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Physiologic and laboratory correlates of depression, anxiety, and poor sleep in liver cirrhosis

Abstract

Background

Studies have shown psychological distress in patients with cirrhosis, yet no studies have evaluated the laboratory and physiologic correlates of psychological symptoms in cirrhosis. This study therefore measured both biochemistry data and heart rate variability (HRV) analyses, and aimed to identify the physiologic correlates of depression, anxiety, and poor sleep in cirrhosis.

Methods

A total of 125 patients with cirrhosis and 55 healthy subjects were recruited. Each subject was assessed through routine biochemistry, 5-minutes ECG monitoring, and psychological ratings of depression, anxiety, and sleep. HRV analysis were used to evaluate autonomic functions. The relationship between depression, sleep, and physiologic correlates was assessed using a multiple regression analysis and stepwise method, controlling for age, duration of illness, and severity of cirrhosis.

Results

Reduced vagal-related HRV was found in patients with severe liver cirrhosis. Severity of cirrhosis measured by the Child-Pugh score was not correlated with depression or anxiety, and only had a weak correlation with poor sleep. The psychological distress in cirrhosis such as depression, anxiety, and insomnia were correlated specifically to increased levels of aspartate aminotransferase (AST), increased ratios of low frequency to high frequency power, or reduced nonlinear properties of HRV (α1 exponent of detrended fluctuation analysis).

Conclusions

Increased serum AST and abnormal autonomic nervous activities by HRV analysis were associated with psychological distress in cirrhosis. Because AST is an important mediator of inflammatory process, further research is needed to delineate the role of inflammation in the cirrhosis comorbid with depression.

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Background

Cirrhosis is a consequence of chronic liver disease commonly caused by alcoholism, viral hepatitis, autoimmune disorders, or other aetiologies. The prevalence of liver cirrhosis is high in most Asian countries where chronic hepatitis B or C are common [1]. Cirrhosis places a significant burden of psychological stress on affected individuals [2, 3]. In patients with liver cirrhosis, quality of life is considerably impaired and associated with mild to moderate depression and anxiety [4–6]. In a study of one hundred and fifty-six Italian patients with liver cirrhosis, Bianchi et al. [6] demonstrated that the global score of Psychological General Well-Being Index was severely reduced compared to the population norm and the score was significantly correlated with the severity of liver failure as assessed by the Child–Pugh (CP) score.

Despite the relationship between cirrhosis and distressed psychological states being well-documented in aforementioned studies, no study has evaluated the laboratory and physiologic correlates of depression, anxiety, or poor sleep commonly seen in patients with cirrhosis. Furthermore, these psychological manifestations are known risk factors for cardiovascular morbidity and are also associated with autonomic dysregulation. A body of research has emerged demonstrating that reduced vagal modulation or increased sympathetic activity are associated with anxiety [7–9], depression [10], and insomnia [11–13]; hence, the physiological and psychological stress of cirrhosis may be measured by heart rate variability (HRV), a non-invasive measure of the cardiac autonomic nervous system.

Functional limitations, altered cardiac autonomic activity, and psychological distress are known disorders in patients with liver cirrhosis, relating to increased morbidity and mortality. However, the inter-relationship between these morbidity remains unclear. The aim of this study was therefore to examine the influence of severity of cirrhosis on emotional parameters and heart rate variability (HRV) indices, as well as to determine whether emotional distress contributes to autonomic dysfunction in these patients. To this end, this study measured both the biochemical data and HRV indices, and identified the physiologic and laboratory correlates of depression, anxiety, and poor sleep in patients with liver cirrhosis.

Methods

Patients

The study sample consisted of 125 patients with liver cirrhosis (73 males, 52 females; mean age = 58.3 ± 11.6 years) and 55 healthy controls (29 males, 26 females; mean age = 58.0 ± 11.8 years) recruited from the outpatient clinics of the Section of Liver Cirrhosis, Shuguang Hospital, China. Inclusion criteria were a positive diagnosis of liver cirrhosis, documented by histology through a liver biopsy, or through clinical, sonographic and endoscopic evidence of portal hypertension and confirmed with laboratory data. Exclusion criteria were (1) a history of major mental illness such as schizophrenia, major depression, or bipolar disorder; (2) current use of psychotropic medication; (3) active infections; (4) hepatocellular carcinoma evidenced by sonographic focal liver lesion or α-fetoprotein exceeding ten times the upper limits of normal values. Of note: patients with viral hepatitis were neither actively treated with interferon at the time of investigation or during the previous year. The control subjects had neither history of mental illness nor liver diseases.

Demographic and clinical variables included age, gender, duration of illness, history of viral hepatitis and alcohol dependence, routine biochemistry, and the five items of the CP score (albumin and total bilirubin levels, prothrombin activity, presence and severity of ascites and encephalopathy) [14]. Of 125 patients, 43 were classified as CP class A, 58 were class B, and 24 were class C. The study protocol was in accordance with the guidelines for clinical research and was approved by the Institutional Review Board and the Ethical Review Committee of the hospital. Informed consent was obtained after all subjects had been fully informed of its purpose.

Psychological measurements

Depression severity was evaluated with the Hamilton Depression Rating Scale (HAMD, 24 items) [15], and anxiety was evaluated with the Hamilton Anxiety Scale (HAMA) [16]. Subjective sleep quality was assessed through the Pittsburgh Sleep Quality Index (PSQI). The ratings were administered by experienced clinical raters certified with high rates of inter-rater reliability and levels of procedural integrity. The self-reported depression scale, such as Beck Depression Inventory (BDI), [17] was not used in this study because the Chinese version of BDI was found to have low reliability in the Chinese population due to cultural bias on depression [18]. The objective rating of depression by HAMD and HAMA may be more appropriate than self-reported measure in our study population.

ECG monitoring

A customized ECG recording device was used to obtain a 5-minute ECG from each recruited subject [19]. ECG signals were recorded at a sampling rate of 256 Hz, and were automatically processed and analyzed by open source HRV algorithms [20]. All ECG monitoring took place during the daytime, and participants were asked to avoid smoking and to remain in a resting state while being monitored.

Analysis of heart rate variability

The standard HRV analysis has been well reviewed [21]. Time domain measures of HRV include the mean heart rate and standard deviation of the normal interbeat intervals (SDNN), and the root mean square successive difference between adjacent normal interbeat intervals (RMSSD). The SDNN assesses the overall variability of interbeat intervals. The RMSSD measures the short-term variation of interbeat intervals, which is primarily modulated by parasympathetic innervation [22]. Standard spectral HRV measures [21] include high-frequency power (HF; 0.15–0.40 Hz), low-frequency power (LF; 0.04–0.15 Hz), and very low-frequency power (VLF; 0.003–0.04 Hz). LF power is suggested to be modulated by both sympathetic and parasympathetic activities, whereas HF power is mainly modulated by parasympathetic activity [23, 24]. The LF/HF ratio is considered a measure of the shift of sympathovagal balance toward sympathetic activity [21, 25]. The physiological mechanism underlying VLF power is disputed but has been suggested to be mediated partly by the renin–angiotensin–aldosterone system or by parasympathetic modulation [26].

In addition, we incorporated a nonlinear HRV index: a Detrended Fluctuation Analysis (DFA) [27, 28]. DFA quantifies the presence of long-range (fractal) correlations inherent in physiologic signals and is therefore a complexity measure. The details of the DFA method is available at Physionet (http://physionet.org), a research resource for complex physiologic signals [20]. The root-mean-square fluctuation of integrated and detrended time series was measured at different observation windows and plotted against the size of the observation window on a log-log scale. The scaling exponent α is then derived from the slope of line fitting to the generated log-log plot. The short-term exponent α1 (4 to 11 heartbeats) and the long-term scaling exponents α2 (>11 heartbeats) were also calculated [27, 29]. Low-exponent values represent reduced fractal properties of heart rate dynamics and have been implicated in increased risks of fatal cardiac arrhythmia, increased mortality, or poor prognosis in cardiovascular diseases [30–33].

Statistical analysis

Statistical Package for the Social Sciences (SPSS version 15.0, Chicago, IL) software was used for the statistical analyses. The spectral HRV indices were log transformed to produce normalized distributions. Chi-squared tests were used to compare categorical variables. One-way Analysis Of Variance (ANOVA) was used to test for differences in demographical, clinical, and HRV measures among groups according to CP class, and post hoc Bonferroni tests were used for paired-group comparisons. Partial correlation controlling for age and duration of illness was used to test the association between CP scores and psychological distress as well as HRV indices. The relationship between depression, sleep, and physiologic correlates was assessed with multiple regression analyses using the backward selection method, controlling for age, duration of illness, and CP score. The physiologic correlates included biochemical data and HRV indices. We estimated the total sample size by the power analysis to be at least 118 by assuming power of 80%, 5% significance level, and a total of 10 predictors. The Variance Inflation Factor (VIF) was estimated for all physiologic correlates and a VIF value of 10 or greater was considered an indication of significant co-linearity. A p value of less than 0.05 (two-tailed) was required for all statistical comparisons.

Results

Patients

Table 1 shows the profiles of demographic, clinical and psychological ratings, as well as HRV data according to CP class. Three groups did not differ in age, gender and duration of illness. Regarding the aetiologies of liver cirrhosis, patients with CP class B and C had higher rate of alcoholism, compared to those with CP class A. The ANOVA test showed significant between-group differences in serum levels of albumin (p < 0.001), aspartate aminotransferase (AST; p < 0.001), total bilirubin (p < 0.001), and direct bilirubin (p < 0.001). As expected, post-hoc tests revealed that assessments of biochemistry were in accordance with the CP class.

Table 1 Demographic, clinical, psychological, and heart rate variability characteristics

Psychological ratings

Regarding psychological ratings (Table 1), significant between-group differences were found in PSQI (p = 0.007), and HAMD (p = 0.017). Patients with CP class C had significantly higher PSQI and HAMD ratings than patients with CP class A or B, suggesting poorer sleep and more severe depressed moods in cases of advanced liver cirrhosis.

HRV analysis

For HRV measures (Table 1), significant between-group differences were found in mean heart rate (p = 0.011), SDNN (p < 0.001), RMSSD (p = 0.035), LF power (p < 0.001), HF power (p = 0.044), and DFA α1 (p < 0.001). Patients with CP class C had a significantly decreased SDNN and LF, and decreased vagal-related HRV such as RMSSD and HF power, compared to controls and those with CP class A or B.

Correlation between CP score and psychological ratings / HRV analysis

Partial correlation analysis controlling for age and duration of illness indicated that CP scores were significantly correlated to levels of PSQI (r = 0.210; p = 0.021), and sub-components of PSQI, including subjective sleep quality (r = 0.217; p = 0.017) and sleep efficiency (r = 0.202; p = 0.027). CP scores were not correlated to HAMD and HAMA ratings. Regarding HRV indices, CP scores were correlated negatively to RMSSD (r = −0.231; p = 0.020), HF power (r = −0.345; p < 0.001), and positively to mean heart rate (r = 0.277; p = 0.005).

Correlation between physiologic measures and psychological ratings

Table 2 shows the physiologic correlates of depression, anxiety and sleep using multiple regression models with the stepwise method. PSQI was predicted only by AST serum levels (r = 0.224; p = 0.027). HAMD was predicted by LF/HF ratios (r = 0.222; p = 0.028), AST (r = 0.170; p = 0.045), and DFA α1 (r = −0.186; p = 0.041). HAMA was predicted by LF/HF ratios (r = 0.190; p = 0.039) and DFA α1 (r = −0.187; p = 0.041).

Table 2 Regression model of clinical and psychological assessment using laboratory and physiologic variables as predictors

Discussion

The key findings of this study were: (1) reduced vagal-related HRV was found in patients with CP class C; (2) severity of cirrhosis as measured by CP scores was not correlated to depression or anxiety, and was only weakly correlated with poor sleep; (3) the psychological distress in cirrhosis such as depression, anxiety, and insomnia were correlated specifically to increased levels of AST, increased LF/HF ratios, or reduced nonlinear properties of HRV – DFA α1. These results complemented prior research and identified the physiologic factors associated with the severity of psychological distress in patients with cirrhosis.

Findings of compromised psychological status related to the severity of cirrhosis were partially consistent with prior studies [4–6, 34, 35]. Although patients with CP class C showed significant psychological distress in sleep (PSQI) and depression (HAMD), we only found a weak correlation between CP scores and PSQI and its sub-component. HAMD and HAMA scores, indicative of depressed moods and anxiety, are not correlated with cirrhosis severity (CP score) in our study. The aetiology of depression in patients with liver cirrhosis remains largely unknown [36]. This finding did not support the study by Bianchi et al. that found a correlation between CP scores and Beck Depression ratings [6]. By contrast, we found that both PSQI and HAMD scores were correlated with levels of AST, a more direct measure of liver damage. This finding may provide a preliminary evidence of the link between liver damage and psychological distress and suggests that individual biochemical data may be more sensitive than CP scores in reflecting the psychological burden of liver cirrhosis.

The cause of differential association between AST/ALT markers and psychological ratings remains unknown. One possible explanation is that AST/ALT ratio are commonly elevated in cirrhosis patients and is a dependent marker of fibrosis stage and cirrhosis [37]. In this study, there were about 86% of patients who had AST/ALT ratio > 1 (data not shown). The elevation of AST may be a more sensitive marker to be correlated with psychological ratings. There are limited data regarding the association between the abnormal liver function and psychological distress in liver diseases. One prior study based on hepatitis C virus infected patients found that the physical function subscale in the quality of life assessment was correlated to serum AST level [38]. AST is an important mediator of the inflammatory processes, and increasing evidence has suggested that pathophysiology of depression is closely related to the proinflammatory cytokines [39], thus our findings of the association between AST and poor sleep and depression may be related to the chronic inflammation in cirrhosis, and warrants future investigation of the association between the degree of liver inflammation (e.g., necroinflammatory scores) and psychological ratings.

Previous studies have found that reduced HRV was correlated with increased severity of cirrhosis [40–43]. This study further reveals that both the severity of cirrhosis and psychological distress are correlated with changes in HRV indices. Although the causal relationship between these factors remains unclear, CP scores only had a weak correlation with poor sleep and no correlation with depression and anxiety ratings, thus suggesting that the effects of cirrhosis and psychological distress on HRV may be independent. Studies on myocardial infarctions have suggested that depression is an independent risk factor for poor cardiovascular outcomes [44–46]. Because cirrhosis has frequent cardiovascular complications [47], cirrhosis comorbid with depression may worsen cardiovascular-related morbidity and mortality and warrants future research. Of note, HAMD and HAMA scores were correlated positively with LF/HF ratios – a marker of sympathovagal balance – and negatively with DFA α1 – a nonlinear marker of vagal activity [29, 48]. DFA α1 has repeatedly demonstrated its ability in predicting cardiovascular mortality [48, 49], and may be instrumental in further investigations of using nonlinear HRV as a predictor of cardiovascular complications in cirrhosis.

There are several limitations in our present study. First, as the study design is cross-sectional, we cannot directly evaluate the long-term impacts of cirrhosis and psychological distress on autonomic function, and the interpretation of results is exploratory. Second, our study did not include a healthy control group; our primary interest was to investigate physiologic correlates of psychological distress within the population of cirrhosis patients. Third, the psychiatric ratings were used as a measure of psychological distress and were not for diagnostic purposes. The incidences of depression, anxiety, and poor sleep in cirrhosis patients might be addressed through psychiatric evaluation in a larger sample.

Conclusions

In summary, this study identifies the physiologic factors associated with psychological distress in cirrhosis patients, including increased AST and abnormal autonomic-nervous activities determined through HRV analyses. Further research is needed to evaluate the use of HRV as a non-invasive tool to assess cardiovascular outcome, and to delineate the role of inflammation in the cirrhosis comorbid with depression.

References

  1. Iwamura K: Liver cirrhosis in Asia and Africa. Z Gastroenterol. 1983, 21: 637-643.

    CAS  PubMed  Google Scholar 

  2. Singh N, Gayowski T, Wagener MM, Marino IR: Vulnerability to psychologic distress and depression in patients with end-stage liver disease due to hepatitis C virus. Clin Transplant. 1997, 11: 406-411.

    CAS  PubMed  Google Scholar 

  3. Rodrigue JR, Davis GL, Howard RJ, Brunson ME, Langham MR, Haiman S, Behen J: Psychological adjustment of liver transplant candidates. Clin Transplant. 1993, 7: 228-229.

    CAS  PubMed  Google Scholar 

  4. Kanwal F, Hays RD, Kilbourne AM, Dulai GS, Gralnek IM: Are physician-derived disease severity indices associated with health-related quality of life in patients with end-stage liver disease?. Am J Gastroenterol. 2004, 99: 1726-1732. 10.1111/j.1572-0241.2004.30300.x.

    Article  PubMed  Google Scholar 

  5. Younossi ZM, Boparai N, McCormick M, Price LL, Guyatt G: Assessment of utilities and health-related quality of life in patients with chronic liver disease. Am J Gastroenterol. 2001, 96: 579-583. 10.1111/j.1572-0241.2001.03537.x.

    Article  CAS  PubMed  Google Scholar 

  6. Bianchi G, Marchesini G, Nicolino F, Graziani R, Sgarbi D, Loguercio C, Abbiati R, Zoli M: Psychological status and depression in patients with liver cirrhosis. Dig Liver Dis. 2005, 37: 593-600. 10.1016/j.dld.2005.01.020.

    Article  CAS  PubMed  Google Scholar 

  7. Carney RM, Freedland KE, Stein PK: Anxiety, depression, and heart rate variability. Psychosom Med. 2000, 62: 84-87.

    Article  CAS  PubMed  Google Scholar 

  8. Bornas X, Llabres J, Noguera M, Lopez AM, Barcelo F, Tortella-Feliu M, Fullana MA: Looking at the heart of low and high heart rate variability fearful flyers: self-reported anxiety when confronting feared stimuli. Biol Psychol. 2005, 70: 182-187. 10.1016/j.biopsycho.2005.01.002.

    Article  PubMed  Google Scholar 

  9. Mellman TA, Knorr BR, Pigeon WR, Leiter JC, Akay M: Heart rate variability during sleep and the early development of posttraumatic stress disorder. Biol Psychiatry. 2004, 55: 953-956. 10.1016/j.biopsych.2003.12.018.

    Article  PubMed  Google Scholar 

  10. 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: 1067-1074. 10.1016/j.biopsych.2009.12.012.

    Article  CAS  PubMed  Google Scholar 

  11. Bonnet MH, Arand DL: Heart rate variability in insomniacs and matched normal sleepers. Psychosom Med. 1998, 60: 610-615.

    Article  CAS  PubMed  Google Scholar 

  12. Nilsson PM, Nilsson JA, Hedblad B, Berglund G: Sleep disturbance in association with elevated pulse rate for prediction of mortality–consequences of mental strain?. J Intern Med. 2001, 250: 521-529. 10.1046/j.1365-2796.2001.00913.x.

    Article  CAS  PubMed  Google Scholar 

  13. Yang AC, Tsai SJ, Yang CH, Kuo CH, Chen TJ, Hong CJ: Reduced physiologic complexity is associated with poor sleep in patients with major depression and primary insomnia. J Affect Disord. 2011, 131: 179-185. 10.1016/j.jad.2010.11.030.

    Article  PubMed  Google Scholar 

  14. Pugh RN, Murray-Lyon IM, Dawson JL, Pietroni MC, Williams R: Transection of the oesophagus for bleeding oesophageal varices. Br J Surg. 1973, 60: 646-649. 10.1002/bjs.1800600817.

    Article  CAS  PubMed  Google Scholar 

  15. Hamilton M: A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960, 23: 56-62. 10.1136/jnnp.23.1.56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Hamilton M: Diagnosis and rating of anxiety. Br J Psychiatry. 1969, 3: 76-79.

    Google Scholar 

  17. Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J: An inventory for measuring depression. Arch Gen Psychiatry. 1961, 4: 561-571. 10.1001/archpsyc.1961.01710120031004.

    Article  CAS  PubMed  Google Scholar 

  18. Zheng YP, Wei LA, Goa LG, Zhang GC, Wong CG: Applicability of the Chinese Beck Depression Inventory. Compr Psychiatry. 1988, 29: 484-489. 10.1016/0010-440X(88)90063-6.

    Article  CAS  PubMed  Google Scholar 

  19. Kuo TB, Lin T, Yang CC, Li CL, Chen CF, Chou P: Effect of aging on gender differences in neural control of heart rate. Am J Physiol. 1999, 277: H2233-2239.

    CAS  PubMed  Google Scholar 

  20. Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng CK, Stanley HE: PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000, 101: E215-220. 10.1161/01.CIR.101.23.e215.

    Article  CAS  PubMed  Google Scholar 

  21. Task-Force: Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology: Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation. 1996, 93: 1043-1065. 10.1161/01.CIR.93.5.1043.

    Article  Google Scholar 

  22. Goldberger JJ, Challapalli S, Tung R, Parker MA, Kadish AH: Relationship of heart rate variability to parasympathetic effect. Circulation. 2001, 103: 1977-1983. 10.1161/01.CIR.103.15.1977.

    Article  CAS  PubMed  Google Scholar 

  23. Katona PG, Jih F: Respiratory sinus arrhythmia: noninvasive measure of parasympathetic cardiac control. J Appl Physiol. 1975, 39: 801-805.

    CAS  PubMed  Google Scholar 

  24. Pomeranz B, Macaulay RJ, Caudill MA, Kutz I, Adam D, Gordon D, Kilborn KM, Barger AC, Shannon DC, Cohen RJ, et al: Assessment of autonomic function in humans by heart rate spectral analysis. Am J Physiol. 1985, 248: H151-153.

    CAS  PubMed  Google Scholar 

  25. Malliani A, Lombardi F, Pagani M: Power spectrum analysis of heart rate variability: a tool to explore neural regulatory mechanisms. Br Heart J. 1994, 71: 1-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Taylor JA, Carr DL, Myers CW, Eckberg DL: Mechanisms underlying very-low-frequency RR-interval oscillations in humans. Circulation. 1998, 98: 547-555. 10.1161/01.CIR.98.6.547.

    Article  CAS  PubMed  Google Scholar 

  27. Peng CK, Havlin S, Stanley HE, Goldberger AL: Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos. 1995, 5: 82-87. 10.1063/1.166141.

    Article  CAS  PubMed  Google Scholar 

  28. Peng CK, Buldyrev SV, Goldberger AL, Havlin S, Sciortino F, Simons M, Stanley HE: Long-range correlations in nucleotide sequences. Nature. 1992, 356: 168-170. 10.1038/356168a0.

    Article  CAS  PubMed  Google Scholar 

  29. Makikallio TH, Seppanen T, Airaksinen KE, Koistinen J, Tulppo MP, Peng CK, Goldberger AL, Huikuri HV: Dynamic analysis of heart rate may predict subsequent ventricular tachycardia after myocardial infarction. Am J Cardiol. 1997, 80: 779-783. 10.1016/S0002-9149(97)00516-X.

    Article  CAS  PubMed  Google Scholar 

  30. Ho KK, Moody GB, Peng CK, Mietus JE, Larson MG, Levy D, Goldberger AL: Predicting survival in heart failure case and control subjects by use of fully automated methods for deriving nonlinear and conventional indices of heart rate dynamics. Circulation. 1997, 96: 842-848. 10.1161/01.CIR.96.3.842.

    Article  CAS  PubMed  Google Scholar 

  31. Tapanainen JM, Thomsen PE, Kober L, Torp-Pedersen C, Makikallio TH, Still AM, Lindgren KS, Huikuri HV: Fractal analysis of heart rate variability and mortality after an acute myocardial infarction. Am J Cardiol. 2002, 90: 347-352. 10.1016/S0002-9149(02)02488-8.

    Article  PubMed  Google Scholar 

  32. Tibby SM, Frndova H, Durward A, Cox PN: Novel method to quantify loss of heart rate variability in pediatric multiple organ failure. Crit Care Med. 2003, 31: 2059-2067. 10.1097/01.CCM.0000069539.65980.58.

    Article  PubMed  Google Scholar 

  33. Huikuri HV, Makikallio TH, Peng CK, Goldberger AL, Hintze U, Moller M: Fractal correlation properties of R-R interval dynamics and mortality in patients with depressed left ventricular function after an acute myocardial infarction. Circulation. 2000, 101: 47-53. 10.1161/01.CIR.101.1.47.

    Article  CAS  PubMed  Google Scholar 

  34. Hauser W, Holtmann G, Grandt D: Determinants of health-related quality of life in patients with chronic liver diseases. Clin Gastroenterol Hepatol. 2004, 2: 157-163. 10.1016/S1542-3565(03)00315-X.

    Article  PubMed  Google Scholar 

  35. Kim SH, Oh EG, Lee WH: Symptom experience, psychological distress, and quality of life in Korean patients with liver cirrhosis: a cross-sectional survey. Int J Nurs Stud. 2006, 43: 1047-1056. 10.1016/j.ijnurstu.2005.11.012.

    Article  PubMed  Google Scholar 

  36. Orru MG, Pariante CM: Depression and liver diseases. Dig Liver Dis. 2005, 37: 564-565. 10.1016/j.dld.2005.04.003.

    Article  PubMed  Google Scholar 

  37. Sheth SG, Flamm SL, Gordon FD, Chopra S: AST/ALT ratio predicts cirrhosis in patients with chronic hepatitis C virus infection. Am J Gastroenterol. 1998, 93: 44-48. 10.1111/j.1572-0241.1998.044_c.x.

    Article  CAS  PubMed  Google Scholar 

  38. Afsar B, Ozdemir NF, Sezer S, Haberal M: Quality of life is not related with liver disease severity but with anemia, malnutrition, and depression in HCV-infected hemodialysis patients. Hemodial Int. 2009, 13: 62-71. 10.1111/j.1542-4758.2009.00329.x.

    Article  PubMed  Google Scholar 

  39. Raison CL, Capuron L, Miller AH: Cytokines sing the blues: inflammation and the pathogenesis of depression. Trends Immunol. 2006, 27: 24-31. 10.1016/j.it.2005.11.006.

    Article  CAS  PubMed  Google Scholar 

  40. Ates F, Topal E, Kosar F, Karincaoglu M, Yildirim B, Aksoy Y, Aladag M, Harputluoglu MM, Demirel U, Alan H, et al: The relationship of heart rate variability with severity and prognosis of cirrhosis. Dig Dis Sci. 2006, 51: 1614-1618. 10.1007/s10620-006-9073-9.

    Article  PubMed  Google Scholar 

  41. Frokjaer VG, Strauss GI, Mehlsen J, Knudsen GM, Rasmussen V, Larsen FS: Autonomic dysfunction and impaired cerebral autoregulation in cirrhosis. Clin Auton Res. 2006, 16: 208-216. 10.1007/s10286-006-0337-4.

    Article  PubMed  Google Scholar 

  42. Mani AR, Montagnese S, Jackson CD, Jenkins CW, Head IM, Stephens RC, Moore KP, Morgan MY: Decreased heart rate variability in patients with cirrhosis relates to the presence and degree of hepatic encephalopathy. Am J Physiol Gastrointest Liver Physiol. 2009, 296: G330-338.

    Article  CAS  PubMed  Google Scholar 

  43. Newton JL, Allen J, Kerr S, Jones DE: Reduced heart rate variability and baroreflex sensitivity in primary biliary cirrhosis. Liver Int. 2006, 26: 197-202. 10.1111/j.1478-3231.2005.01214.x.

    Article  PubMed  Google Scholar 

  44. Barefoot JC, Schroll M: Symptoms of depression, acute myocardial infarction, and total mortality in a community sample. Circulation. 1996, 93: 1976-1980. 10.1161/01.CIR.93.11.1976.

    Article  CAS  PubMed  Google Scholar 

  45. Carney RM, Blumenthal JA, Stein PK, Watkins L, Catellier D, Berkman LF, Czajkowski SM, O'Connor C, Stone PH, Freedland KE: Depression, heart rate variability, and acute myocardial infarction. Circulation. 2001, 104: 2024-2028. 10.1161/hc4201.097834.

    Article  CAS  PubMed  Google Scholar 

  46. Carney RM, Freedland KE, Smith L, Lustman PJ, Jaffe AS: Relation of depression and mortality after myocardial infarction in women. Circulation. 1991, 84: 1876-1877.

    CAS  PubMed  Google Scholar 

  47. Moller S, Henriksen JH: Cardiovascular complications of cirrhosis. Gut. 2008, 57: 268-278. 10.1136/gut.2006.112177.

    Article  CAS  PubMed  Google Scholar 

  48. Makikallio TH, Barthel P, Schneider R, Bauer A, Tapanainen JM, Tulppo MP, Schmidt G, Huikuri HV: Prediction of sudden cardiac death after acute myocardial infarction: role of Holter monitoring in the modern treatment era. Eur Heart J. 2005, 26: 762-769. 10.1093/eurheartj/ehi188.

    Article  PubMed  Google Scholar 

  49. Kop WJ, Stein PK, Tracy RP, Barzilay JI, Schulz R, Gottdiener JS: Autonomic nervous system dysfunction and inflammation contribute to the increased cardiovascular mortality risk associated with depression. Psychosom Med. 2010, 72: 626-635. 10.1097/PSY.0b013e3181eadd2b.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported in part by National Science Council (NSC) of Taiwan (NSC 100-2911-I-008-001). The authors wish to thank Jing Zhang for excellent technical assistance.

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Correspondence to Lie-Ming Xu.

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Authors’ contributions

FYK designed the clinical experiment, carried out the studies and drafted the manuscript. ACY and SJT performed heart rate variability and statistical analysis, and helped to draft the manuscript. YZ and LMX designed the clinical experiment, contributed study sample, and supervised the study. All authors read and approved the final manuscript.

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Ko, FY., Yang, A.C., Tsai, SJ. et al. Physiologic and laboratory correlates of depression, anxiety, and poor sleep in liver cirrhosis. BMC Gastroenterol 13, 18 (2013). https://doi.org/10.1186/1471-230X-13-18

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