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Salluce C, Cocciante M, Gazzillo M, Ferrari AR, Battini R, Santorelli FM, Bartolini E. Children and Young Adults with Epilepsy Exhibit an Interictal Autonomic Dysfunction: A Prospective Exploratory Study. Brain Sci 2024; 14:670. [PMID: 39061411 PMCID: PMC11274926 DOI: 10.3390/brainsci14070670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 06/25/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024] Open
Abstract
Dysautonomic disorders are an increasingly studied group of conditions, either as isolated diseases or associated with other neurological disorders. There is growing interest in understanding how dysautonomia affects people with epilepsy, who may report autonomic symptoms before, during and after seizures. Furthermore, autonomic abnormalities appear to play a role in sudden unexpected death in epilepsy, likely contributing to the increased mortality rate described in epilepsy. To better understand the association between epilepsy and dysautonomia, we explored electrochemical skin conductance in a group of 18 children and young adults with epilepsy compared to 15 age- and sex-matched healthy controls by the SudoscanTM test. We found a significant difference in terms of electrochemical skin conductance, suggesting that people with epilepsy suffer significantly reduced conductance in small nerve fibers. Within patients, values were significantly different according to the type of epilepsy and to neuroimaging results, with lower conductance values in epilepsies of unknown origin and in patients with morphological abnormalities of the brain. Using a non-invasive test, we identified altered conductance of small sympathetic nerve fibers in children and young adults with epilepsy, suggesting underlying dysautonomia. Further studies are needed to investigate this association and to clarify its neurobiological substrates.
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Affiliation(s)
- Carmen Salluce
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, 56128 Pisa, Italy; (C.S.); (M.C.); (M.G.); (A.R.F.); (R.B.); (F.M.S.)
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy
| | - Marco Cocciante
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, 56128 Pisa, Italy; (C.S.); (M.C.); (M.G.); (A.R.F.); (R.B.); (F.M.S.)
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy
| | - Marisa Gazzillo
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, 56128 Pisa, Italy; (C.S.); (M.C.); (M.G.); (A.R.F.); (R.B.); (F.M.S.)
- Division of Pediatric Neurology, Department of Neurosciences, Santobono-Pausillipon Children’s Hospital, 80129 Naples, Italy
| | - Anna Rita Ferrari
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, 56128 Pisa, Italy; (C.S.); (M.C.); (M.G.); (A.R.F.); (R.B.); (F.M.S.)
| | - Roberta Battini
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, 56128 Pisa, Italy; (C.S.); (M.C.); (M.G.); (A.R.F.); (R.B.); (F.M.S.)
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy
| | - Filippo Maria Santorelli
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, 56128 Pisa, Italy; (C.S.); (M.C.); (M.G.); (A.R.F.); (R.B.); (F.M.S.)
| | - Emanuele Bartolini
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, 56128 Pisa, Italy; (C.S.); (M.C.); (M.G.); (A.R.F.); (R.B.); (F.M.S.)
- Tuscany PhD Program in Neurosciences, 50139 Florence, Italy
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Assessing epilepsy-related autonomic manifestations: Beyond cardiac and respiratory investigations. Neurophysiol Clin 2023; 53:102850. [PMID: 36913775 DOI: 10.1016/j.neucli.2023.102850] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 02/15/2023] [Accepted: 02/19/2023] [Indexed: 03/13/2023] Open
Abstract
The Autonomic Nervous System (ANS) regulates many critical physiological functions. Its control relies on cortical input, especially limbic areas, which are often involved in epilepsy. Peri-ictal autonomic dysfunction is now well documented, but inter-ictal dysregulation is less studied. In this review, we discuss the available data on epilepsy-related autonomic dysfunction and the objective tests available. Epilepsy is associated with sympathetic-parasympathetic imbalance and a shift towards sympathetic dominance. Objective tests report alterations in heart rate, baroreflex function, cerebral autoregulation, sweat glands activity, thermoregulation, gastrointestinal and urinary function. However, some tests have found contradictory results and many tests suffer from a lack of sensitivity and reproducibility. Further study on interictal ANS function is required to further understand autonomic dysregulation and the potential association with clinically-relevant complications, including risk of Sudden Unexpected Death In Epilepsy (SUDEP).
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Yang Z, Cheng TY, Deng J, Wang Z, Qin X, Fang X, Yuan Y, Hao H, Jiang Y, Liao J, Yin F, Chen Y, Zou L, Li B, Gao Y, Shu X, Huang S, Gao F, Liang J, Li L. Impairment of Cardiac Autonomic Nerve Function in Pre-school Children With Intractable Epilepsy. Front Neurol 2021; 12:632370. [PMID: 34248813 PMCID: PMC8267887 DOI: 10.3389/fneur.2021.632370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 05/10/2021] [Indexed: 02/05/2023] Open
Abstract
Objective: Intractable epilepsy and uncontrolled seizures could affect cardiac function and the autonomic nerve system with a negative impact on children's growth. The aim of this study was to investigate the variability and complexity of cardiac autonomic function in pre-school children with pediatric intractable epilepsy (PIE). Methods: Twenty four-hour Holter electrocardiograms (ECGs) from 93 patients and 46 healthy control subjects aged 3-6 years were analyzed by the methods of traditional heart rate variability (HRV), multiscale entropy (MSE), and Kurths-Wessel symbolization entropy (KWSE). Receiver operating characteristic (ROC) curve analysis was used to estimate the overall discrimination ability. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) models were also analyzed. Results: Pre-school children with PIE had significantly lower HRV measurements than healthy controls in time (Mean_RR, SDRR, RMSSD, pNN50) and frequency (VLF, LF, HF, LF/HF, TP) domains. For the MSE analysis, area 1_5 in awake state was lower, and areas 6_15 and 6_20 in sleep state were higher in PIE with a significant statistical difference. KWSE in the PIE group was also inferior to that in healthy controls. In ROC curve analysis, pNN50 had the greatest discriminatory power for PIE. Based on both NRI and IDI models, the combination of MSE indices (wake: area1_5 and sleep: area6_20) and KWSE (m = 2, τ = 1, α = 0.16) with traditional HRV measures had greater discriminatory power than any of the single HRV measures. Significance: Impaired HRV and complexity were found in pre-school children with PIE. HRV, MSE, and KWSE could discriminate patients with PIE from subjects with normal cardiac complexity. These findings suggested that the MSE and KWSE methods may be helpful for assessing and understanding heart rate dynamics in younger children with epilepsy.
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Affiliation(s)
- Zhao Yang
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Tung-Yang Cheng
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Jin Deng
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Zhiyan Wang
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Xiaoya Qin
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Xi Fang
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Yuan Yuan
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Hongwei Hao
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Yuwu Jiang
- Division of Pediatric Neurology, Pediatrics Department, Peking University First Hospital, Beijing, China
- Department of Pediatric Epilepsy Center, Peking University First Hospital, Beijing, China
| | - Jianxiang Liao
- Department of Neurology, Shenzhen Children's Hospital, Shenzhen, China
| | - Fei Yin
- Department of Pediatrics, Xiangya Hospital of Central South University, Changsha, China
- Hunan Intellectual and Developmental Disabilities Research Center of Children, Changsha, China
| | - Yanhui Chen
- Division of Pediatric Neurology, Pediatrics Department, Fujian Medical University Union Hospital, Fuzhou, China
- Department of Epilepsy Center, Fujian Medical University Union Hospital, Fuzhou, China
| | - Liping Zou
- Department of Pediatric, The People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Baomin Li
- Pediatics Department, Qilu Hospital of Shandong University, Jinan, China
| | - Yuxing Gao
- Division of Pediatrics Neurology, Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Xiaomei Shu
- Department of Pediatrics, Affiliated Hospital of Zunyi Medical College, Zunyi, China
| | - Shaoping Huang
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Feng Gao
- Department of Neurology, The Children's Hospital, ZheJiang University School of Medicine, Hangzhou, China
| | - Jianmin Liang
- Department of Pediatric Neurology, First Bethune Hospital, Jilin University, Changchun, China
- Research Center of Neuroscience, First Bethune Hospital, Jilin University, Changchun, China
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
- Precision Medicine and Healthcare Research Center, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China
- Institute of Human-Machine, School of Aerospace Engineering, Tsinghua University, Beijing, China
- Center of Epilepsy, Beijing Institute for Brain Disorders, Beijing, China
- *Correspondence: Luming Li
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Liu H, Zhan P, Shi J, Hu M, Wang G, Wang W. Heart rhythm complexity as predictors for the prognosis of end-stage renal disease patients undergoing hemodialysis. BMC Nephrol 2020; 21:536. [PMID: 33297978 PMCID: PMC7727237 DOI: 10.1186/s12882-020-02196-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Accepted: 11/29/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Heart rhythm complexity, a measure of heart rate dynamics and a risk predictor in various clinical diseases, has not been systematically studied in patients with end-stage renal disease. The aim of this study is to investigate the heart rhythm complexity and its prognostic value for mortality in end-stage renal disease patients undergoing hemodialysis. METHODS To assess heart rhythm complexity and conventional heart rate variability measures, 4-h continuous electrocardiography for a retrospective cohort of 202 ostensibly healthy control subjects and 51 hemodialysis patients with end-stage renal disease were analyzed. Heart rhythm complexity was quantified by the complexity index from the measurement of the multiscale entropy profile. RESULTS During a follow-up of 13 months, 8 people died in the patient group. Values of either traditional heart rate variability measurements or complexity indices were found significantly lower in patients than those in healthy controls. In addition, the complexity indices (Area 1-5, Area 6-15 and Area 6-20) in the mortality group were significantly lower than those in the survival group, while there were no significant differences in traditional heart rate variability parameters between the two groups. In receiver operating characteristic curve analysis, Area 6-20 (AUC = 0.895, p < 0.001) showed the strongest predictive power between mortality and survival groups. CONCLUSION The results suggest that heart rhythm complexity is impaired for patients with end-stage renal disease. Furthermore, the complexity index of heart rate variability quantified by multiscale entropy may be a powerful independent predictor of mortality in end-stage renal disease patients undergoing hemodialysis.
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Affiliation(s)
- Hongyun Liu
- Research Center for Biomedical Engineering, Medical Innovation & Research Division, Chinese PLA General Hospital, Fuxing Road, Beijing, 100853, China
| | - Ping Zhan
- Research Center for Biomedical Engineering, Medical Innovation & Research Division, Chinese PLA General Hospital, Fuxing Road, Beijing, 100853, China
| | - Jinlong Shi
- Medical Big Data Center, Medical Innovation & Research Division, Chinese PLA General Hospital, Fuxing Road, Beijing, 100853, China
| | - Minlu Hu
- Research Center for Biomedical Engineering, Medical Innovation & Research Division, Chinese PLA General Hospital, Fuxing Road, Beijing, 100853, China
| | - Guojing Wang
- Research Center for Biomedical Engineering, Medical Innovation & Research Division, Chinese PLA General Hospital, Fuxing Road, Beijing, 100853, China
| | - Weidong Wang
- Research Center for Biomedical Engineering, Medical Innovation & Research Division, Chinese PLA General Hospital, Fuxing Road, Beijing, 100853, China.
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Spectral entropy indicates electrophysiological and hemodynamic changes in drug-resistant epilepsy - A multimodal MREG study. NEUROIMAGE-CLINICAL 2019; 22:101763. [PMID: 30927607 PMCID: PMC6444290 DOI: 10.1016/j.nicl.2019.101763] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Revised: 02/01/2019] [Accepted: 03/10/2019] [Indexed: 12/20/2022]
Abstract
Objective Epilepsy causes measurable irregularity over a range of brain signal frequencies, as well as autonomic nervous system functions that modulate heart and respiratory rate variability. Imaging dynamic neuronal signals utilizing simultaneously acquired ultra-fast 10 Hz magnetic resonance encephalography (MREG), direct current electroencephalography (DC-EEG), and near-infrared spectroscopy (NIRS) can provide a more comprehensive picture of human brain function. Spectral entropy (SE) is a nonlinear method to summarize signal power irregularity over measured frequencies. SE was used as a joint measure to study whether spectral signal irregularity over a range of brain signal frequencies based on synchronous multimodal brain signals could provide new insights in the neural underpinnings of epileptiform activity. Methods Ten patients with focal drug-resistant epilepsy (DRE) and ten healthy controls (HC) were scanned with 10 Hz MREG sequence in combination with EEG, NIRS (measuring oxygenated, deoxygenated, and total hemoglobin: HbO, Hb, and HbT, respectively), and cardiorespiratory signals. After pre-processing, voxelwise SEMREG was estimated from MREG data. Different neurophysiological and physiological subfrequency band signals were further estimated from MREG, DC-EEG, and NIRS: fullband (0–5 Hz, FB), near FB (0.08–5 Hz, NFB), brain pulsations in very-low (0.009–0.08 Hz, VLFP), respiratory (0.12–0.4 Hz, RFP), and cardiac (0.7–1.6 Hz, CFP) frequency bands. Global dynamic fluctuations in MREG and NIRS were analyzed in windows of 2 min with 50% overlap. Results Right thalamus, cingulate gyrus, inferior frontal gyrus, and frontal pole showed significantly higher SEMREG in DRE patients compared to HC. In DRE patients, SE of cortical Hb was significantly reduced in FB (p = .045), NFB (p = .017), and CFP (p = .038), while both HbO and HbT were significantly reduced in RFP (p = .038, p = .045, respectively). Dynamic SE of HbT was reduced in DRE patients in RFP during minutes 2 to 6. Fitting to the frontal MREG and NIRS results, DRE patients showed a significant increase in SEEEG in FB in fronto-central and parieto-occipital regions, in VLFP in parieto-central region, accompanied with a significant decrease in RFP in frontal pole and parietal and occipital (O2, Oz) regions. Conclusion This is the first study to show altered spectral entropy from synchronous MREG, EEG, and NIRS in DRE patients. Higher SEMREG in DRE patients in anterior cingulate gyrus together with SEEEG and SENIRS results in 0.12–0.4 Hz can be linked to altered parasympathetic function and respiratory pulsations in the brain. Higher SEMREG in thalamus in DRE patients is connected to disturbances in anatomical and functional connections in epilepsy. Findings suggest that spectral irregularity of both electrophysiological and hemodynamic signals are altered in specific way depending on the physiological frequency range. Simultaneous imaging methods indicate spectral irregularity in neurovascular and electrophysiological brain pulsations in DRE. Altered spectral entropy in EEG, NIRS and BOLD indicate dysfunctional brain pulsations in respiratory frequency in epilepsy. Spectral irregularity (0-5 Hz) of BOLD in right thalamus supports previous structural and functional findings in epilepsy.
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Yang Z, Liu H, Meng F, Guan Y, Zhao M, Qu W, Hao H, Luan G, Zhang J, Li L. The analysis of circadian rhythm of heart rate variability in patients with drug-resistant epilepsy. Epilepsy Res 2018; 146:151-159. [DOI: 10.1016/j.eplepsyres.2018.08.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Revised: 07/17/2018] [Accepted: 08/06/2018] [Indexed: 01/01/2023]
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Liu H, Yang Z, Meng F, Huang L, Qu W, Hao H, Zhang J, Li L. Chronic vagus nerve stimulation reverses heart rhythm complexity in patients with drug-resistant epilepsy: An assessment with multiscale entropy analysis. Epilepsy Behav 2018; 83:168-174. [PMID: 29709876 DOI: 10.1016/j.yebeh.2018.03.035] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Revised: 03/22/2018] [Accepted: 03/26/2018] [Indexed: 12/16/2022]
Abstract
OBJECTIVE Vagus nerve stimulation (VNS) is an adjunctive treatment in drug-resistant epilepsy. The alterations in heart rate dynamics through VNS are not well understood. This study aimed to determine changes in heart rhythm complexity in association with VNS and to relate the findings to the outcome of VNS treatment in patients with drug-resistant epilepsy. METHODS We prospectively analyzed 32 patients with drug-resistant epilepsy, who underwent VNS implantation, and 32 age- and sex-matched healthy control subjects. The interictal heartbeat intervals were analyzed using the heart rhythm complexity with multiscale entropy (MSE) and traditional heart rate variability (HRV) analyses based on ambulatory 24-hour electrocardiograms (ECGs). RESULTS Patients had significantly decreased complexity indices (Slope 5, Area 1-5, Area 6-15, Area 6-20) on MSE analysis and decreased HRV measurements (standard deviation of the heartbeat interval (SDNN), square root of the mean of sum of squares of the differences between adjacent RR intervals (RMSSD), pNN50, very low frequency (VLF), low frequency (LF), high frequency (HF), total power (TP)) in time and frequency domain analyses. After one year of VNS treatment in patients with drug-resistant epilepsy, there was a trend in an elevated MSE profile with significant higher values between the scales 1 and 9. Vagus nerve stimulation induces a more significant increase of MSE in VNS responders than those in the nonresponders. The conventional HRV measurements did not change. CONCLUSION Our results suggest that heart rhythm complexity is impaired in patients with drug-resistant epilepsy, and this is at least partially reversed by VNS treatment. Furthermore, VNS-induced effects on heart rate complexity may be associated with the therapeutic response to VNS in patients with drug-resistant epilepsy.
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Affiliation(s)
- Hongyun Liu
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing 100084, China; Department of Biomedical Engineering, Chinese PLA General Hospital, Beijing 100853, China
| | - Zhao Yang
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing 100084, China
| | - Fangang Meng
- Beijing Neurosurgical Institute, 100050 Beijing, China; Neurosurgery, Beijing Tian Tan Hospital Capital Medical University, 100050 Beijing, China
| | - Lei Huang
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing 100084, China
| | - Wei Qu
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing 100084, China
| | - Hongwei Hao
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing 100084, China
| | - Jianguo Zhang
- Neurosurgery, Beijing Tian Tan Hospital Capital Medical University, 100050 Beijing, China
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing 100084, China; Man-Machine-Environment Engineering Institute, School of Aerospace Engineering, Tsinghua University, 100084 Beijing, China; Precision Medicine & Healthcare Research Center, Tsinghua-Berkeley Shenzhen Institute, 518055 Shenzhen, China; Center of Epilepsy, Beijing Institute for Brain Disorders, 100069 Beijing, China.
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