Abstract
BACKGROUND: Heart rate variability (HRV) is defined as variations in R-R interval with time. Dysautonomia is common in patients with psychiatric disorders such as depression and anxiety. Using HRV analysis, recent studies showed that in anxiety disorders, the vagal cardiac function decreases, and sympathetic function increases. This study aimed at investigating citalopram effects on HRV.
METHODS: This before and after study was conducted in 25 generalized anxiety disorder (GAD) patients. GAD was diagnosed based on clinical interview according to diagnostic and statistical manual of mental disorders IV-Text revised (DSM-IV-TR) criteria using Structured Clinical Interview for DSM Disorders-I questionnaire. A cardiologist studied 24 h ambulatory monitoring of the electrocardiogram (Holter) on all patients before the treatment. A volume of 20 mg of citalopram was administered to the subjects on a daily basis. Then, they were studied by Holter monitoring again after 1-month of administration of citalopram.
RESULTS: The average age of participants was 35.32 ± 8.7. The average Holter monitoring time was 23.29 ± 1.14 h before treatment and 23.81 ± 0.68 after it. The 3 h low frequency/high frequency ratio was significantly different between 3 h segments of time before treatment (P < 0.001). This difference was even higher after treatment (P = 0.001). Data showed an increase in parasympathetic tone during sleep both before and after treatment.
CONCLUSION: These patients showed some impairments of HRV indices that did not improve by citalopram in future, the clinical importance of such disturbances should be evaluated in details with prolonged follow-up and greater sample size.
Keywords: Anxiety disorders, Heart Rate, Ambulatory electrocardiography
Date of submission:11 Aug 2014, Date of acceptance:3 Feb 2015
Introduction
Heart rate variability (HRV) is defined as variations in R-R interval with time. HRV is actually heartbeat variations from one beat to another, which is used for evaluation of sympathetic and vagus nerve effects on the Sinoatrial node, and consequently on the heartbeat.1,2
Apart from body mass index and elevated blood glucose or blood pressure, mental status, and related processes can significantly affect cardiac autonomic control.3 Stressors increase cardiac sympathetic control and decrease cardiac parasympathetic control, which consequently result in an increase in low frequency (LF) HRV and a decrease in high frequency (HF) HRV.4 Dysautonomia is common in patients with psychiatric disorders such as depression and anxiety. This is diagnosed via HRV.5 Anxiety disorders are highly associated with dysautonomia, which increases cardiovascular mortality. Patients with panic disorder or phobia are prone to cardiovascular diseases.6-8 Using HRV analysis, recent studies showed that in anxiety disorders, the vagal cardiac function decreases, and sympathetic function increases.9,10 Miu et al. showed a correlation between characteristic anxiety and dysautonomia using HRV analysis.11
Generalized anxiety disorder (GAD) is characterized by a pattern of frequent, persistent worry, and anxiety that is disproportionate to the impact of the events or circumstances on which the worry focuses.12 An acute episode of anxiety is defined as an increase in heart rate, decrease in HRV, and respiratory sinus arrhythmia. Anxiety disorders are highly associated with an increased risk of mortality and cardiovascular complications.13,14 One of the hypotheses raised on this issue is impaired regulation of cardiac autonomic control due to the correlation of the cardiac autonomic control system with cardiovascular diseases and mortality.15
The selective serotonin reuptake inhibitors (SSRIs) do have cardiac effects, the best demonstrated of those being a mild bradycardia observed during chronic treatment with fluoxetine, fluvoxamin, and paroxetine. Moreover, there are increasing the number of case reports on dysrhythmia and syncope associated with fluoxetine and another SSRIs treatment and overdose. A multicenter case-control study has shown that in the elderly the consumption of fluoxetine was significantly associated with an excess risk of syncope and orthostatic hypotension.16 This study aimed to investigate effects of citalopram on HRV.
Materials and Methods
This before and after study aimed to investigate the effects of citalopram on HRV in patients with GAD. GAD was diagnosed based on clinical interview, according to diagnostic and statistical manual of mental disorders IV - Text revised criteria using Structured Clinical Interview for DSM Disorders-I questionnaire.12 Due to shortage in studies that could provide valid data to estimate the sample size appropriately, we were not able to make a sample size calculation and started the study as a pilot exploratory design with minimum sample size (30 patients). Because of a higher prevalence of GAD in women, all of the participants were selected by using convenience sampling from female patients. Patients from Razi hospital outpatient clinic voluntarily entered the study after being diagnosed with GAD and considering inclusion and exclusion criteria from August to December in 2013. After explaining the safety of Holter monitoring to patients, providing them with the full information required for participation in interventional studies and letting them know that no cost will be imposed on them, subjects entered the study. In addition, all of them could withdraw from the study at any point. They were also ensured that all of their personal and medical information would remain confidential.
A cardiologist performed 24 h ambulatory monitoring of the electrocardiogram (Holter-Norav version 2.978) on all patients before the treatment. A volume of 20 mg of citalopram was administered to the subjects on a daily basis. Then, they were studied by Holter monitoring again after 1-month of administration of citalopram. Usually, the patients with GAD show a response to treatment in 4 weeks.
Techniques for measures calculating HRV in regard of equipment, condition, and preparation met the criteria mentioned in another article on HRV.17
Holter monitoring calculates two indicator categories HRV: Time domain and frequency domain parameters. Frequency domain analysis is measured in 2-5 min intervals. HRV indicators are presented in table 1. The 24 h monitoring of HRV are divided into 4 periods of 3 h recordings by the device (16-19, 20-23, 02-05 and 11-14). Each parameter of time domain and frequency domain measured again. Inclusion criteria were female gender, diagnosed with GAD and informed consent to participate in the study. Exclusion criteria were pregnant and lactating women, menopausal age, having an underlying heart disease, medical conditions affecting the heart rhythm including thyroid disease, diabetes mellitus, neuropathy, and tetraplegia concurrent use of drugs affecting heart rhythm and existence of atrial fibrillation; and significant rhythm disorders of heart like as frequent extra stimuli. Demographic variables that were assessed in the study were: Age, education level, and occupation. GAD diagnosis was given if at least three symptoms were present.
Descriptive methodologies (frequency, percentage, mean ± standard deviation) were used to perform statistical analysis. Kolmogorov-Smirnov test was used for normality assessment. In variables that had nonnormal distribution, we used non-parametric tests (Wilcoxon test) to perform comparisons between before and after HRV indices in variables with normal distribution, paired t-test was used. Used repeated measure analysis of variance for evaluates, the effect of 3 h segments of time (within subjects) and groups (between subjects). Mauchly's sphericity test was used to validate it. If sphericity is violated, the GreenhouseGeisser correction was used. All statistical analyses were conducted via SPSS (version 16, SPSS Inc., Chicago, IL, USA). Significance level was considered as P < 0.050. Trends for time domain measures in 24 hour electrocardiography monitoring are shown in figure 1.
Results
The average age of participants was 35.32 ± 8.7, with the minimum and maximum age of 25 and 59, respectively. Five patients dropped out of the study (because of unwillingness to do after treatment Holter monitoring), so 25 were studied. Four patients (16%) were single, and 21 of them (84%) were married. In addition, 6 (24%), 11 (44%), and 8 (32%) held undergraduate, graduated, and higher education degrees, respectively. Seven (28%) and 18 (72%) were employed and housekeepers, respectively. The average Holter monitoring time was 23.29 ± 1.14 h before treatment and 23.81 ± 0.68 after it table 2 shows the variation of HRV indices in 24 h.
The data showed that 7 individuals suffered from ventricular arrhythmia before the administration of citalopram. Moreover, 3, 2, and 2 patients suffered from premature ventricular contraction (PVC), bigeminy and trigeminy, respectively. In follow-up, Holter monitoring, which was done 1-month after the administration of citalopram, ventricular arrhythmia, PVC, bigeminy, and trigeminy were observed in 5, 2, 2, and 3 individuals, respectively. One of the three patients suffering from PVC prior to the treatment had no symptoms. The frequency of PVCs in the other 2 participants reduced from 818 to 618 in the first and from 1050 to 625 beats in the second patient, during 24 h, respectively. During the initial monitoring, supraventricular arrhythmia (SVT) [premature atrial contraction (PAC)] was observed in 4 cases and SVT in one case, while during the follow-up monitoring, PAC was observed in 3 cases. The frequency of PACs increased in one case after treatment, but none of the subjects had SVT.
The 3 h LF/HF ratio was significantly different between 3 h segments of time before treatment (P < 0.001). This difference was higher after treatment (P = 0.001) (Figure 2). Figure 2 shows a significant increase in parasympathetic tone during sleep both before and after treatment. Table 3 shows no significant different between variables before and after using citalopram.
In frequency domain analysis, LF/HF ratio variations, which is a sign of sympathetic and parasympathetic balance, were compared during 3-h periods before the treatment, and indicated a significant difference (P = 0.010). This index showed that sympathetic and parasympathetic balance differences during different periods of the day were different between time periods, but this difference was higher after treatment (P = 0.003). These findings mean that the flat and narrow difference of balance between sympathetic and parasympathetic activation becomes wider after therapy. While the sympathetic tone of patients decreased after treatment but the parasympathetic tone was not increased significantly after treatment. Sleep is the time that increasing in parasympathetic tone should be increased but both before and after treatment this increase was not high enough to improve the LF/HF ratio.
Discussion
HRV triangle is the estimate for total HR variability. This index was 36.52 before treatment, which increased to 37.55 after treatment. Although this difference was not different statistically, but the difference between time segments of HRV before treatment was significant (P = 0.010). This difference was not significant after treatment, which indicates some kind of autonomic stability after therapy with citalopram.
The standard deviation of NN intervals (SDNN) is an estimate for total HRV parameters. The total value of this parameter was 252 and the normal value 141. The average is better than normal but when comparing 3 h periods, the privilege of this parameter occurred during sleep. In other words, when the patient was awake this parameter was lower than normal. Furthermore, van Zyl et al. showed that SSRIs decrease heart rate and also cause a possible increase in SDNN.18
The disturbances in autonomic function were high when the patient was awake. It is notable that SDANN before treatment was very high when Holter monitoring started during evening and soon reached its average state during night time. This finding did not occur during follow-up. This finding may be related to the extra anxiety of patients who were attached to leads and device for the first time.
SDANN, which is a long-term estimate of HRV, may be a better estimation for HRV because it removes short-term effects of HRV components. This parameter was always lower in patients before and after treatment. Patients with anxiety disorders had autonomic disorders, which did not improve by gitolpram administration despite the improvement in their clinical status.
Root mean square of the successive differences is an estimate of short-term variation of autonomic balance. This parameter was always higher than normal value, which indicates a high level of fluctuation and variation in the autonomic drive of patients. The clinical importance of this finding should be evaluated further.
The value of LF and HF in the frequency domain analysis was lower than normal before and after therapy. The ratio of LF/HF was higher than normal values except during sleep. This finding is not a correct finding and is could not be interpreted as a sign of improvement in HRV. The values of LF and HF were less than normal. Their ratio can be normal but based on components of this ratio, the LF/HF ration cannot be interpreted as a sign of improvement in HRV. Actually, this finding shows our patients had blunted autonomic status before and after therapy for anxiety disorders.
The above mentioned results are comparable with other findings. McFarlane et al. showed that the HRV improvement indices in depressed patients with myocardial infarction, who received sertraline for 6 months was more than those of the control group, and this increase in HRV was equal to non-depressed patients.19 In a randomized clinical trial study, Brunoni et al. demonstrates that HRV did not change after treatment with 50 mg sertraline for 6 weeks, neither was an increased HRV observed in the clinical response.20
In their clinical trial study, Chappell et al. stated that duloxetine and escitalopram did not have a significant effect on HRV.21 Penttila et al. reported that the cardiac effect of citalopram on heart rate was the same as a placebo.22 In the Netherlands Study of Depression and Anxiety, Licht et al. showed that patients with anxiety had lower SDNN compared to the control group.23 Kemp et al. in a meta-analysis showed that tricyclic medication decreased HRV, although serotonin reuptake inhibitors, mirtazapine, and nefazodone had no significant impact on HRV despite patients' response to treatment.24 Although tricyclic antidepressants reduce HRV, at least one study has suggested that, in patients with panic disorder, treatment with the SSRI paroxetine normalizes HRV.25
Conclusion
Our patients showed some impairment of HRV indices that did not improve significantly after therapy with citalopram in future; the clinical importance of such disturbances should be evaluated in details with prolonged follow-up and greater sample size.
Limitation
· We had not a control group
· We studied only the female patients.
Acknowledgments
Great thanks to GAD patients that participated in the study. This study was supported by Tabriz University of Medical Sciences. This paper was prepared from the dissertation for receiving specialty degree in psychiatry, presented by Faramarz Zakeri in Tabriz University of Medical Sciences.
Conflict of Interests
Authors have no conflict of interests.
How to cite this article: Ranjbar F, Akbarzadeh F, Zakeri F, Farahbakhsh M, Nazari MA. Effects of citalopram on heart rate variability in women with generalized anxiety disorder. ARYA Atheroscler 2015; 11(3): ??-??.
References
1. Tulppo M, Huikuri HV. Origin and significance of heart rate variability. J Am Coll Cardiol 2004; 43(12): 2278-80.
2. Hoffman J. Grimm W. Muller H. et al, Heart rate variability and Baroreflex sensitivity in idiopathic dilated Cardiomyopathy. Heart 2000; 83(5): 531-38.
3. Huikuri HV, Makikallo TH. Heart rate variability in ischemic heart disease. Auton Neurosci 2001; 90(12): 95-101.
4. Berntson GG, Sarter M, Cacioppo JT. Anxiety and cardiovascular reactivity: the basal forebrain cholinergic link. Behav Brain Res 1998; 94(2): 22548.
5. Yang AC, Hong CJ, Tsai SJ. Heart Rate Variability in Psychiatric Disorders. Taiwanese Journal of Psychiatry (Taipei) Vol 24 No 2 2010; 24(2): 99-109.
6. Roose SP. Depression, anxiety, and the cardiovascular system: the psychiatrist's perspective. J Clin Psychiatry 2001; 62(Suppl 8): 19-22.
7. Kawachi I, Colditz GA, Ascherio A, Rimm EB, Giovannucci E, Stampfer MJ, et al. Prospective study of phobic anxiety and risk of coronary heart disease in men. Circulation 1994; 89(5): 1992-7.
8. Weissman MM, Markowitz JS, Ouellette R, Greenwald S, Kahn JP. Panic disorder and cardiovascular/cerebrovascular problems: results from a community survey. Am J Psychiatry 1990; 147(11): 1504-8.
9. Yeragani VK, Tancer M, Uhde T. Heart rate and QT interval variability: abnormal alpha-2 adrenergic function in patients with panic disorder. Psychiatry Res 2003; 121(2): 185-96.
10. Srinivasan K, Ashok MV, Vaz M, Yeragani VK. Decreased chaos of heart rate time series in children of patients with panic disorder. Depress Anxiety 2002; 15(4): 159-67.
11. Miu AC, Heilman RM, Miclea M. Reduced heart rate variability and vagal tone in anxiety: trait versus state, and the effects of autogenic training. Auton Neurosci 2009; 145(1-2): 99-103.
12. Sadock BJ, Kaplan HI, Sadock VA. Kaplan and Sadock's Synopsis of Psychiatry. Philadelphia, PA: Lippincott Williams & Wilkins; 2009.
13. Albert CM, Chae CU, Rexrode KM, Manson JE, Kawachi I. Phobic anxiety and risk of coronary heart disease and sudden cardiac death among women. Circulation 2005; 111(4): 480-7.
14. Dunner DL. Anxiety and panic: relationship to depression and cardiac disorders. Psychosomatics 1985; 26(11 Suppl): 18-22.
15. Fuller BF. The effects of stress-anxiety and coping styles on heart rate variability. Int J Psychophysiol 1992; 12(1): 81-6.
16. Pacher P, Kecskemeti V. Cardiovascular side effects of new antidepressants and antipsychotics: new drugs, old concerns? Curr Pharm Des 2004; 10(20): 2463-75.
17. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation 1996; 93(5): 1043-65.
18. van Zyl LT, Hasegawa T, Nagata K. Effects of antidepressant treatment on heart rate variability in major depression: a quantitative review. Biopsychosoc Med 2008; 2: 12.
19. McFarlane A, Kamath MV, Fallen EL, Malcolm V, Cherian F, Norman G. Effect of sertraline on the recovery rate of cardiac autonomic function in depressed patients after acute myocardial infarction. Am Heart J 2001; 142(4): 617-23.
20. Brunoni AR, Kemp AH, Dantas EM, Goulart AC, Nunes MA, Boggio PS, et al. Heart rate variability is a trait marker of major depressive disorder: evidence from the sertraline vs. electric current therapy to treat depression clinical study. Int J Neuropsychopharmacol 2013; 16(9): 1937-49.
21. Chappell JC, Kovacs R, Haber H, Wright R, Mitchell MI, Detke M, et al. Evaluation of the effects of duloxetine and escitalopram on 24-hour heart rate variability: a mechanistic study using heart rate variability as a pharmacodynamic measure. J Clin Psychopharmacol 2013; 33(2): 236-9.
22. Penttila J, Syvalahti E, Hinkka S, Kuusela T, Scheinin H. The effects of amitriptyline, citalopram and reboxetine on autonomic nervous system. A randomised placebo-controlled study on healthy volunteers. Psychopharmacology (Berl) 2001; 154(4): 343-9.
23. Licht CM, de Geus EJ, van DR, Penninx BW. Association between anxiety disorders and heart rate variability in The Netherlands Study of Depression and Anxiety (NESDA). Psychosom Med 2009; 71(5): 508-18.
24. Kemp AH, Quintana DS, Gray MA, Felmingham KL, Brown K, Gatt JM. Impact of depression and antidepressant treatment on heart rate variability: a review and meta-analysis. Biol Psychiatry 2010; 67(11): 1067-74.
25. Gorman JM, Sloan RP. Heart rate variability in depressive and anxiety disorders. Am Heart J 2000; 140(4 Suppl): 77-83.
Fatemeh Ranjbar(1), Fariborz Akbarzadeh(2), Faramarz Zakeri(3),
Mostafa Farahbakhsh(3), Mohammad Ali Nazari(4)
1- Associate Professor, Clinical Psychiatry Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
2- Associate Professor, Cardiovascular Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
3- Resident, Clinical Psychiatry Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
4- Assistant Professor, Department of Psychology, School of Psychology, University of Tabriz, Tabriz, Iran
Correspondence to: Fariborz Akbarzadeh, Email: [email protected]
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