) (Figure 1). By multivariate analysis, PWD (OR: 1.13, 95% CI: 1.02–1.25; ), LA volume index (OR: 1.19, 95% CI: 1.02–1.37; ), left intra-atrial (OR: 1.12, 95% CI: 1.01–1.24; ), and interatrial EMD (OR: 1.08, 95% CI: 1.01–1.16; ) were found to be independent predictors of PD (Table 3).

Figure 1: (a) Correlation between left intra-atrial EMD and the severity of Parkinson’s disease (UPDRS score). (b) Correlation between p-wave dispersion and the severity of Parkinson’s disease. (c) Correlation between interatrial EMD and the severity of Parkinson’s disease UPDRS, Unified Parkinson’s Disease Rating Scale; EMD, electromechanical delay.
Table 3: Multivariate analyses of variables associated with Parkinson’s disease.

4. Discussion

The major findings of the present study are (1) patients with newly diagnosed PD are more likely to have abnormal atrial conduction times as assessed by prolonged PWD, PAs, PAl, PAt, intra-atrial, and interatrial EMD; (2) prolonged atrial conduction times were significantly correlated with the severity of PD as assessed by the UPDRS score, and (3) PWD, left intra-atrial, and interatrial EMD were found to be independent predictors of PD.

Atrial fibrillation is the most common sustained arrhythmia in clinical practice [14]. Electrophysiological studies have revealed prolonged atrial conduction times as predictors of atrial fibrillation [15, 16]. In a previous study examining atrial conduction times with TDE, Deniz et al. have found significant correlations regarding left intra-atrial and interatrial conduction times detected by TDE and by electrophysiological study [9]. PWD and left intra-atrial conduction time detected by TDE were found to be independent predictors of inducibility of sustained atrial fibrillation in their study. Sequential analysis of atrial electromechanical coupling to evaluate the mechanisms of paroxysmal atrial fibrillation showed that atrial electromechanical coupling at the interventricular septum, left lateral mitral annulus, and right lateral tricuspid annulus was significantly longer in patients with paroxysmal atrial fibrillation (with or without underlying heart disease) compared to control subjects [7]. Left intra-atrial EMD was significantly prolonged even after correction for age in patients with atrial fibrillation [7]. The juxtaposition of atrial fibrotic lesions with normal atrial fibers has been suggested as a mechanism for nonhomogeneity of atrial conduction in atrial fibrillation [17]. Prolongation of atrial electromechanical coupling might be due to the time delay from atrial electric activation to myocardial contraction and/or left atrial enlargement [8]. In our study, PAs, PAl, and PAt durations were significantly prolonged and interatrial, right intra-atrial, and left intra-atrial EMD were significantly longer in patients with newly diagnosed PD. LA volume index was also increased in patients with PD.

Previous clinical studies have shown electrocardiographic PWD to be a predictor of paroxysmal atrial fibrillation [10]. PWD reflects inhomogeneous atrial conduction via variation in p-wave duration between different surface ECG leads [18, 19]. PWD was significantly prolonged in PD patients in our study. Furthermore, we demonstrated that PWD had significant correlations with left intra-atrial and interatrial EMD durations in PD patients.

Patients with atrial fibrillation have an increased risk of stroke even after adjustment for risk factors [5]. PD has also been related with an increased risk of stroke [13]. Therefore, prediction of development of atrial fibrillation might be vital for risk stratification of PD patients with regard to ischemic stroke. Indeed, prolonged atrial conduction times were found to be significantly correlated with the severity of PD in our study.

Several potential explanations may be postulated for the pathophysiologic mechanisms by which atrial fibrillation and PD may be related. First, both atrial fibrillation and PD are associated with an increased inflammatory state [2023]. Neuroinflammation plays an important role in the pathogenesis of PD and contributes to the progressive loss of nigral dopaminergic neurons [20]. Inflammatory responses mediated by activated glial cells, T cell infiltration, and increased expression of inflammatory cytokines are described as features of PD [20]. Likewise, the prevalence and prognosis of atrial fibrillation have been associated with increased levels of inflammatory markers [21, 22]. Moreover, high-sensitivity C-reactive protein levels have shown significant positive correlations with stroke risk factors in atrial fibrillation patients and have been associated with a composite endpoint of ischemic stroke, myocardial infarction, and death [23]. Second, oxidative stress plays an important role in the pathogenesis of atrial fibrillation and PD [24, 25]. Oxidative stress has been shown to increase dopamine cell degeneration in PD [24]. Increased oxidative stress measured by the redox potentials of glutathione has been found to be an independent predictor of atrial fibrillation after adjustment for risk factors, heart failure, coronary artery disease, and high-sensitivity C-reactive protein levels [25]. Third, dysfunction of the autonomic nervous system is a common occurrence in atrial fibrillation and PD [2629]. Symptoms of cardiovascular dysautonomia such as orthostatic hypotension have been frequently reported in PD [26]. Likewise, increased vagal tone has been related to the onset of paroxysmal atrial fibrillation both through cholinergic and noncholinergic pathways [27, 28]. An interaction between sympathetic and parasympathetic nervous system demonstrated via recording activities from stellate ganglia and vagal nerve has been shown to play a role in the development of atrial fibrillation [29].

A limitation of our study might be that the study population was not followed up in terms of development of atrial fibrillation. Another limitation might be that data regarding inflammatory and oxidative markers were not studied. Also because of the limited number of patients included in the study, our findings require validation and further studies with larger patient groups with follow-up for arrhythmias are needed.

In conclusion, the present study showed that atrial conduction times were prolonged in patients with newly diagnosed PD. Furthermore, atrial conduction parameters were significantly correlated with the severity of PD. Our findings might contribute to risk stratification of PD patients with regard to atrial fibrillation.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Disclosure

The manuscript was presented as an oral presentation at “14th International Congress of Update in Cardiology and Cardiovascular Surgery” and published as abstract at the supplement of The American Journal of Cardiology (Volume 121, Issue 8, Supplement, 15 April 2018, Page e54).

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

  1. C. Becker, S. S. Jick, and C. R. Meier, “Risk of stroke in patients with idiopathic Parkinson’s disease,” Parkinsonism & Related Disorders, vol. 16, no. 1, pp. 31–35, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. Y. Ben-Shlomo and M. G. Marmot, “Survival and cause of death in a cohort of patients with parkinsonism: possible clue to etiology?” Journal of Neurology, Neurosurgery & Psychiatry, vol. 58, no. 3, pp. 293–299, 1995. View at Publisher · View at Google Scholar · View at Scopus
  3. J. M. Gorel, C. C. Johnson, and B. A. Rybicki, “Parkinson’s disease and its comorbid disorders: an analysis of Michigan mortality data, 1970 to 1990,” Neurology, vol. 44, no. 10, pp. 1865–1868, 1994. View at Publisher · View at Google Scholar
  4. Y.-P. Huang, L.-S. Chen, M.-F. Yen et al., “Parkinson’s disease is related to an increased risk of ischemic stroke-a population-based propensity score-matched follow-up study,” PLoS One, vol. 8, no. 9, Article ID e68314, 2013. View at Publisher · View at Google Scholar
  5. P. A. Wolf, T. R. DAwber, H. E. Thomas Jr., and W. B. Kannel, “Epidemiologic assessment of chronic atrial fibrillation and risk of stroke: The Framingham Study,” Neurology, vol. 28, no. 10, pp. 973–977, 1978. View at Publisher · View at Google Scholar
  6. T. A. Manolio, R. A. Kronmal, G. L. Burke, D. H. O’leary, and T. R. Price, “Short-term predictors of incident stroke in older adults: the Cardiovascular Health Study,” Stroke, vol. 27, no. 9, pp. 1479–1486, 1996. View at Publisher · View at Google Scholar · View at Scopus
  7. Q. Q. Cui, W. Zhang, H. Wang et al., “Assessment of atrial electromechanical coupling and influential factors in nonrheumatic paroxysmal atrial fibrillation,” Clinical Cardiology, vol. 31, no. 2, pp. 74–78, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. W. Omi, H. Nagai, M. Takamura et al., “Doppler tissue analysis of atrial electromechanical coupling in paroxysmal atrial fibrillation,” Journal of the American Society of Echocardiography, vol. 18, no. 1, pp. 39–44, 2005. View at Publisher · View at Google Scholar · View at Scopus
  9. A. Deniz, D. Y. Sahin, and M. Kanadasi, “Conduction characteristics in atrial fibrillation,” Herz, vol. 39, no. 1, pp. 137–141, 2014. View at Publisher · View at Google Scholar · View at Scopus
  10. S. Okutucu, K. Aytemir, and A. Oto, “P-wave dispersion: what we know till now?” JRSM Cardiovascular Disease, vol. 5, Article ID 2048004016639443, 2016. View at Publisher · View at Google Scholar
  11. A. J. Hughes, S. E. Daniel, L. Kilford, and A. J. Lees, “Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: a clinico-pathological study of 100 cases,” Journal of Neurology, Neurosurgery and Psychiatry, vol. 55, no. 3, pp. 181–184, 1992. View at Publisher · View at Google Scholar · View at Scopus
  12. Movement Disorder Society Task Force on Rating Scales for Parkinson’s Disease, “The Unified Parkinson’s Disease Rating Scale (UPDRS): status and recommendations,” Movement Disorders, vol. 18, no. 7, Article ID 738750, 2003. View at Google Scholar
  13. R. M. Lang, M. Bierig, F. A. Flachskampf et al., “Recommendations for chamber quantification: a report from the American society of Echocardiography’s guidelines and standards committee and the chamber quantification writing group, developed in conjunction with the European association of Echocardiography, a branch of the European Society of Cardiology,” Journal of the American Society of Echocardiography, vol. 18, no. 12, pp. 1440–1463, 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. C. R. C. Wyndham, “Atrial fibrillation: the most common arrhythmia,” Texas Heart Institute Journal, vol. 27, no. 3, pp. 257–267, 2000. View at Google Scholar
  15. JC. Daubert, D. Pavin, G. Jauvert, and P. Mabo, “Intra- and interatrial conduction delay: implications for cardiac pacing,” Pacing and Clinical Electrophysiology, vol. 27, no. 4, pp. 507–525, 2004. View at Publisher · View at Google Scholar · View at Scopus
  16. P. Papageorgiou, K. Monahan, N. G. Boyle et al., “Site-dependent intra-atrial conduction delay: relationship to initiation of atrial fibrillation,” Circulation, vol. 94, no. 3, pp. 384–389, 1996. View at Publisher · View at Google Scholar · View at Scopus
  17. M. Allessie, J. Ausma, and U. Schotten, “Electrical, contractile and structural remodeling during atrial fibrillation,” Cardiovascular Research, vol. 54, no. 2, pp. 230–246, 2002. View at Publisher · View at Google Scholar · View at Scopus
  18. P. E. Dilaveris and J. E. Gialafos, “P-wave dispersion: a novel predictor of paroxysmal atrial fibrillation,” Annals of Noninvasive Electrocardiology, vol. 6, no. 2, pp. 159–165, 2001. View at Publisher · View at Google Scholar · View at Scopus
  19. P. E. Dilaveris, E. J. Gialafos, S. K. Sideris et al., “Simple electrocardiographic markers for the prediction of paroxysmal idiopathic atrial fibrillation,” American Heart Journal, vol. 135, no. 5, pp. 733–738, 1998. View at Publisher · View at Google Scholar · View at Scopus
  20. K. U. Tufekci, R. Meuwissen, S. Genc, and K. Genc, “Inflammation in Parkinson’s disease,” Advances in Protein Chemistry and Structural Biology, vol. 88, pp. 69–132, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. Y. Guo, G. Y. Lip, and S. Apostolakis, “Inflammation in atrial fibrillation,” Journal of the American College of Cardiology, vol. 60, no. 22, pp. 2263–2270, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. J. A. Vilchez, V. Roldan, D. Hernandez-Romero, M. Valdes, G. Y. Lip, and F. Marin, “Biomarkers in atrial fibrillation: an overview,” International Journal of Clinical Practice, vol. 68, no. 4, pp. 434–443, 2014. View at Publisher · View at Google Scholar · View at Scopus
  23. J. Hermida, F. L. Lopez, R. Montes, K. Matsushita, B. C. Astor, and A. Alonso, “Usefulness of high-sensitivity C-reactive protein to predict mortality in patients with atrial fibrillation,” American Journal of Cardiology, vol. 109, no. 1, pp. 95–99, 2012. View at Publisher · View at Google Scholar · View at Scopus
  24. P. Jenner, “Oxidative stress in Parkinson’s disease,” Annals of Neurology, vol. 53, no. S3, pp. S26–S38, 2003. View at Publisher · View at Google Scholar · View at Scopus
  25. A. Samman Tahhan, P. B. Sandesara, S. S. Hayek et al., “Association between oxidative stress and atrial fibrillation,” Heart Rhythm, vol. 14, no. 12, pp. 1849–1855, 2017. View at Publisher · View at Google Scholar · View at Scopus
  26. T. Ziemssen and H. Reichmann, “Cardiovascular dysautonomia in de novo Parkinson’s disease,” Journal of the Neurological Sciences, vol. 289, no. 1-2, pp. 74–80, 2010. View at Publisher · View at Google Scholar · View at Scopus
  27. H. E. Hoff and L. A. Geddes, “Cholinergic factor in auricular fibrillation,” Journal of Applied Physiology, vol. 8, no. 2, pp. 177–192, 1955. View at Publisher · View at Google Scholar
  28. D. Yang, Y. Xi, T. Ai et al., “Vagal stimulation promotes atrial electrical remodeling induced by rapid atrial pacing in dogs: evidence of a noncholinergic effect,” Pacing and Clinical Electrophysiology, vol. 34, no. 9, pp. 1092–1099, 2011. View at Publisher · View at Google Scholar · View at Scopus
  29. P. S. Chen, L. S. Chen, M. C. Fishbein et al., “Role of the autonomic nervous system in atrial fibrillation: pathophysiology and therapy,” Circulation Research, vol. 114, no. 9, pp. 1500–1515, 2014. View at Publisher · View at Google Scholar · View at Scopus