The Prognostic Correlation of Heart rate variability and body weight status in liver cancer patients

The Prognostic Correlation of Heart rate variability and body weight status in liver cancer patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Prognostic Correlation of Heart rate variability and body weight status in liver cancer patients Qingqing Huang, Xiping Liang, Changyan Feng, Vishnu Prasad Adhikari, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4509982/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Weight status play an important role in the evolution and prognosis of cancer patients; however alterations of autonomic nervous system (ANS) caused by cancer may be the associated symptoms in cancer-related weight change. Objective The aim of this study is to identify the influence of weight status on ANS and determine whether ANS can be used as an index for early detection and prediction of weight changes in liver cancer patients with HRV. Methods We conducted a retrospective analysis of clinical data for newly diagnosed liver cancer from 2017 to 2022 in China. The authors conducted clinical and ECG data of liver cancer with special emphasis on advances ECG and the BMI aspect. Results Both BMI and KPS were lower in the liver cancer group compared to benign tumor patients and healthy controls (p ≤ 0.001). Liver cancer patients were more likely to have a history of diabetes (p = 0.005) and hepatitis B virus infection (p ≤ 0.001) compared to non-liver cancer patients. Moreover, the HRV indices and variations remained low in liver cancer patients Additionally, the mean average levels of SDNN and VLF bands in liver cancer remained significantly low (p ≤ 0.005). The results reveal that a lower BMI, lower VLF index, together with history of HBV infection positively correlated in liver cancer patients. The study reveals that HRV indices is associated with BMI in liver cancer patients with lesser body weight. As predicted, the LF and LF/VLF scores had correlation with lower BMI in the liver cancer patients (p < 0.05). Conclusion In liver cancer patients, decreased HRV was associated with a lower BMI independent of other con-founders. The role of HRV as a potential index for predicting cancer-related weight loss and improving the survival time of liver cancer patients are promising but require further validation in future studies. autonomous nervous system liver cancer sympathetic activity weight loss body mass index Figures Figure 1 Introduction An abnormal body mass index (BMI) has an important role in the evolution and prognosis of cancer. Over weight is a well-known co-factor for the development of hepatocellular carcinoma (HCC). In a Taiwanese study, obesity was associated with a two-fold risk of HCC in patients without viral infections, and four-fold risk in anti-hepatitis C virus (HCV)-positive subjects[ 1 ]. A meta-analysis also showed that overweight patients had a 19% increased risk of liver cancer. Obesity was associated with 87% increased risk of liver cancer[ 2 ]. Effective measures to reduce excess weight may decrease EBW-associated HCC risk[ 3 ].Excess weight also predicts prognosis in patients with liver cancer. Compared with normal BMI patients, liver cancer patients with overweight/obesity is associated significantly with increased risk of mortality (9% and 66%, respectively)[ 2 ]. However, patients with rapid weight loss usually predicts a poor prognosis. Weight loss is also one of the most common and torturous symptoms reported by cancer patients and survivors. Weight loss during primary therapy is a strong predictor for prognostic and Overall Survival (OS) in epithelial ovarian carcinoma patients[ 4 ]. And the relative risk for death increased by 7% for each 5% decrease in weight, independent of other confounders[ 4 ]. Weight loss affects the susceptibility to adverse effects and response to treatment leading to a poor prognosis and QoL in cancer patients[ 5 , 6 , 7 , 8 , 9 ]. Given the higher prevalence and worse impact of weight changes in cancer patients, early detection and prevention of weight changes are of great significance to the prognosis of cancer patients. An indicator that can predict weight changes is particularly important. One possible hypothesis is the autonomous nervous system (ANS). The ANS is a part of the peripheral nervous system and it plays an important role in cancer patients and the associated symptoms of cancer-related weight changes[ 10 ]. However, the possible indicator predicting weight changes in liver cancer has not yet been determined. Heart rate variability (HRV) is a systemic marker of ANS activity. It significantly and independently predicts cancer prognosis[ 11 ]. Study revealed that higher HRV predicts lower levels of tumor marker independent confounders[ 12 ]. Indeed, HRV ensures liver sensing of glucose, lipids, hormones, and owing to its well-known implication in liver pathology of tumor metabolism[ 13 ].Additionally, studies have reported that HRV responds to various aspects of the diet, raising the possibility that HRV offers a convenient measure of potential benefit[ 14 ]. HRV has the potential to become a widely used biomarker for the prognosis of cancer patients with weight changes. In this study, we chose liver cancer and non-liver cancer patients as the focus to examine the relationship of HRV and weight status. Furthermore, we explored the possibility of HRV in predicting weight changes in HCC patients. Methods The retrospective study was conducted at Chongqing University Cancer Hospital. The participants enrolled in the study were diagnosed with liver cancer or benign liver tumors with intact ECG data from August 2017- July 2021. Approval for these studies was obtained from the Academic Medical Center Institutional Review Board (CZLS2022022-A). Informed consent was provided according to the Declaration of Helsinki. The control group comprised of healthy people undertaking physical examination in the Physical Examination Center of Chongqing University Cancer. All participants were ≥ 18 years of age. Participant information, such as general condition, racial/ethnicity, marital status, education, employment, income, smoking history, HRV indicators, demographics, cancer history, pain scores, and QoL scores were collected from the hospital electronic recording system and electrocardiogram software. Body weight and height were measured at the time of admission to hospital by nurses, with the participants wearing light clothing and bare feet. The formula of BMI is as follows: BMI (kg/m 2 ) = weight (kg) / height (m 2 ). According to World Health Organization (WHO) guidelines, BMI values were divided into four categories, as follows: underweight (< 18.5 kg/m 2 ); normal weight (18.5 ~ 24.9 kg/m 2 ); overweight (25 ~ 29.9 kg/m 2 ); obese (≥ 30 kg/m 2 ). Obese includes Level 1–3 obesity status. All patients reported their average levels of pain and the most severe pain in the past week on a 11-point pain score (0, representing no pain, to 10 representing “pain as bad as you can imagine” or “worst pain imaginable”). Participants also reported the number of days they felt pain in the past week. Higher scores indicated worse pain. Performance status (i.e., physical activity) was assessed by the clinician. The Karnofsky Performance Scale (KPS) is usually used to measure the ability of cancer patients to perform ordinary tasks, the KPS covers 11 stages from 100 (normal health) to 0 (death)[ 15 ]. Patients having ability to carry on normal activity and work with no need for special care had a KPS score between 100 and 80. A KPS score between 70 and 50 are unable to work, but live at home and care for most personal needs with a varying amount of assistance[ 15 ]. HRV analysis during a 24-hECG recording was performed to assess ANS activity. A low RMSSD (Root mean square of the successive differences) at rest is a proposed index of poor autonomous regulation[ 16 ]. RMSSD and the percentage of adjacent RR intervals with a duration difference > 50ms (pNN50) are frequently used as an index of the parasympathetic system[ 17 ]. The frequency domain analysis of HRV were divided into multiple frequency bands. Total power in the frequency range was divided into low frequency (LF) (0.04–0.15 Hz), very low frequency (VLF), and high frequency (HF) (0.15–0.4 Hz); the LF/HF rate represents the sympathovagal balance[ 17 , 18 ]. Except for those who had died and lost contact, all patients were informed by telephone and informed consent. The patient's privacy information is well protected in this study. There is no possibility of any invasion of patient privacy or endanger to their health. Statistical Analyses SPSS (version23.0) was used for statistical analyses. Data were summarized using frequency counts and descriptive statistics. Intergroup comparisons were performed by one-way analysis of variance, t-tests, chi-square tests, single factor variance analysis, or multiple logistic regression analysis, as indicated. Measurement variables are expressed as the mean ± standard error of the mean. A p < 0.05 was considered statistically significant. Results 1.Participant characteristics During the investigation period, a total of 357 patients visited the Affiliated Oncology Hospital of Chongqing University complaining of liver tumor. Among them, 280 patients were diagnosed with liver cancer. Ten patients opted not to receive any treatment. A total of 77 unselected patients with de liver benign tumor patients and 77 healthy controls would like to take part in this study. 24-hECG recording were collected at the time of initial presentation. The demographic and complication characteristics of the patients’ data are summarized in Table 1 . Table 1 Demographic and clinical characteristics of participants Variable Liver cancer (n = 270) Liver benign tumor(n = 77) Healthy cohort control group (n = 77) p value Age(y), M (SD) 67.24 ± 9.084 64.43 ± 11.432 65.81 ± 7.352 0.157 BMI, M (SD) 22.2461 ± 3.66 23.4571 ± 3.16 24.3829 ± 3.481 ≤ 0.001 KPS score, M (SD) 82.69 ± 8.74 83.4 ± 8.15 89.30 ± 7.036 ≤ 0.001 Hypertension (n, %) 43(26.9%) 18(38.3%) 21(36.8%) 0.194 Diabetes (n, %) 37(23.3%) 4(8.5%) 4(7%) 0.005 Heart disease (n, %) 14(8.8%) 6(12.8%) 6(10.5%) 0.711 HBV (n, %) 93(58.1%) 7(14.9%) 5(8.8%) ≤ 0.001 Smoking (n, %) 106(66.3%) 41(87.2%) 42(73.7%) 0.018 Alcohol consumption (n, %) 125(78.1%) 43(91.5%) 50(87.7%) 0.054 Marital Status Married (%) 155(96.9%) 40(85.1%) 57(100%) 0.001 Gender, Female (n, %) 42(26.3%) 27(57.4%) 28(49.1%) ≤ 0.001 Atrial fibrillation (n, %) 8(5%) 1(2.1%) 0(0%) 0.165 Racial (n, %) 159(99.4%) 47(100%) 56(98.2%) 1 Note, HBV: Hepatitis B Virus Both BMI and KPS were lower than benign tumor patients and healthy controls (p ≤ 0.001). The proportion of female patients was also significantly lower in the liver cancer group compared to benign tumor patients and healthy controls (p ≤ 0.001). Majority participants were married in the three groups. The mean age was 66.43 ± 9.25 years for the entire study cohort; No statistical difference was observed between the 3 groups (p>0.05). Compared to non-liver cancer patients, liver cancer patients were more likely to have a history of diabetes (p = 0.005) and hepatitis B virus infection (p ≤ 0.001). Meanwhile, the probability of cigarette smoking and alcohol consumption was lower in liver cancer patients; However, only the cigarette smoking was significantly different among 3 groups(p = 0.018). 2. HRV and liver cancer In order to know the ANS activity in liver cancer, we compared the difference of HRV by 24-hECG record. The majority of HRV indices in liver cancer patients were lower. However, we found that the mean average levels of SDNN and VLF bands in liver cancer were significantly lower than the other 2 groups (p < 0.05). The total variation of HRV in liver cancer patients were decreased compared to the healthy controls and patients with benign liver tumors. The HRV measures for the three groups are presented in Table 2 and Fig. 1, A. Table 2 Means of HRV variables compared between liver cancers and the other 2 groups Variable Liver cancer(n = 270) Liver benign tumor (n = 77) p value 95%CI Healthy cohort control group (n = 77) p value 95%CI Compared with liver cancer SDNN,M (SD) 101.18 ± 37.30 120.98 ± 36.59 0.003 -33.98~-5.61 117.26 ± 28.59 0.001 -29.27~-2.89 SDNN index ,M (SD) 45.38 ± 31.01 52.80 ± 42.26 0.457 -19.88 ~ 5.04 48.86 ± 14.42 1 -14.87 ~ 7.91 RMSSD,M (SD) 27.77 ± 18.04 27.79 ± 17.35 1 -7.11 ~ 7.07 26.67 ± 10.09 0.922 -3.61 ~ 5.81 PNN50,M (SD) 7.72 ± 13.22 6.17 ± 6.78 1 -2.83 ~ 5.83 5.82 ± 4.98 0.79 -2.18 ~ 5.97 Triangular index, M (SD) 21.54 ± 7.59 23.87 ± 7.80 0.203 -5.37 ~ 0.37 26.47 ± 7 ≤ 0.001 -7.72~-2.14 HF,M (SD) 214.17 ± 451.89 218.77 ± 420.17 1 -176.73 ~ 167.53 179.42 ± 253.49 1 -118.55~-188.06 LF,M (SD) 258.47 ± 287.75 380.79 ± 584.84 0.47 -350.33 ~ 105.69 307.77 ± 218.35 0.46 -138.95 ~ 40.35 VLF,M (SD) 647.10 ± 440.90 914.15 ± 769.22 0.007 -475.31~-58.79 893.18 ± 387.37 0.005 -433.28~-58.88 LF/HF,M (SD) 2.21 ± 1.43 2.43 ± 1.39 1 -0.8 ~ 0.37 2.25 ± 1.27 1 -0.56 ~ 0.48 Heart rate,M (SD) 75.83 ± 12.13 74.65 ± 10.55 0.89 -3.27 ~ 5.63 71.37 ± 8.23 0.008 0.96 ~ 7.97 Note, HF: high frequency indices; LF: low frequency indices; VLF : Very low frequency indices; NRS :Numerical rating scale;RMSSD: Root mean square of the successive differences༛SDNN: Standard deviation of the NN (R-R) intervals༛NN50: The number of pairs of successive NN (R-R) intervals that differ by more than 50 ms༛PNN50: The proportion of NN50 divided by the total number of NN (R-R) interval We further analyzed the relationship of HRV and demographics, treatment-related history, and other potential confounders in liver cancer patients using multiple logistic regression analysis (Table 3 ). In agreement with previous research findings, the results showed that a lower BMI, lower VLF index, and history of hepatitis B virus infection were positively correlated with liver cancer patients. While age, history of diabetes, numerical rating scale (NRS), and PNN50 were negatively correlated with liver cancer patients. In liver cancer patients, BMI, the VLF indices and the total variation of HRV were decreased; and the correlation of reduced variation of HRV, VLF indices and BMI with liver cancer patients still exists, unaffected by confounders, such as diabetes and age (shown in Table 2 ). Table 3 Multiple Logistic Regression Analysis of liver cancer compared to benign liver tumor Variable p value OR 95% CI for OR Age 0.019 0.94 0.89–0.99 Diabetes 0.001 0.062 0.01–0.30 BMI 0.027 1.16 1.02–1.32 History of HBV ≤ 0.001 24.95 7.55–82.43 NRS 0.001 0.557 0.40–0.78 PNN50 0.044 0.926 0.86–0.998 VLF 0.017 1.001 1.00-1.003 Note, HBV: Hepatitis B Virus; NRS: Numerical rating scale; PNN50: The proportion of NN50 divided by the total number of NN (R-R) intervals; VLF: Very low frequency indices 3. Associations between HRV and BMI The results above showed that BMI and HRV indices were positively correlated with liver cancer patients. To further determine whether the HRV changes in liver cancer patients are correlated with BMI status, we designed the following analysis. BMI was divided into low weight, normal weight, overweight, obesity, and morbidly obese groups in accordance with WHO criteria. The morbidly obese patients were included in the obesity group due to their lesser counts. The relationship of HRV and BMI status in liver cancer patients is presented in Table 4 and Fig. 1, B. Table 4 Associations between BMI category and HRV score in liver cancer group. Variable Normal BMI (n =154) Underweight (n = 48) p value 95%CI Overweight (n =56) p value 95%CI Obese (n =12) p value 95%CI Compared with normal BMI SDNN, M (SD) 98.37 ± 30.64 92.91 ± 27.09 0.953 -23.31-12.39 115.97 ± 58.16 0.537 -48.45-13.26 103.5 ± 29.96 1 -92.46-82.21 SDNN index, M (SD) 44.51 ± 25.13 35.53 ± 13.26 0.106 -1.11-19.09 53.63 ± 51.05 0.925 -36.11-17.86 45.5 ± 15.86 1 -44.26-42.28 RMSSD, M (SD) 27.27 ± 17.37 22.7 ± 8.53 0.346 -2.12-11.28 30.97 ± 21.71 0.952 -15.64-8.26 32 ± 26.32 1 -84.03-74.58 PNN50, M (SD) 7.25 ± 12.87 4.17 ± 4.24 0.263 -1.08-7.24 10 ± 15.46 0.943 -11.3-5.81 10 ± 14.45 1 -45.42-39.93- Triangular index, M (SD) 21.26 ± 7.32 21.35 ± 7.91 1 -4.8-4.64 22.57 ± 8.2 1 -5.55-2.55 23.25 ± 10.63 1 -12.41-8.44 HF, M (SD) 191.88 ± 389.36 90.79 ± 67.4 0.101 -11.26-213.43 309.69 ± 664.66 0.937 -479.83-244.21 390.08 ± 605.95 0.993 -2024.28-1627.88 LF, M (SD) 261.21 ± 257.78 146.03 ± 135.64 0.023 10.60-219.74 302.42 ± 412.95 0.997 -267.22-184.79 348.1 ± 292.45 0.996 -949.72-775.93 VLF, M (SD) 687.79 ± 469.58 524.32 ± 366.57 0.677 -110.6-437.53 613.60 ± 398.57 1 -175.91-324.28 686.3 ± 419.57 1 -601.43-604.4 LF/HF, M (SD) 2.40 ± 1.38 1.68 ± 0.85 0.015 0.098–1.34 2.02 ± 1.79 0.876 -0.62-1.38 2.48 ± 1.94 1 -5.88-5.73 Heart rate, M (SD) 75.51 ± 12.77 77.22 ± 10.54 0.985 -8.74-5.33 76.37 ± 11.94 1 -7.76-6.05 70.75 ± 6.8 0.838 -13.11-26.63 Note, HF: high frequency indices; LF: low frequency indices; VLF : Very low frequency indices; NRS :Numerical rating scale;RMSSD: Root mean square of the successive differences༛SDNN: Standard deviation of the NN (R-R) intervals༛NN50: The number of pairs of successive NN (R-R) intervals that differ by more than 50 ms༛PNN50: The proportion of NN50 divided by the total number of NN (R-R) interval In comparison to the HRV index in the underweight group decreased significantly compared to the patients with normal weight. Meanwhile, it was not statistically significant for the patients with overweight and obesity, (Table 4 ). Significance between HRV indices values and BMI in liver cancer patients was only reported in the low weight group patients. It seems that the HRV indexes maybe used to predict weight loss in liver cancer patients. As predicted, the LF and LF/VLF scores were correlated with low BMI in the liver cancer patients. The correlation was independent of several other confounders, such as age and history of diabetes. This finding further showed that the decreased ANS activity in liver cancer patients was mainly related to low body weight, with the difference being statistically significant. 4. Associations between HRV and pain Pain is related with ANS and body weight in cancer patients[ 12 ]. The incidence of pain is relatively high (64.81%) in liver cancer patients; Therefore, we further analyzed the relationship between pain and HRV in liver cancer patients. The liver cancer patients were divided into pain and no-pain groups; the results are shown in Table 5 . No difference was demonstrated between the two groups, with the exception of cigarette smoking and gender. The proportion of patients who smoked cigarettes in the pain group was significantly higher than the no-pain group. No significant difference was found in HRV indices and BMI between the two groups. There was no relationship between pain and HRV changes in liver cancer patients. Table 5 Associations between HRV and pain in liver cancer patients. variable Non-Cancer- pain(n = 175) Cancer-related pain(n = 95) p value Age(y), M (SD) 68.58 ± 8.89 66.72 ± 9.15 0.242 BMI, M (SD) 22.25 ± 3.71 22.25 ± 3.66 0.998 KPS score, M (SD) 84.22 ± 8.39 82.09 ± 8.84 0.158 Hypertension (n, %) 13(30.2%) 30(69.8%) 0.697 Diabetes (n, %) 15(40.5%) 22(59.5%) 0.059 Heart disease (n, %) 6(42.9%) 8(57.1%) 0.165 HBV (n, %) 31(32.3%) 65(67.7%) 0.209 Smoking (n, %) 22(40.7%) 32(59.3%) 0.015 Alcohol consumption (n, %) 12(34.3%) 23(65.7%) 0.397 Married, N (%) 44(28.4%) 111(71.6%) 0.566 Gender, male (n, %) 39(33.1%) 70(66.9%) 0.027 Racial (n, %) 44(27.7% 115(72.3% 0.281 Atrial fibrillation (n, %) 0 8(100%) 0.066 Chemotherapy 9(50%) 9(50%) 0.058 Radiation therapy 0 4(100%) 0.263 Surgery Type (n, %) 27(30%) 63(70%) 0.598 SDNN 102.36 ± 28.37 100.72 ± 40.37 0.773 SDNN index 44.36 ± 14.82 45.78 ± 35.44 0.794 RMSSD 27.00 ± 11.1 28.07 ± 20.15 0.737 PNN50 5.67 ± 6.29 8.52 ± 15.04 0.221 Triangular index 22.09 ± 7.55 21.33 ± 7.62 0.57 HF 143.56 ± 167.09 242.42 ± 522.30 0.221 LF 238.45 ± 155.39 266.48 ± 326.30 0.587 VLF 736.98 ± 385.82 611.15 ± 457.79 0.087 LF/HF 2.43 ± 1.52 2.13 ± 1.39 0.231 Heart rate 71.91 ± 10.22 77.37 ± 12.50 0.01 Note, HF: high frequency indices; LF: low frequency indices; VLF : Very low frequency indices; NRS :Numerical rating scale;RMSSD: Root mean square of the successive differences༛SDNN: Standard deviation of the NN (R-R) intervals༛NN50: The number of pairs of successive NN (R-R) intervals that differ by more than 50 ms༛PNN50: The proportion of NN50 divided by the total number of NN (R-R) interval Discussion Liver cancer is the sixth most commonly diagnosed cancer and the fourth leading cause of cancer deaths worldwide in 2018, with approximately 841,000 new cases and 782,000 deaths annually[ 19 ]. Liver cancer is increasing in the United States and other countries, with an age-adjusted incidence rising from 1.5 to 4.9 per 100,000 individuals in the past 30 years[ 20 ]. Liver cancer has imposed a huge economic burden on society and the family[ 21 ]. Over the past decade, cancers associated with excess body weight (EBW) have shown troubling signs of increasing incidence among young adults and even adolescents. Growing number of evidence support an association between childhood or adolescent obesity and increased risk of liver cancer [ 22 ]. Besides, involuntary weight loss is a common symptom among liver cancer patients. Among advanced cancer patients, even patients with the higher food intake had a recent history of weight loss and 40% likelihood of energy intake insufficiency to support basal metabolism[ 23 ]. Patients with liver cancer had lower body weight, which was consistent with the other study[ 23 ]. An increased rate of weight loss is related to poor prognosis[ 24 ]. Weight loss not only predicts a shorter median survival, but also a lower response to chemotherapy[ 25 , 26 ]. The response to chemotherapy is also directly associated to total weight loss as well as the rate of weight loss[ 27 , 28 ]. Given the higher prevalence and worse impact of weight changes in the liver cancer patients, early detection and prevention of weight changes are of great significance to the prognosis of cancer patients. Although, measuring weight change is the most frequently used methods due to the advantage of being low cost to implement in clinical practice. However, there is no effective marker that can predict weight loss in advance. Several studies have demonstrated the association of weight alteration and HRV parameter. HRV represents the activity and balance of the autonomic nervous system and its capability to react to internal and external stimuli. As a measure of general body homeostasis, HRV is linked to lifestyle factors and it is associated with weight reduction[ 29 , 30 ]. Studies also show that decreased HRV is associated with cancer progression. Increased HRV predicts lower levels of lower tumor marker and higher survival of cancer patients[ 12 , 31 , 32 ]. A current ongoing clinical trial is testing the use of HRV changes as an early indicator of pancreatic cancer development (NCT04400903). In the current study, we focused on the role of ANS activity in liver cancer and examined the association between autonomic nervous activity and various risk factors. We first showed that liver cancer patients had lower BMI and lower HRV variation than non-malignant tumor population. Multiple logistic regression analysis further showed that a lower BMI, lower VLF indices, and history of hepatitis B virus infection were positively correlated with liver cancer. In order to demonstrate the relationship between HRV and body weight, HRV was tested in different groups of body weight. LF/VLF scores were shown to have a correlation with low weight in liver cancer patients. Patients with lower LF scores and HRV scores had a significantly lower average BMI. Therefore, HRV might be used as an indicator for the early detection of weight loss and prognosis among liver cancer patients. Early monitoring of HRV changes prior to the decline of HRV activity, even if the body weight is in the normal range, should be closely monitored to identify the risk of weight loss and cachexia as early as possible. Moreover, we should make early nutritional assessment and intervention in order to prevent the occurrence of weight loss through early monitoring of the HRV changes. This study provides the basis and direction for our future research. The mechanisms by which ANS predict abnormal BMI is still unclear. Collective studies have showed that the ANS modulates the inflammatory reflex, which are the indicators of vagally-mediated HRV, and is associated with reduced levels of inflammation by the cholinergic anti-inflammatory pathway[ 33 ]. Recent evidences also suggests that higher vagal nerve activity might have a protective effect on cancer patients, which might be linked to decreased levels of inflammation[ 34 ]. In a word, parasympathetic activation leads to reduced inflammation and sympathetic activation leads to increased inflammation, although these effects are complex and highly contextual[ 35 , 36 ]. Pain is related to ANS and body weight in the cancer patients[ 12 ]. Cancer-related pain, reported by > 70% of patients[ 37 ],is also a common liver cancer symptom, and the incidence of pain exceeded to 64.81% in our study. However, there was no relationship between pain and HRV changes in liver cancer patients. There are some limitations in our study. Firstly, the sample size is relatively small, which may affect the results; secondly, survival in patients with liver cancer, which is important in cancer research, is not evaluated; and as a retrospective study, this study has an intrinsic limitation, which may have affected the results. Therefore, in future more comprehensive measurements should be conducted including the survival, as a prospective study. Conclusion: This is the first time a study has shown that a decreased HRV is associated correlated with lower BMI independent of other con-founders in liver cancer. As predicted, the LF and LF/VLF scores were associated with low BMI. The role of HRV as a potential index for predicting cancer-related weight loss and improving the survival time of liver cancer patients is promising but require further validation by future studies. Declarations Author contributions Qingqing Huang designed and performed the current study. Vishnu Prasad Adhikari and Xi Quan performed some procedures. Changyan Feng assisted with the statistical analysis. Xiping Liang collected and drafted the related studies. Huiqing Yu participated in the design, revised, and finalized the manuscript. All authors read and approved the final manuscript. Competing interests There is no potential conflicts of interest. Acknowledgments This work is supported by research funding from Chongqing Scientific Research Institutions Performance Incentive and guidance Project, China (cstc2021jxj10166) and Natural Science Foundation of Chongqing, China (cstc2021jcyj-msxmX0400). All authors have agreed with the publication of this article and authorship, research. Consent to participate All patients were informed of the purpose of the study by telephone, and they or their relative provided consent through telephone calls. Consent for publication: All authors have agreed with the submission and publication of the article. Availability of data and material All data in this study can be got from the first author if necessary. Statement of Human and Animal Rights The privacy and human rights are fully protected in this study. There is no possibility of any infringement of patient privacy or endanger to their health. References Chen CL, Yang HI, Yang WS, et al. Metabolic factors and risk of hepatocellular carcinoma by chronic hepatitis B/C infection: a follow-up study in Taiwan. Gastroenterology, 2008. 135 (1): p. 111-21. Yang C, Lu YF, Xiao H, et al. Excess Body Weight and the Risk of Liver Cancer: Systematic Review and a Meta-Analysis of Cohort Studies. Nutr Cancer, 2019: p. 1-13. Schauer DP, Feigelson HS, Koebnick C, et al. Bariatric Surgery and the Risk of Cancer in a Large Multisite Cohort. Ann Surg. 2019 Jan;269((1)):95–101.4. L M Hess , R.B., C Tian, R F Ozols, et al. Weight Change During Chemotherapy as a Potential Prognostic Factor for Stage Iii Epithelial Ovarian Carcinoma. Gynecol Oncol 2007. 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Assessment of Karnofsky (KPS) and WHO (WHO-PS) performance scores in brain tumour patients: the role of clinician bias. Support Care Cancer, 2021. 29 (4): p. 1883-1891. Appelhans, B.M. and L.J. Luecken, Heart rate variability as an index of regulated emotional responding. Review of General Psychology, 2006. 10 (3): p. 229-240. 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. Eur Heart J, 1996. 17 (3): p. 354-81. Gigante A, Rosato E, Proietti M, et al. Heart rate variability in nephrotic syndrome: Role of sympathetic and parasympathetic system. Eur J Intern Med, 2018. 54 : p. e21-e22. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2018. 68 (6): p. 394-424. Altekruse, S.F., K.A. McGlynn, and M.E. Reichman. Hepatocellular carcinoma incidence, mortality, and survival trends in the United States from 1975 to 2005. J Clin Oncol, 2009. 27 (9): p. 1485-91. Zhou M, Wang H, Zeng X. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet, 2019. 394 (10204): p. 1145-1158. Scherübl H. Excess Body Weight and Gastrointestinal Cancer Risk. Visc Med. 2021 Aug;37(4):261-266. Hutton JL, Martin L, Field CJ, et al. Dietary patterns in patients with advanced cancer: implications for anorexia-cachexia therapy. Am J Clin Nutr, 2006. 84 (5): p. 1163-70. Deans DA, Tan BH, Wigmore SJ, et al. The influence of systemic inflammation, dietary intake and stage of disease on rate of weight loss in patients with gastro-oesophageal cancer. British Journal of Cancer, 2009. 100 (1): p. 63-69. Dewys WD, Begg C, Lavin PT, et al. Prognostic effect of weight loss prior to chemotherapy in cancer patients. Eastern Cooperative Oncology Group. Am J Med, 1980. 69 (4): p. 491-7. Persson C, Glimelius B. The relevance of weight loss for survival and quality of life in patients with advanced gastrointestinal cancer treated with palliative chemotherapy. Anticancer Res, 2002. 22 (6B): p. 3661-8. Willemsen ACH, De Moor N, Van Dessel J, et al. The predictive and prognostic value of weight loss and body composition prior to and during immune checkpoint inhibition in recurrent or metastatic head and neck cancer patients. Cancer Med. 2023 Apr;12(7):7699-7712. Cuttica CM, Briata IM, DeCensi A. Novel Treatments for Obesity: Implications for Cancer Prevention and Treatment. Nutrients. 2023 Aug 25;15(17):3737. Arab C, Dias DP, Barbosa RT, et al. Heart rate variability measure in breast cancer patients and survivors: A systematic review. Psychoneuroendocrinology, 2016. 68 : p. 57-68. McGee JE, Early KS, Huff AC, et al. Effects of weight loss and weight loss maintenance on cardiac autonomic function in obesity: a randomized controlled trial. Appl Physiol Nutr Metab. 2023 Sep 1;48(9):678-691. Wu S, Li G, Chen M, et al. Association of heartbeat complexity with survival in advanced non-small cell lung cancer patients. Front Neurosci. 2023 Apr 12;17:1113225. Kloter E, Barrueto K, Klein SD, et al. Heart rate variability as a prognostic factor for cancer survival‐A systematic review. Frontiers in Physiology, 2018. 9, 623. Williams DP, Koenig J, Carnevali L, et al. Heart rate variability and inflammation: A meta-analysis of human studies. Brain Behav Immun, 2019. 80 : p. 219-226. De Couck M, Maréchal R, Moorthamers S, et al. Vagal nerve activity predicts overall survival in metastatic pancreatic cancer, mediated by inflammation. Cancer Epidemiol, 2016. 40 : p. 47-51. Herhaus B, Conrad R, Petrowski K. Effect of a slow-paced breathing with heart rate variability biofeedback intervention on pro-inflammatory cytokines in individuals with panic disorder - A randomized controlled trial. J Affect Disord. 2023 Apr 1;326:132-138. Herhaus B, Thesing G, Conrad R, et al. Alterations in heart rate variability and pro-inflammatory cytokine TNF-alpha in individuals with panic disorder. Psychiatry Res. 2023 Apr;322:115107. Murofushi KN, Komazawa M, Murofushi W, et al. Preliminary Study on Establishing a Heart Rate Variability-based Method for Objectively Evaluating Bone Metastasis Pain. In Vivo. 2023 Mar-Apr;37(2):940-947. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4509982","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":312192238,"identity":"eb2ec369-8458-49f9-886b-c1eddcf7670f","order_by":0,"name":"Qingqing Huang","email":"","orcid":"","institution":"Chongqing University Cancer Hospital \u0026 Chongqing Cancer Institute \u0026 Chongqing Cancer Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qingqing","middleName":"","lastName":"Huang","suffix":""},{"id":312192239,"identity":"04dcedc4-fdee-428a-afae-84b03b7dd916","order_by":1,"name":"Xiping Liang","email":"","orcid":"","institution":"Chongqing University Cancer Hospital \u0026 Chongqing Cancer Institute \u0026 Chongqing Cancer Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiping","middleName":"","lastName":"Liang","suffix":""},{"id":312192240,"identity":"00bd7809-6903-4886-b8b8-1a4f7f427172","order_by":2,"name":"Changyan Feng","email":"","orcid":"","institution":"Chongqing University Cancer Hospital \u0026 Chongqing Cancer Institute \u0026 Chongqing Cancer Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Changyan","middleName":"","lastName":"Feng","suffix":""},{"id":312192241,"identity":"c25c2028-9bb8-467d-929f-3ef05a3cbf8b","order_by":3,"name":"Vishnu Prasad Adhikari","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Vishnu","middleName":"Prasad","lastName":"Adhikari","suffix":""},{"id":312192242,"identity":"543aba07-3287-4e12-8cf0-5f8a7adb4dc5","order_by":4,"name":"Xi Quan","email":"","orcid":"","institution":"Chongqing University Cancer Hospital \u0026 Chongqing Cancer Institute \u0026 Chongqing Cancer Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xi","middleName":"","lastName":"Quan","suffix":""},{"id":312192243,"identity":"b29066cf-752c-46f0-a011-ea7064bdecde","order_by":5,"name":"Huiqing Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYFACHgaGBAYJBgb2xsYHCRUScvLEa+E5fNjgwxkLY8MGYrSAgURamuTMtopEhgMENBjcyD0m8aDMIk/eIcdAmneeRAJjA/PDRzfwaslLk0g4J1FseOCMgTHvNok8dgY2Y+McvFpyzCQS2yQSNzb2GCQDtRQzNvCwSROnpZnH4DDvHInEhgPEapnPxpbYOLOBCC2SZ94YWwD9kriBh/kww4djEsaGzQT8wnc8x/Dmj7K6xPnzH7b/SKipk5Nnb374GJ8WhQMgkg3owgMwIWY8ykFAvgGqBcIYBaNgFIyCUYAFAAAk8k7x02zYOwAAAABJRU5ErkJggg==","orcid":"","institution":"Chongqing University Cancer Hospital \u0026 Chongqing Cancer Institute \u0026 Chongqing Cancer Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Huiqing","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2024-05-31 15:36:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4509982/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4509982/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58609190,"identity":"8bf7c375-2a9c-4e77-9877-cbd20c7ff306","added_by":"auto","created_at":"2024-06-18 21:55:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":73720,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"9.26figureMicrosoftPowerPoint.png","url":"https://assets-eu.researchsquare.com/files/rs-4509982/v1/2d9475ef9bdf469dd5b910ed.png"},{"id":58610981,"identity":"7d826d49-4037-4f5f-9fd9-cc59607ce29f","added_by":"auto","created_at":"2024-06-18 22:11:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":790350,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4509982/v1/dabd52e3-f4f8-41cf-996f-d104a57266ce.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Prognostic Correlation of Heart rate variability and body weight status in liver cancer patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAn abnormal body mass index (BMI) has an important role in the evolution and prognosis of cancer. Over weight is a well-known co-factor for the development of hepatocellular carcinoma (HCC). In a Taiwanese study, obesity was associated with a two-fold risk of HCC in patients without viral infections, and four-fold risk in anti-hepatitis C virus (HCV)-positive subjects[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A meta-analysis also showed that overweight patients had a 19% increased risk of liver cancer. Obesity was associated with 87% increased risk of liver cancer[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Effective measures to reduce excess weight may decrease EBW-associated HCC risk[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].Excess weight also predicts prognosis in patients with liver cancer. Compared with normal BMI patients, liver cancer patients with overweight/obesity is associated significantly with increased risk of mortality (9% and 66%, respectively)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, patients with rapid weight loss usually predicts a poor prognosis. Weight loss is also one of the most common and torturous symptoms reported by cancer patients and survivors. Weight loss during primary therapy is a strong predictor for prognostic and Overall Survival (OS) in epithelial ovarian carcinoma patients[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. And the relative risk for death increased by 7% for each 5% decrease in weight, independent of other confounders[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Weight loss affects the susceptibility to adverse effects and response to treatment leading to a poor prognosis and QoL in cancer patients[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the higher prevalence and worse impact of weight changes in cancer patients, early detection and prevention of weight changes are of great significance to the prognosis of cancer patients. An indicator that can predict weight changes is particularly important. One possible hypothesis is the autonomous nervous system (ANS). The ANS is a part of the peripheral nervous system and it plays an important role in cancer patients and the associated symptoms of cancer-related weight changes[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, the possible indicator predicting weight changes in liver cancer has not yet been determined.\u003c/p\u003e \u003cp\u003eHeart rate variability (HRV) is a systemic marker of ANS activity. It significantly and independently predicts cancer prognosis[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Study revealed that higher HRV predicts lower levels of tumor marker independent confounders[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Indeed, HRV ensures liver sensing of glucose, lipids, hormones, and owing to its well-known implication in liver pathology of tumor metabolism[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].Additionally, studies have reported that HRV responds to various aspects of the diet, raising the possibility that HRV offers a convenient measure of potential benefit[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. HRV has the potential to become a widely used biomarker for the prognosis of cancer patients with weight changes.\u003c/p\u003e \u003cp\u003eIn this study, we chose liver cancer and non-liver cancer patients as the focus to examine the relationship of HRV and weight status. Furthermore, we explored the possibility of HRV in predicting weight changes in HCC patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe retrospective study was conducted at Chongqing University Cancer Hospital. The participants enrolled in the study were diagnosed with liver cancer or benign liver tumors with intact ECG data from August 2017- July 2021. Approval for these studies was obtained from the Academic Medical Center Institutional Review Board (CZLS2022022-A). Informed consent was provided according to the Declaration of Helsinki. The control group comprised of healthy people undertaking physical examination in the Physical Examination Center of Chongqing University Cancer. All participants were \u0026ge;\u0026thinsp;18 years of age.\u003c/p\u003e \u003cp\u003eParticipant information, such as general condition, racial/ethnicity, marital status, education, employment, income, smoking history, HRV indicators, demographics, cancer history, pain scores, and QoL scores were collected from the hospital electronic recording system and electrocardiogram software. Body weight and height were measured at the time of admission to hospital by nurses, with the participants wearing light clothing and bare feet. The formula of BMI is as follows: BMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;weight (kg) / height (m\u003csup\u003e2\u003c/sup\u003e). According to World Health Organization (WHO) guidelines, BMI values were divided into four categories, as follows: underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e); normal weight (18.5\u0026thinsp;~\u0026thinsp;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e); overweight (25\u0026thinsp;~\u0026thinsp;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e); obese (\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e). Obese includes Level 1\u0026ndash;3 obesity status.\u003c/p\u003e \u003cp\u003eAll patients reported their average levels of pain and the most severe pain in the past week on a 11-point pain score (0, representing no pain, to 10 representing \u0026ldquo;pain as bad as you can imagine\u0026rdquo; or \u0026ldquo;worst pain imaginable\u0026rdquo;). Participants also reported the number of days they felt pain in the past week. Higher scores indicated worse pain. Performance status (i.e., physical activity) was assessed by the clinician. The Karnofsky Performance Scale (KPS) is usually used to measure the ability of cancer patients to perform ordinary tasks, the KPS covers 11 stages from 100 (normal health) to 0 (death)[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Patients having ability to carry on normal activity and work with no need for special care had a KPS score between 100 and 80. A KPS score between 70 and 50 are unable to work, but live at home and care for most personal needs with a varying amount of assistance[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHRV analysis during a 24-hECG recording was performed to assess ANS activity. A low RMSSD (Root mean square of the successive differences) at rest is a proposed index of poor autonomous regulation[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. RMSSD and the percentage of adjacent RR intervals with a duration difference\u0026thinsp;\u0026gt;\u0026thinsp;50ms (pNN50) are frequently used as an index of the parasympathetic system[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The frequency domain analysis of HRV were divided into multiple frequency bands. Total power in the frequency range was divided into low frequency (LF) (0.04\u0026ndash;0.15 Hz), very low frequency (VLF), and high frequency (HF) (0.15\u0026ndash;0.4 Hz); the LF/HF rate represents the sympathovagal balance[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Except for those who had died and lost contact, all patients were informed by telephone and informed consent. The patient's privacy information is well protected in this study. There is no possibility of any invasion of patient privacy or endanger to their health.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analyses\u003c/h2\u003e \u003cp\u003eSPSS (version23.0) was used for statistical analyses. Data were summarized using frequency counts and descriptive statistics. Intergroup comparisons were performed by one-way analysis of variance, t-tests, chi-square tests, single factor variance analysis, or multiple logistic regression analysis, as indicated. Measurement variables are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean. A p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.Participant characteristics\u003c/h2\u003e \u003cp\u003eDuring the investigation period, a total of 357 patients visited the Affiliated Oncology Hospital of Chongqing University complaining of liver tumor. Among them, 280 patients were diagnosed with liver cancer. Ten patients opted not to receive any treatment. A total of 77 unselected patients with de liver benign tumor patients and 77 healthy controls would like to take part in this study. 24-hECG recording were collected at the time of initial presentation. The demographic and complication characteristics of the patients\u0026rsquo; data are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and clinical characteristics of participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver cancer (n\u0026thinsp;=\u0026thinsp;270)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLiver benign tumor(n\u0026thinsp;=\u0026thinsp;77)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHealthy cohort control group (n\u0026thinsp;=\u0026thinsp;77)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026nbsp;value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(y),\u0026nbsp;M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.24\u0026thinsp;\u0026plusmn;\u0026thinsp;9.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.43\u0026thinsp;\u0026plusmn;\u0026thinsp;11.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.81\u0026thinsp;\u0026plusmn;\u0026thinsp;7.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.2461\u0026thinsp;\u0026plusmn;\u0026thinsp;3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.4571\u0026thinsp;\u0026plusmn;\u0026thinsp;3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.3829\u0026thinsp;\u0026plusmn;\u0026thinsp;3.481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKPS score, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.69\u0026thinsp;\u0026plusmn;\u0026thinsp;8.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.30\u0026thinsp;\u0026plusmn;\u0026thinsp;7.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43(26.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(38.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(36.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37(23.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart\u0026nbsp;disease\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14(8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(10.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBV (n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93(58.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(14.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106(66.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(87.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(73.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol\u0026nbsp;consumption\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125(78.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(91.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50(87.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital\u0026nbsp;Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u0026nbsp;(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155(96.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(85.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, Female\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42(26.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(57.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28(49.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial fibrillation\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRacial (n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e159(99.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56(98.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote, HBV: Hepatitis B Virus\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBoth BMI and KPS were lower than benign tumor patients and healthy controls (p\u0026thinsp;\u0026le;\u0026thinsp;0.001). The proportion of female patients was also significantly lower in the liver cancer group compared to benign tumor patients and healthy controls (p\u0026thinsp;\u0026le;\u0026thinsp;0.001). Majority participants were married in the three groups. The mean age was 66.43\u0026thinsp;\u0026plusmn;\u0026thinsp;9.25 years for the entire study cohort; No statistical difference was observed between the 3 groups (p\u0026gt;0.05). Compared to non-liver cancer patients, liver cancer patients were more likely to have a history of diabetes (p\u0026thinsp;=\u0026thinsp;0.005) and hepatitis B virus infection (p\u0026thinsp;\u0026le;\u0026thinsp;0.001). Meanwhile, the probability of cigarette smoking and alcohol consumption was lower in liver cancer patients; However, only the cigarette smoking was significantly different among 3 groups(p\u0026thinsp;=\u0026thinsp;0.018).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2. HRV and liver cancer\u003c/h2\u003e \u003cp\u003eIn order to know the ANS activity in liver cancer, we compared the difference of HRV by 24-hECG record. The majority of HRV indices in liver cancer patients were lower. However, we found that the mean average levels of SDNN and VLF bands in liver cancer were significantly lower than the other 2 groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The total variation of HRV in liver cancer patients were decreased compared to the healthy controls and patients with benign liver tumors. The HRV measures for the three groups are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;1, A.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeans of HRV variables compared between liver cancers and the other 2 groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver\u0026nbsp;cancer(n\u0026thinsp;=\u0026thinsp;270)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLiver benign tumor (n\u0026thinsp;=\u0026thinsp;77)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026nbsp;value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHealthy cohort control group (n\u0026thinsp;=\u0026thinsp;77)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026nbsp; value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCompared\u0026nbsp;with\u0026nbsp;liver\u0026nbsp;cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDNN,M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e101.18\u0026thinsp;\u0026plusmn;\u0026thinsp;37.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e120.98\u0026thinsp;\u0026plusmn;\u0026thinsp;36.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e-33.98~-5.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e117.26\u0026thinsp;\u0026plusmn;\u0026thinsp;28.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-29.27~-2.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDNN\u0026nbsp;index ,M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e45.38\u0026thinsp;\u0026plusmn;\u0026thinsp;31.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e52.80\u0026thinsp;\u0026plusmn;\u0026thinsp;42.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-19.88\u0026thinsp;~\u0026thinsp;5.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e48.86\u0026thinsp;\u0026plusmn;\u0026thinsp;14.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-14.87\u0026thinsp;~\u0026thinsp;7.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRMSSD,M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e27.77\u0026thinsp;\u0026plusmn;\u0026thinsp;18.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e27.79\u0026thinsp;\u0026plusmn;\u0026thinsp;17.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-7.11\u0026thinsp;~\u0026thinsp;7.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e26.67\u0026thinsp;\u0026plusmn;\u0026thinsp;10.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-3.61\u0026thinsp;~\u0026thinsp;5.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNN50,M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.72\u0026thinsp;\u0026plusmn;\u0026thinsp;13.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.17\u0026thinsp;\u0026plusmn;\u0026thinsp;6.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.83\u0026thinsp;~\u0026thinsp;5.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e5.82\u0026thinsp;\u0026plusmn;\u0026thinsp;4.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.18\u0026thinsp;~\u0026thinsp;5.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriangular index, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e21.54\u0026thinsp;\u0026plusmn;\u0026thinsp;7.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e23.87\u0026thinsp;\u0026plusmn;\u0026thinsp;7.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-5.37\u0026thinsp;~\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e26.47\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-7.72~-2.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHF,M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e214.17\u0026thinsp;\u0026plusmn;\u0026thinsp;451.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e218.77\u0026thinsp;\u0026plusmn;\u0026thinsp;420.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-176.73\u0026thinsp;~\u0026thinsp;167.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e179.42\u0026thinsp;\u0026plusmn;\u0026thinsp;253.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-118.55~-188.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLF,M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e258.47\u0026thinsp;\u0026plusmn;\u0026thinsp;287.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e380.79\u0026thinsp;\u0026plusmn;\u0026thinsp;584.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-350.33\u0026thinsp;~\u0026thinsp;105.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e307.77\u0026thinsp;\u0026plusmn;\u0026thinsp;218.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-138.95\u0026thinsp;~\u0026thinsp;40.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVLF,M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e647.10\u0026thinsp;\u0026plusmn;\u0026thinsp;440.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e914.15\u0026thinsp;\u0026plusmn;\u0026thinsp;769.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e-475.31~-58.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e893.18\u0026thinsp;\u0026plusmn;\u0026thinsp;387.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-433.28~-58.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLF/HF,M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.8\u0026thinsp;~\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e2.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.56\u0026thinsp;~\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate,M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e75.83\u0026thinsp;\u0026plusmn;\u0026thinsp;12.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e74.65\u0026thinsp;\u0026plusmn;\u0026thinsp;10.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.27\u0026thinsp;~\u0026thinsp;5.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e71.37\u0026thinsp;\u0026plusmn;\u0026thinsp;8.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.96\u0026thinsp;~\u0026thinsp;7.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote, HF: high frequency indices; LF: low frequency indices; VLF : Very low frequency indices; NRS :Numerical rating scale;RMSSD: Root mean square of the successive differences༛SDNN: Standard deviation of the NN (R-R) intervals༛NN50: The number of pairs of successive NN (R-R) intervals that differ by more than 50 ms༛PNN50: The proportion of NN50 divided by the total number of NN (R-R) interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe further analyzed the relationship of HRV and demographics, treatment-related history, and other potential confounders in liver cancer patients using multiple logistic regression analysis (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In agreement with previous research findings, the results showed that a lower BMI, lower VLF index, and history of hepatitis B virus infection were positively correlated with liver cancer patients. While age, history of diabetes, numerical rating scale (NRS), and PNN50 were negatively correlated with liver cancer patients. In liver cancer patients, BMI, the VLF indices and the total variation of HRV were decreased; and the correlation of reduced variation of HRV, VLF indices and BMI with liver cancer patients still exists, unaffected by confounders, such as diabetes and age (shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Logistic Regression Analysis of liver cancer compared to benign liver tumor\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u0026nbsp;value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95%\u0026nbsp;CI\u0026nbsp;for\u0026nbsp;OR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u0026ndash;0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u0026ndash;0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.02\u0026ndash;1.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of HBV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.55\u0026ndash;82.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.40\u0026ndash;0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNN50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.86\u0026ndash;0.998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVLF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00-1.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote, HBV: Hepatitis B Virus; NRS: Numerical rating scale; PNN50: The proportion of NN50 divided by the total number of NN (R-R) intervals; VLF: Very low frequency indices\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3. Associations between HRV and BMI\u003c/h2\u003e \u003cp\u003eThe results above showed that BMI and HRV indices were positively correlated with liver cancer patients. To further determine whether the HRV changes in liver cancer patients are correlated with BMI status, we designed the following analysis. BMI was divided into low weight, normal weight, overweight, obesity, and morbidly obese groups in accordance with WHO criteria. The morbidly obese patients were included in the obesity group due to their lesser counts. The relationship of HRV and BMI status in liver cancer patients is presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;1, B.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations between BMI category and HRV score in liver cancer group.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u0026nbsp;BMI\u0026nbsp;(n\u0026nbsp;=154)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnderweight\u0026nbsp;(n\u0026nbsp;=\u0026nbsp;48)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026nbsp;value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOverweight\u0026nbsp;(n\u0026nbsp;=56)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u0026nbsp;value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eObese\u0026nbsp;(n\u0026nbsp;=12)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep\u0026nbsp;value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCompared\u0026nbsp;with\u0026nbsp;normal\u0026nbsp;BMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDNN, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e98.37\u0026thinsp;\u0026plusmn;\u0026thinsp;30.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e92.91\u0026thinsp;\u0026plusmn;\u0026thinsp;27.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-23.31-12.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e115.97\u0026thinsp;\u0026plusmn;\u0026thinsp;58.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-48.45-13.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e103.5\u0026thinsp;\u0026plusmn;\u0026thinsp;29.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-92.46-82.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDNN\u0026nbsp;index, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e44.51\u0026thinsp;\u0026plusmn;\u0026thinsp;25.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e35.53\u0026thinsp;\u0026plusmn;\u0026thinsp;13.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.11-19.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e53.63\u0026thinsp;\u0026plusmn;\u0026thinsp;51.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-36.11-17.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e45.5\u0026thinsp;\u0026plusmn;\u0026thinsp;15.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-44.26-42.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRMSSD, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e27.27\u0026thinsp;\u0026plusmn;\u0026thinsp;17.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e22.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.12-11.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e30.97\u0026thinsp;\u0026plusmn;\u0026thinsp;21.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-15.64-8.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;26.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-84.03-74.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNN50, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.25\u0026thinsp;\u0026plusmn;\u0026thinsp;12.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.17\u0026thinsp;\u0026plusmn;\u0026thinsp;4.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.08-7.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;15.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-11.3-5.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;14.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-45.42-39.93-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriangular index, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e21.26\u0026thinsp;\u0026plusmn;\u0026thinsp;7.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e21.35\u0026thinsp;\u0026plusmn;\u0026thinsp;7.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.8-4.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e22.57\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-5.55-2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e23.25\u0026thinsp;\u0026plusmn;\u0026thinsp;10.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-12.41-8.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHF, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e191.88\u0026thinsp;\u0026plusmn;\u0026thinsp;389.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e90.79\u0026thinsp;\u0026plusmn;\u0026thinsp;67.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-11.26-213.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e309.69\u0026thinsp;\u0026plusmn;\u0026thinsp;664.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-479.83-244.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e390.08\u0026thinsp;\u0026plusmn;\u0026thinsp;605.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-2024.28-1627.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLF, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e261.21\u0026thinsp;\u0026plusmn;\u0026thinsp;257.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e146.03\u0026thinsp;\u0026plusmn;\u0026thinsp;135.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.60-219.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e302.42\u0026thinsp;\u0026plusmn;\u0026thinsp;412.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-267.22-184.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e348.1\u0026thinsp;\u0026plusmn;\u0026thinsp;292.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-949.72-775.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVLF, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e687.79\u0026thinsp;\u0026plusmn;\u0026thinsp;469.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e524.32\u0026thinsp;\u0026plusmn;\u0026thinsp;366.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-110.6-437.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e613.60\u0026thinsp;\u0026plusmn;\u0026thinsp;398.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-175.91-324.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e686.3\u0026thinsp;\u0026plusmn;\u0026thinsp;419.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-601.43-604.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLF/HF, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.098\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e2.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-0.62-1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e2.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-5.88-5.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e75.51\u0026thinsp;\u0026plusmn;\u0026thinsp;12.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e77.22\u0026thinsp;\u0026plusmn;\u0026thinsp;10.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-8.74-5.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e76.37\u0026thinsp;\u0026plusmn;\u0026thinsp;11.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e \u003cp\u003e-7.76-6.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c9\"\u003e \u003cp\u003e70.75\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e \u003cp\u003e-13.11-26.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote, HF: high frequency indices; LF: low frequency indices; VLF : Very low frequency indices; NRS :Numerical rating scale;RMSSD: Root mean square of the successive differences༛SDNN: Standard deviation of the NN (R-R) intervals༛NN50: The number of pairs of successive NN (R-R) intervals that differ by more than 50 ms༛PNN50: The proportion of NN50 divided by the total number of NN (R-R) interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn comparison to the HRV index in the underweight group decreased significantly compared to the patients with normal weight. Meanwhile, it was not statistically significant for the patients with overweight and obesity, (Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Significance between HRV indices values and BMI in liver cancer patients was only reported in the low weight group patients. It seems that the HRV indexes maybe used to predict weight loss in liver cancer patients.\u003c/p\u003e \u003cp\u003eAs predicted, the LF and LF/VLF scores were correlated with low BMI in the liver cancer patients. The correlation was independent of several other confounders, such as age and history of diabetes. This finding further showed that the decreased ANS activity in liver cancer patients was mainly related to low body weight, with the difference being statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4. Associations between HRV and pain\u003c/h2\u003e \u003cp\u003ePain is related with ANS and body weight in cancer patients[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The incidence of pain is relatively high (64.81%) in liver cancer patients; Therefore, we further analyzed the relationship between pain and HRV in liver cancer patients. The liver cancer patients were divided into pain and no-pain groups; the results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. No difference was demonstrated between the two groups, with the exception of cigarette smoking and gender. The proportion of patients who smoked cigarettes in the pain group was significantly higher than the no-pain group. No significant difference was found in HRV indices and BMI between the two groups. There was no relationship between pain and HRV changes in liver cancer patients.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations between HRV and pain in liver cancer patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003evariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Cancer-\u0026nbsp;pain(n\u0026thinsp;=\u0026thinsp;175)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCancer-related pain(n\u0026thinsp;=\u0026thinsp;95)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026nbsp;value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(y),\u0026nbsp;M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.58\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.72\u0026thinsp;\u0026plusmn;\u0026thinsp;9.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKPS score, M\u0026nbsp;(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.22\u0026thinsp;\u0026plusmn;\u0026thinsp;8.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.09\u0026thinsp;\u0026plusmn;\u0026thinsp;8.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(30.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(69.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15(40.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(59.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart\u0026nbsp;disease\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(57.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBV (n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31(32.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65(67.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(59.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol\u0026nbsp;consumption\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(34.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(65.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried, N\u0026nbsp;(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44(28.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111(71.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, male\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39(33.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70(66.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRacial (n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44(27.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115(72.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial fibrillation\u0026nbsp;(n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiation\u0026nbsp;therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgery\u0026nbsp;Type (n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27(30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63(70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDNN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102.36\u0026thinsp;\u0026plusmn;\u0026thinsp;28.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.72\u0026thinsp;\u0026plusmn;\u0026thinsp;40.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDNN\u0026nbsp;index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.36\u0026thinsp;\u0026plusmn;\u0026thinsp;14.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.78\u0026thinsp;\u0026plusmn;\u0026thinsp;35.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRMSSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.00\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.07\u0026thinsp;\u0026plusmn;\u0026thinsp;20.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.737\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNN50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.67\u0026thinsp;\u0026plusmn;\u0026thinsp;6.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.52\u0026thinsp;\u0026plusmn;\u0026thinsp;15.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriangular index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.09\u0026thinsp;\u0026plusmn;\u0026thinsp;7.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.33\u0026thinsp;\u0026plusmn;\u0026thinsp;7.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143.56\u0026thinsp;\u0026plusmn;\u0026thinsp;167.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242.42\u0026thinsp;\u0026plusmn;\u0026thinsp;522.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e238.45\u0026thinsp;\u0026plusmn;\u0026thinsp;155.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e266.48\u0026thinsp;\u0026plusmn;\u0026thinsp;326.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.587\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVLF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e736.98\u0026thinsp;\u0026plusmn;\u0026thinsp;385.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e611.15\u0026thinsp;\u0026plusmn;\u0026thinsp;457.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLF/HF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.91\u0026thinsp;\u0026plusmn;\u0026thinsp;10.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.37\u0026thinsp;\u0026plusmn;\u0026thinsp;12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote, HF: high frequency indices; LF: low frequency indices; VLF : Very low frequency indices; NRS :Numerical rating scale;RMSSD: Root mean square of the successive differences༛SDNN: Standard deviation of the NN (R-R) intervals༛NN50: The number of pairs of successive NN (R-R) intervals that differ by more than 50 ms༛PNN50: The proportion of NN50 divided by the total number of NN (R-R) interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eLiver cancer is the sixth most commonly diagnosed cancer and the fourth leading cause of cancer deaths worldwide in 2018, with approximately 841,000 new cases and 782,000 deaths annually[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Liver cancer is increasing in the United States and other countries, with an age-adjusted incidence rising from 1.5 to 4.9 per 100,000 individuals in the past 30 years[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Liver cancer has imposed a huge economic burden on society and the family[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOver the past decade, cancers associated with excess body weight (EBW) have shown troubling signs of increasing incidence among young adults and even adolescents. Growing number of evidence support an association between childhood or adolescent obesity and increased risk of liver cancer [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Besides, involuntary weight loss is a common symptom among liver cancer patients. Among advanced cancer patients, even patients with the higher food intake had a recent history of weight loss and 40% likelihood of energy intake insufficiency to support basal metabolism[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Patients with liver cancer had lower body weight, which was consistent with the other study[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. An increased rate of weight loss is related to poor prognosis[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Weight loss not only predicts a shorter median survival, but also a lower response to chemotherapy[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The response to chemotherapy is also directly associated to total weight loss as well as the rate of weight loss[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the higher prevalence and worse impact of weight changes in the liver cancer patients, early detection and prevention of weight changes are of great significance to the prognosis of cancer patients. Although, measuring weight change is the most frequently used methods due to the advantage of being low cost to implement in clinical practice. However, there is no effective marker that can predict weight loss in advance. Several studies have demonstrated the association of weight alteration and HRV parameter. HRV represents the activity and balance of the autonomic nervous system and its capability to react to internal and external stimuli. As a measure of general body homeostasis, HRV is linked to lifestyle factors and it is associated with weight reduction[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Studies also show that decreased HRV is associated with cancer progression. Increased HRV predicts lower levels of lower tumor marker and higher survival of cancer patients[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. A current ongoing clinical trial is testing the use of HRV changes as an early indicator of pancreatic cancer development (NCT04400903).\u003c/p\u003e \u003cp\u003eIn the current study, we focused on the role of ANS activity in liver cancer and examined the association between autonomic nervous activity and various risk factors. We first showed that liver cancer patients had lower BMI and lower HRV variation than non-malignant tumor population. Multiple logistic regression analysis further showed that a lower BMI, lower VLF indices, and history of hepatitis B virus infection were positively correlated with liver cancer. In order to demonstrate the relationship between HRV and body weight, HRV was tested in different groups of body weight. LF/VLF scores were shown to have a correlation with low weight in liver cancer patients. Patients with lower LF scores and HRV scores had a significantly lower average BMI. Therefore, HRV might be used as an indicator for the early detection of weight loss and prognosis among liver cancer patients. Early monitoring of HRV changes prior to the decline of HRV activity, even if the body weight is in the normal range, should be closely monitored to identify the risk of weight loss and cachexia as early as possible. Moreover, we should make early nutritional assessment and intervention in order to prevent the occurrence of weight loss through early monitoring of the HRV changes. This study provides the basis and direction for our future research.\u003c/p\u003e \u003cp\u003eThe mechanisms by which ANS predict abnormal BMI is still unclear. Collective studies have showed that the ANS modulates the inflammatory reflex, which are the indicators of vagally-mediated HRV, and is associated with reduced levels of inflammation by the cholinergic anti-inflammatory pathway[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Recent evidences also suggests that higher vagal nerve activity might have a protective effect on cancer patients, which might be linked to decreased levels of inflammation[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In a word, parasympathetic activation leads to reduced inflammation and sympathetic activation leads to increased inflammation, although these effects are complex and highly contextual[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePain is related to ANS and body weight in the cancer patients[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Cancer-related pain, reported by \u0026gt;\u0026thinsp;70% of patients[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e],is also a common liver cancer symptom, and the incidence of pain exceeded to 64.81% in our study. However, there was no relationship between pain and HRV changes in liver cancer patients.\u003c/p\u003e \u003cp\u003eThere are some limitations in our study. Firstly, the sample size is relatively small, which may affect the results; secondly, survival in patients with liver cancer, which is important in cancer research, is not evaluated; and as a retrospective study, this study has an intrinsic limitation, which may have affected the results. Therefore, in future more comprehensive measurements should be conducted including the survival, as a prospective study.\u003c/p\u003e \u003cp\u003eConclusion: This is the first time a study has shown that a decreased HRV is associated correlated with lower BMI independent of other con-founders in liver cancer. As predicted, the LF and LF/VLF scores were associated with low BMI. The role of HRV as a potential index for predicting cancer-related weight loss and improving the survival time of liver cancer patients is promising but require further validation by future studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQingqing Huang designed\u0026nbsp;and\u0026nbsp;performed the current study.\u0026nbsp;Vishnu Prasad Adhikari and Xi Quan\u0026nbsp;performed\u0026nbsp;some\u0026nbsp;procedures. Changyan Feng assisted with the statistical analysis.\u0026nbsp;Xiping Liang collected and drafted the related studies. Huiqing Yu participated in the design, revised, and finalized the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is\u0026nbsp;no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is supported by research funding from Chongqing Scientific Research Institutions Performance Incentive and guidance Project, China (cstc2021jxj10166) and Natural Science Foundation of Chongqing, China (cstc2021jcyj-msxmX0400).\u003c/p\u003e\n\u003cp\u003eAll authors have agreed with the publication of this article and authorship, research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll\u0026nbsp;patients were informed of the purpose of the study by telephone, and they or their relative provided consent through telephone calls.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have agreed with the submission and publication of the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data in this study can be got from the first author if necessary.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of Human and Animal Rights\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe privacy and human rights are fully protected in this study. There is no possibility of any infringement of patient privacy or endanger to their health. \u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen CL, Yang HI, Yang WS, et al. Metabolic factors and risk of hepatocellular carcinoma by chronic hepatitis B/C infection: a follow-up study in Taiwan. Gastroenterology, 2008. \u003cstrong\u003e135\u003c/strong\u003e(1): p. 111-21.\u003c/li\u003e\n\u003cli\u003eYang C, Lu YF, Xiao H, et al. Excess Body Weight and the Risk of Liver Cancer: Systematic Review and a Meta-Analysis of Cohort Studies. Nutr Cancer, 2019: p. 1-13.\u003c/li\u003e\n\u003cli\u003eSchauer DP, Feigelson HS, Koebnick C, et al. Bariatric Surgery and the Risk of Cancer in a Large Multisite Cohort. Ann Surg. 2019 Jan;269((1)):95\u0026ndash;101.4. \u003c/li\u003e\n\u003cli\u003eL M Hess , R.B., C Tian, R F Ozols, et al. Weight Change During Chemotherapy as a Potential Prognostic Factor for Stage Iii Epithelial Ovarian Carcinoma. 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In Vivo. 2023 Mar-Apr;37(2):940-947.\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"autonomous nervous system, liver cancer, sympathetic activity, weight loss, body mass index","lastPublishedDoi":"10.21203/rs.3.rs-4509982/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4509982/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWeight status play an important role in the evolution and prognosis of cancer patients; however alterations of autonomic nervous system (ANS) caused by cancer may be the associated symptoms in cancer-related weight change.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThe aim of this study is to identify the influence of weight status on ANS and determine whether ANS can be used as an index for early detection and prediction of weight changes in liver cancer patients with HRV.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective analysis of clinical data for newly diagnosed liver cancer from 2017 to 2022 in China. The authors conducted clinical and ECG data of liver cancer with special emphasis on advances ECG and the BMI aspect.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eBoth BMI and KPS were lower in the liver cancer group compared to benign tumor patients and healthy controls (p\u0026thinsp;\u0026le;\u0026thinsp;0.001). Liver cancer patients were more likely to have a history of diabetes (p\u0026thinsp;=\u0026thinsp;0.005) and hepatitis B virus infection (p\u0026thinsp;\u0026le;\u0026thinsp;0.001) compared to non-liver cancer patients. Moreover, the HRV indices and variations remained low in liver cancer patients Additionally, the mean average levels of SDNN and VLF bands in liver cancer remained significantly low (p\u0026thinsp;\u0026le;\u0026thinsp;0.005). The results reveal that a lower BMI, lower VLF index, together with history of HBV infection positively correlated in liver cancer patients. The study reveals that HRV indices is associated with BMI in liver cancer patients with lesser body weight. As predicted, the LF and LF/VLF scores had correlation with lower BMI in the liver cancer patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn liver cancer patients, decreased HRV was associated with a lower BMI independent of other con-founders. The role of HRV as a potential index for predicting cancer-related weight loss and improving the survival time of liver cancer patients are promising but require further validation in future studies.\u003c/p\u003e","manuscriptTitle":"The Prognostic Correlation of Heart rate variability and body weight status in liver cancer patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-18 21:55:12","doi":"10.21203/rs.3.rs-4509982/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2c1c075f-e588-4e52-a119-947dcede7ef7","owner":[],"postedDate":"June 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-18T21:55:14+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-18 21:55:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4509982","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4509982","identity":"rs-4509982","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}