Electroencephalogram in cirrhotic children without clinical encephalopathy

Electroencephalogram in cirrhotic children without clinical encephalopathy | 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 Electroencephalogram in cirrhotic children without clinical encephalopathy Iraj Shahramian, Mohammad Hassan Mohammadi, Alireza Aminisefat, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4232587/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 Introduction Cirrhosis is one of the most common causes of hospitalization and death in children, so prevention of progressive liver diseases such as hepatic encephalopathy (HE) is critical. In addition to overt HE, subclinical hepatic encephalopathy (SHE) and mild hepatic encephalopathy (MHE) are stages of HE that can only be diagnosed by psychometric and neurophysiological tests, and with early diagnosis and treatment, daily functioning of patients will improve. Therefore, purpose of this study is determining electroencephalogram (EEG) findings in children with cirrhosis without clinical encephalopathy. Methods This study was conducted observationally at Amir Al Momenin Zabol Hospital, Zabol University of Medical Sciences, Iran. In this study, 50 children with cirrhosis without encephalopathy symptoms and 50 healthy children were examined for abnormal electroencephalogram findings. Finally, the data were analyzed using SPSS V22 software. Results The mean and standard deviation of study population age was 57.6 ± 76.17 months. Of a total of 50 children with cirrhosis, 21 (42%) had abnormal EEG findings, whereas no child in the healthy group had abnormal EEG findings. There was a significant association between abnormal EEG findings and older age (P = 0.001), underlying autoimmune hepatitis disease (P = 0.011), and abnormal (elevated) serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) .Children with cirrhosis who had abnormal EEG findings had a higher mean Pediatric End-Stage Liver Disease (PELD) score (18.1 ± 4.1) than patients with normal EEG findings (17.2 ± 3.7), but these findings was not statistically significant or remarkable ( P = 0.073). The sensitivity of EEG for predicting the severity of cirrhosis was estimated to be 70% and the specificity to be 65%. Conclusion The results of this study demonstrate that the higher sensitivity of EEG compared to the specificity in predicting the severity of cirrhosis indicates that EEG can be used to exclude severe cirrhosis or to screen cirrhotic patients at risk of deterioration than in confirming its diagnosis. Hepatic cirrhosis Electroencephalogram Children Introduction Cirrhosis is the terminal stage of chronic liver disease of various etiologies and causes more than 1 million deaths worldwide each year ( 1 ). Cirrhosis of the liver is a serious health problem, affecting approximately 160 million people in 2017 alone. Today, the prevalence of this disease is increasing, with the highest annual incidence in East Asia ( 2 , 3 ). The most common causes of chronic liver disease in children include neonatal liver disease, alpha-1 antitrypsin deficiency, autoimmune liver disease, cystic fibrosis, chronic viral hepatitis (hepatitis B), and nonalcoholic fatty liver disease (NAFLD), metabolic liver disease (galactosemia, fructosemia), Wilson's disease ( 4 – 7 ). Hepatic cirrhosis often accompanies portal hypertension, which is the most common cause of gastroesophageal varices, with a prevalence of 40–85% in cirrhotic patients. Also, visceral bleeding is one of the severe complications associated with cirrhosis and portal hypertension, with a prevalence of 20–76% ( 8 ). Cirrhosis can also lead to cognitive dysfunction. This association is linked to brain atrophy. Interestingly, studies have shown that both cerebral atrophy and abnormal EEG findings can independently predict cognitive decline in cirrhotic patients ( 9 ). EEG is a sensitive and fast method to identify brain disorders by recording brain electrical signals. Evidence has shown that EEG can be used as a sensitive and reliable method for screening brain and nerve disorders ( 10 ). Many studies have mentioned EEG abnormality as a primary diagnostic sign for brain dysfunction in the absence of overt hepatic encephalopathy (OHE) or minimal hepatic encephalopathy (MHE) ( 11 , 12 ). MHE is the mildest form of hepatic encephalopathy in which patients do not have obvious symptoms; but may have subtle and mild motor deficits along with cognitive impairment and impairment in neuropsychological tests, studies have shown that more than 50% of children with chronic liver disease have MHE, which in turn, it harms brain function and their activity in school, So these cases suggest the need for early identification and treatment( 13 , 14 ). The evidence shows that even in milder types of HE, the quality-of-life pattern, sleep and wakefulness pattern, balance, and interpersonal relationships of the patient are affected ( 15 ). However, although several strategies are available to describe HE in the early stages, there is limited data to predict OHE, and many of them are impractical in clinical practice ( 16 ). However, some studies have shown that performing EEG as patient follow-up has prognostic value for the occurrence of OHE attacks and mortality in cirrhotic patients ( 17 ). So, in patients with hepatic cirrhosis, changes in EEG are significantly associated with the severity of liver disease and the occurrence of HE, and it may be possible to use EEG in determining the prognosis of patients ( 18 ). However, although EEG has been widely studied and used in clinical practice, studies have also shown that this clinical tool is not useful for early detection of HE, as typical EEG changes occur only in patients with severe HE. It should also be noted that these changes are not specific to HE and are also observed in other metabolic diseases such as hyponatremia and uremic encephalopathy ( 19 , 20 ). Therefore, the present study was conducted to investigate EEG changes in children with liver cirrhosis and no clinical encephalopathy. Method 2.1. Patients The present study was conducted in an observational-analytical manner at Amir-al-momenin Hospital, Zabol University of Medical Sciences, Zabol, Iran, from March 2022 to January 2022. All children with hepatic cirrhosis who visited the hospital’s pediatric clinic during this period were evaluated. Inclusion criteria included age under 18 years, hepatic cirrhosis confirmed based on clinical examinations, biochemical findings, ultrasound and liver biopsy, absence of symptoms in favor of hepatic encephalopathy, and personal consent of the patient to perform EEG. 2.2. Exclusion Criteria Children with Chronic lung disease or any type of lung disease with respiratory failure (PaO2 50 mmHg), renal failure (serum creatinine level > 200 µmol/L), heart disease of any cause, history of focal neurological episode or any type of neurological diseases, psychiatric disorders, use of neuropsychiatric drugs in the past 6 months, various metabolic disorders such as hyponatremia or uremic encephalopathy, and lack of consent for EEG were excluded from the study. Finally, 50 children with cirrhosis were included in the study. At the same time, a control group of 50 healthy children was also tested. The Pediatric End-Stage Liver Disease (PELD) scoring system was used to determine disease severity and predict patient survival. The PELD score was calculated based on each patient's age, bilirubin, albumin, and INR. Patients with a score of 20 or more were included in the severe cirrhosis group, and patients with a score of less than 20 were included in the non-severe cirrhosis group. In addition, the project manager recorded the patient's demographic and anthropometric information, comorbidities, required laboratory information, and additional information using the developed checklist and entered it into the questionnaire. This project was approved by the Ethics Committee of Zabol University of medical sciences. The study method was explained to all subjects and/or partners and obtained written consent from them. 2.3. EEG assessment EEG was performed in rest condition while the patients were awake and closed-eyes using Neurofax EEG-4518, as previously described. The 10–20 international system was applied. Five electrodes were attached to the skin surface at T3, T4, O1, O2, and locations. The evaluation was performed for 100 seconds at frequencies from 0.53 to 35 Hz. 2.4. Statistical Analysis Data were collected using SPSS 22 software and percentages, means, and standard deviations were calculated after describing the data in frequency form. Chi-square and independent samples Student's t test were used for univariate analysis. A significant value of 0.05 was considered. Results In the present study, 50 children with hepatic cirrhosis and 50 healthy children were studied in the control group. The mean and standard deviation of the age of children with hepatic cirrhosis and healthy children were 65.4 ± 83.0 and 48.3 ± 69.2 months, respectively, which were not statistically significant. Also, 24 children with hepatic cirrhosis and 18 healthy children were boys. The mean and standard deviation of the PELD score among children with hepatic cirrhosis was 17.6 ± 3.8. The lowest and highest PELD scores were 12 and 27, respectively. The results of the study showed that the most common etiology of hepatic cirrhosis in the studied children was genetic-metabolic diseases (13 patients, 26%), Wilson disease (11 patients, 22%), and autoimmune hepatitis (10 patients, 20%). Also, 7 patients (14%) were diagnosed with cryptogenic cirrhosis, 6 patients (12%) with biliary atresia, and pancreatic cancer with liver metastases in 3 patients (6%). Additionally this study investigated that the serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALK P), total bilirubin, direct bilirubin, albumin, total protein, prothrombin time(PT), and partial thromboplastin time(PTT) were significantly different between cirrhotic and healthy children (Table 1 ). Out of a total of 50 children with hepatic cirrhosis, 21 children (42%) had abnormal findings in EEG, while none of the children in the healthy group had abnormal findings in EEG. Irregular spikes along with alpha waves were the most common EEG findings reported in 8 patients (16%). After that, fast waves (4 patients, 8%), slow and high voltage (4 patients, 8%), and slow with frequent epileptic discharge (2 patients, 4%) were the most frequent among the EEG findings in the studied patients. Also, irregular spikes along with delta and triphasic waves were observed in 4% and 2% of children with hepatic cirrhosis, respectively. Patients with abnormal EEG patterns had a significantly higher average age (62.1 ± 117.19 months) than patients with normal EEG (56.9 ± 58.3) (P = 0.001). We also observed that among the children with abnormal EEG findings, 16 (76.1%) were older than 7 years and only 5 (23.8%) were younger than 7 years. Abnormal EEG findings had no statistically significant association with patient gender (P = 0.578). Children with cirrhosis with abnormal EEG findings had a higher mean PELD score (18.1 ± 4.1) than patients with normal EEG findings (17.2 ± 3.7). The results also showed that 70% (7 patients) of patients with PELD score ≥ 20 had abnormal EEG findings, but these findings were not statistically significant (P = 0.073). The sensitivity of EEG for predicting the severity of cirrhosis was estimated to be 70% and the specificity to be 65%. A significant percentage of patients with abnormal EEG findings had abnormal serum levels of AST (13 patients, 61.9%) and ALT (47.6%). The mean serum levels of AST and ALT in patients with abnormal EEG findings (140.3 ± 256.5 and 135.3 ± 190.5) were significantly higher than in patients with normal EEG findings (135.4 ± 215.1 and 130.5 ± 157.3) (P = 0.010 and P = 0.030). Also, the results indicated that there is a statistically significant relationship between abnormal EEG findings and serum levels of ALK P (P = 0.464), Bili T (P = 0.774), D (P = 0.774), and Alb (P = 0.686). T.Pro (P = 0.549), PT (P = 0.171), and PTT (0.243) did not exist (Table 2 ). By examining the etiology of hepatic cirrhosis in the studied patients, it was found that among the patients with abnormal EEG findings, 8 patients (38%) were suffering from Autoimmune Hepatitis. 80% of patients with autoimmune hepatitis had abnormal findings in EEG(P = 0.011). No significant statistical association was observed between other types of cirrhosis etiology and abnormal EEG findings (Table 3 ). Table 1 Baseline and Demographic Characteristics of Children with Cirrhosis and Their Controls Parameters Cirrhotic Children (N = 50) Healthy Children (N = 50) P Value Mean (SD) Minimum - Maximum Mean (SD) Minimum - Maximum Age (mon) 83.0(65.4) 2-204 69.2(48.3) 2-156 0.233 PELD score 17.6(3.8) 12–27 Aspartate amino transferase (IU/L) 232.5(121.8) 38–419 32.5(9.6) 20–45 0.001 Alanine aminotransferase (IU/L) 171.3(116) 42–366 23.6(7.5) 12–38 < 0.001 Alkaline phosphatase (IU/L) 877.6(619.5) 141–2060 389(123.8) 211–575 < 0.001 Total bilirubin (mg/dL) 16.2(14.3) 1.5–39 0.9 (0.4) 0.5–2 < 0.001 Direct bilirubin (mg/dL) 5.7(5.7) 0.7–15 0.29 (0.25) 0.1–1 < 0.001 Albumin (g/dL) 2.8(0.6) 1.7–3.8 4.4 (0.5) 3.2–5 0.027 Total protein (g/dL) 5.0(0.8) 4-6.3 7 (0.8) 5.8–8.2 0.006 Prothrombin time (s) 27.6(9.3) 15–41 12.6 (1.07) 10–14 0.04 Partial thromboplastin time (s) 49.8(12.1) 28–66 33.7 (4.9) 30–45 0.01 Table 2 A Comparison of Different Clinical and Laboratory Parameters Between Cirrhotic Children with Normal and Abnormal EEG Profiles Parameters Electroencephalography P value Normal(N = 29) Abnormal(N = 21) Age (years) 7 > 21 5(23.8%) 0.001 7 ≤ 8 16(76.1%) Sex Male 15(51.7%) 9(42.8%) 0.578 Female 14(48.2%) 12(57.1%) PELD score 20 > 26(89.6%) 14(66.6%) 0.073 20 ≤ 3(10.3%) 7(33.3%) Aspartate amino transferase (IU/L) Normal 22(75.8%) 8(38.09%) 0.010 Abnormal 7(24.1%) 13(61.9%) Alanine aminotransferase (IU/L) Normal 24(82.7%)T 11(52.3%) 0.030 Abnormal 5(17.2%) 10(47.6%) Alkaline phosphatase (IU/L) Normal 25(86.2%) 16(76.1%) 0.464 Abnormal 4(13.7%) 5(23.8%) Albumin (g/dL) Normal 16(55.1%) 14(66.6%) 0.686 Abnormal 13(44.8%) 7(33.3%) Total protein (g/dL) Normal 24(82.7%) 18(85.7%) 0.549 Abnormal 5(17.2%) 3(14.2%) Total bilirubin (mg/dL) Normal 18(62.06%) 14(66.6%) 0.774 Abnormal 11(37.9%) 7(33.3%) Direct bilirubin (mg/dL) Normal 18(62.06%) 14(66.6%) 0.774 Abnormal 11(37.9%) 7(33.3%) Prothrombin time (s) Normal 24(82.7%) 17(80.9%) 0.117 Abnormal 5(17.2%) 4(19.04%) Partial thromboplastin time (s) Normal 27 (93.1%) 18(85.7%) 0.243 Abnormal 2(6.8%) 3(14.2%) Table 3 A Comparison of Different Etiology of Cirrhosis Between Cirrhotic Children with Normal and Abnormal EEG Profiles Etiology of Cirrhosis Electroencephalography P value Normal(N = 29) Abnormal(N = 21) Genetic-Metabolic diseases YES 11(37.9%) 2(9.5%) 0.095 NO 18(62.06%) 19(90.4%) Wilson YES 5(17.2%) 6(28.5%) 0.491 NO 24(82.7%) 15(71.4%) Autoimmune Hepatitis YES 2(6.8%) 8(38.09%) 0.011 NO 27(93.1%) 13(61.9%) Cryptogenic cirrhosis YES 5(17.2%) 2(9.5%) 0.684 NO 24(82.7%) 19(90.4%) Biliary atresia YES 5(17.2%) 1(4.7%) 0.380 NO 24(82.7%) 20(95.2%) Pancreatic cancer with metastasis to the liver YES 1(3.4%) 2(9.5%) 0.565 NO 28(96.5%) 19(90.4%) Discussion Cirrhosis is one of the most common causes of hospitalization and death in children, and prevention of progressive liver damage such as HE is critical for children. In addition to overt HE, SHE and MHE are stages of HE that can only be diagnosed by psychometric and neurophysiological tests, and early diagnosis and treatment improve patients' daily functioning ( 21 , 22 ). Therefore, this study aimed to determine the EEG findings in children with cirrhosis without clinical encephalopathy. Many studies have shown that EEG is a targeted and quantitative tool for diagnosing and evaluating treatment response in patients with hepatic cirrhosis with MHE, which improves the diagnosis of MHE by providing quantitative parameters of brain dysfunction ( 23 ). Little information is available on EEG findings in children with hepatic cirrhosis. In the present study, of a total of 50 children with hepatic cirrhosis, 21 children (42%) had abnormal EEG findings. The results of this study indicated that abnormal EEG findings in children with hepatic cirrhosis were significantly related to older age, underlying autoimmune hepatitis, and abnormal and elevated serum levels of liver enzymes AST and ALT. In line with the findings of the present study, Amodio et al. ( 17 ) in their study evaluated 296 patients with hepatic cirrhosis and showed that abnormal EEG findings were observed in 38% of patients, and there was no significant relationship between abnormal EEG findings and the etiology of hepatic cirrhosis. This study introduced EEG as a suitable tool to predict the occurrence and mortality of overt HE. Also, Quero et al. ( 24 ) showed in a study that the frequency of abnormal EEG findings in patients with liver cirrhosis was approximately 17%. In this study, the occurrence of SHE and abnormal EEG findings was significantly associated with the severity of liver disease and older age of the patient. Formentin et al. ( 25 ) also showed in a study that neuropsychological tests, including EEG, may play an important role in predicting HE. In this study, it was observed that patients with a history of HE suffered from significantly more severe liver dysfunction. EEG findings in children with cirrhosis showed that irregular spikes with alpha waves (8 patients, 16%) were the most common abnormal EEG finding. Additionally, alpha wave slowing was observed in 6 patients (12%). 8% of patients (4 patients) had a rapid background, and 4% of patients (2 patients) had epileptiform discharges. Consistent with the above findings, Patel et al. ( 26 ) showed in their study that the changes in frequency and amplitude of alpha waves in patients with hepatic cirrhosis were significantly higher than in the control group. This study found that slowing of alpha waves in the EEG is considered the first finding of MHE. One of the earliest findings of HE is a loss of alpha rhythm frequency, which causes the onset of a progressively slower rhythm. Marchetti et al. ( 18 ) also showed that the average incidence of overt HE patients was much slower than that of his MHE patients. Also, Assem et al. ( 27 ) showed in their evaluation that the frequency of EEG slowing in patients with liver cirrhosis was approximately 30%, and a significant association was observed between the severity of EEG slowing and the duration and severity of liver disease. Generally, EEG changes in HE can occur in the form of increased amplitude, low frequency waves, and triphasic waves. However, in the present study, only 2% of patients had triphasic waves. Despite the mentioned cases, there have been reports of HE manifests in the form of generalized seizures ( 28 , 29 ). The incidence of nonconvulsive status epilepticus in patients with liver cirrhosis is rare. However, there is evidence that it is important to consider the possibility of nonconvulsive status epilepticus, especially in high-grade HE ( 30 – 32 ). Studies have also shown that cerebral dysrhythmias often appear on the EEG as focal or generalized spikes/sharp wave discharges that resemble epileptic discharges. Mitra et al. ( 33 ) The study also showed that the frequency of cerebral dysrhythmias in patients with cirrhosis was approximately 24%. children with cirrhosis with abnormal EEG findings had a higher mean PELD score (18.1 ± 4.1) than patients with normal EEG findings (17.2 ± 3.7). The results also showed that 70% (7 patients) of patients with a PELD score of 20 or higher had abnormal EEG findings, but these findings were not statistically significant. Mitra et al. ( 33 ) By studying patients with liver cirrhosis and HE, it was shown that EEG findings may have an effective relationship with the severity of liver disease. Therefore, patients with abnormal brain waves were found to have significantly higher end-stage liver disease (MELD) scales than those with normal brain waves. Dasgupta et al. ( 34 ) Also, their study showed that EEG can be used as an available and inexpensive diagnostic tool in MHE and was positively correlated with CTP class severity and higher MELD score. Also, Montagnese et al. (37) showed in a study that performing electroencephalography in patients with liver cirrhosis in combination with MELD could improve the prognostic accuracy of the MELD score. Therefore, the combination of EEG and MELD score may be a suitable option for patients with liver cirrhosis. Yoo et al. (38) in contrast to the materials mentioned above Their research on patients with liver cirrhosis revealed a weak correlation between MELD score and HE. In cases of HE and ascites, relying solely on the MELD score for a liver transplant may result in a delay or even failure to receive the transplant in a timely manner. Conclusion The outcomes of the study showed that although this limited sample size did not allow us to detect the high specificity of EEG, the higher sensitivity of EEG compared to the specificity in predicting the severity of cirrhosis indicates that EEG is more useful to ruling out severe cirrhosis or to screen cirrhosis patients at risk of deterioration rather than confirming its diagnosis. Furthermore, the results of this study demonstrate that implementing EEG as a useful and targeted tool along with clinical and biochemical tests may be an appropriate option for the evaluation and follow-up of children with cirrhosis. Declarations Conflict of interest The authors declare that they have no conflict of interest. Ethical approval The project was found to be in accordance to the ethical principles and the national norms and standards for conducting Medical Research in Iran and evaluated by Research Ethics Committees of Zabol University of Medical Sciences. Notes The authors declare no competing financial interest. Author Contribution Amini sefat and shafiei sabet collected data and wrote the main parts. Afshari analyzed the data and statistics. Mohammadi helped to interpret eeg. Shahramian and ataollahi surveyed the whole study and guided us as gastroenterologists to make a sensible correlation between datas. Acknowledgement The authors thanks to zabol University of medical sciences and Amir Al Momenin Hospital for allowing us to collect data. We would like to express our sincere gratitude to the patients and their families. References Stroffolini T, Sagnelli E, Gaeta GB, Sagnelli C, Andriulli A, Brancaccio G, Pirisi M, Colloredo G, Morisco F, Furlan C, Almasio PL (2017) Characteristics of liver cirrhosis in Italy: evidence for a decreasing role of HCV etiology. Eur J Intern Med 38:68–72 Nault JC, Ningarhari M, Rebouissou S, Zucman-Rossi J (2019) The role of telomeres and telomerase in cirrhosis and liver cancer. Nat Reviews Gastroenterol Hepatol 16(9):544–558 Zhai M, Long J, Liu S, Liu C, Li L, Yang L, Li Y, Shu B (2021) The burden of liver cirrhosis and underlying etiologies: results from the global burden of disease study 2017. Aging 13(1):279 Akhan O, Akpinar E, Karcaaltincaba M, Haliloglu M, Akata D, Karaosmanoglu AD, Ozmen M (2009) Imaging findings of liver involvement of Wilson's disease. Eur J Radiol 69(1):147–155 McGoogan KE, Smith PB, Choi SS, Berman W, Jhaveri R (2010) Performance of the AST to platelet ratio index (APRI) as a noninvasive marker of fibrosis in pediatric patients with chronic viral hepatitis. J Pediatr Gastroenterol Nutr 50(3):344 Lebensztejn DM, Skiba E, Sobaniec-Lotowska M, Kaczmarski M (2005) A simple noninvasive index (APRI) predicts advanced liver fibrosis in children with chronic hepatitis B. Hepatology 41(6):1434–1435 Kelly D The Child with Chronic Liver Disease. InAtlas of Pediatric Hepatology 2018 (pp. 71–80). Springer, Cham Rahmani P, Farahmand F, Heidari G, Sayarifard A (2021) Noninvasive markers for esophageal varices in children with cirrhosis. Clin Experimental Pediatr 64(1):31 Amodio P, Pellegrini A, Amista P, Luise S, Del Piccolo F, Mapelli D, Montagnese S, Musto C, Valenti P, Gatta A (2003) Neuropsychological–neurophysiological alterations and brain atrophy in cirrhotic patients. Metab Brain Dis 18(1):63–78 Shahramian I, Mohammadi MH, Akbari A, Sargazi A, Delaramnasab M, Bazi A (2019) Electroencephalogram Abnormalities in Very Young Children with Acute Hepatitis A Infection: A Cross-Sectional Study. J Compr Pediatr. ;10(3) Morgan MY, Amodio P, Cook NA, Jackson CD, Kircheis G, Lauridsen MM, Montagnese S, Schiff S, Weissenborn K (2016) Qualifying and quantifying minimal hepatic encephalopathy. Metab Brain Dis 31(6):1217–1229 Direkze S, Jalan R (2015) Diagnosis and treatment of low-grade hepatic encephalopathy. Dig Dis 33(4):562–569 Srivastava A, Chaturvedi S, Gupta RK, Malik R, Mathias A, Jagannathan NR, Jain S, Pandey CM, Yachha SK, Rathore RK (2017) Minimal hepatic encephalopathy in children with chronic liver disease: prevalence, pathogenesis, and magnetic resonance-based diagnosis. J Hepatol 66(3):528–536 Mack CL, Zelko FA, Lokar J, Superina R, Alonso EM, Blei AT, Whitington PF (2006) Surgically restoring portal blood flow to the liver in children with primary extrahepatic portal vein thrombosis improves fluid neurocognitive ability. Pediatrics 117(3):e405–e412 Montagnese S, Bajaj JS (2019) Impact of hepatic encephalopathy in cirrhosis on quality-of-life issues. Drugs 79(1):11–16 Tapper EB (2019) Predicting overt hepatic encephalopathy for the population with cirrhosis. Hepatology 70(1):403–409 Amodio P, Del Piccolo F, Pettenò E, Mapelli D, Angeli P, Iemmolo R, Muraca M, Musto C, Gerunda G, Rizzo C, Merkel C (2001) Prevalence and prognostic value of quantified electroencephalogram (EEG) alterations in cirrhotic patients. J Hepatol 35(1):37–45 Marchetti P, D'Avanzo C, Orsato R, Montagnese S, Schiff S, Kaplan PW, Piccione F, Merkel C, Gatta A, Sparacino G, Toffolo GM (2011) Electroencephalography in patients with cirrhosis. Gastroenterology 141(5):1680–1689 Guerit JM, Amantini A, Fischer C, Kaplan PW, Mecarelli O, Schnitzler A, Ubiali E, Amodio P (2009) members of the ISHEN Commission on Neurophysiological Investigations. Neurophysiological investigations of hepatic encephalopathy: ISHEN practice guidelines. Liver Int 29(6):789–796 Xu XY, Ding HG, Li WG, Jia JD, Wei L, Duan ZP, Liu YL, Ling-Hu EQ, Zhuang H, Chinese Medical Association (2019) Chinese guidelines on management of hepatic encephalopathy in cirrhosis. World J Gastroenterol 25(36):5403 Sahney A, Wadhawan M (2022) Encephalopathy in cirrhosis: prevention and management. J Clin Experimental Hepatol 12(3):927–936 Dehghani SM, Imanieh MH, Haghighat M, Malekpour A, Falizkar Z (2013) Etiology and complications of liver cirrhosis in children: report of a single center from southern Iran. Middle East J Dig Dis (MEJDD) 5(1):41–46 Singh J, Sharma BC, Maharshi S, Puri V, Srivastava S (2016) Spectral electroencephalogram in liver cirrhosis with minimal hepatic encephalopathy before and after lactulose therapy. J Gastroenterol Hepatol 31(6):1203–1209 Quero JC, Hartmann IJ, Meulstee J, Hop WC, Schalm SW (1996) The diagnosis of subclinical hepatic encephalopathy in patients with cirrhosis using neuropsychological tests and automated electroencephalogram analysis. Hepatology 24(3):556–560 Formentin C, Zarantonello L, Mangini C, Frigo AC, Montagnese S, Merkel C (2021) Clinical, neuropsychological and neurophysiological indices and predictors of hepatic encephalopathy (HE). Liver Int 41(5):1070–1082 Patel NP, Chafekar ND, Sonwane PB (2019 Jun) Slowing of Alpha Waves on EEG, an Early Marker of Minimal Hepatic Encephalopathy. MVP J Med Sci 1:60–65 ASSEM, Sharif EI et al (2007) Diagnosis of subclinical hepatic encephalopathy in patients with liver cirrhosis Tanaka H, Ueda H, Kida Y, Hamagami H, Tsuji T, Ichinose M (2006) Hepatic encephalopathy with status epileptics: a case report. World J gastroenterology: WJG 12(11):1793 Ficker DM, Westmoreland BF, Sharbrough FW (1997) Epileptiform abnormalities in hepatic encephalopathy. J Clin Neurophysiol 14(3):230–234 Eleftheriadis N, Fourla E, Eleftheriadis D, Karlovasitou A (2003) Status epilepticus as a manifestation of hepatic encephalopathy. Acta Neurol Scand 107(2):142–144 Jo YM, Lee SW, Han SY, Baek YH, Ahn JH, Choi WJ, Lee JY, Kim SH, Yoon BA (2015) Nonconvulsive status epilepticus disguising as hepatic encephalopathy. World J Gastroenterology: WJG 21(16):5105 Newey CR, George P, Sarwal A, So N, Hantus S (2018) Electro-Radiological Observations of Grade III/IV Hepatic Encephalopathy Patients with Seizures. Neurocrit Care 28:97–103 Mitra LG, Rajput G, Saluja V, Kumar G (2021) EEG abnormality as a prognostic factor in cirrhotic patients with Grade III-IV hepatic encephalopathy requiring mechanical ventilation: A retrospective analysis. J Clin Translational Res 7(4):467 Dasgupta A, Debbarma A, Choudhury SK (2019) Evaluation of the Role of Electroencephalography in the Early Diagnosis of Minimal Hepatic Encephalopathy in Patients with Cirrhosis of Liver. J Evid Based Med Healthc 6:2945–2949 Montagnese S, De Rui M, Schiff S, Ceranto E, Valenti P, Angeli P, Cillo U, Zanus G, Gatta A, Amodio P, Merkel C (2015) Prognostic benefit of the addition of a quantitative index of hepatic encephalopathy to the MELD score: the MELD-EEG. Liver Int 35(1):58–64 Yoo HY, Edwin D PJ Thuluvath - The American journal of gastroenterology, 2003 – Elsevier 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4232587","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":290802397,"identity":"305edf8a-5d2a-40d7-8316-5b1bd9ef949e","order_by":0,"name":"Iraj Shahramian","email":"","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Iraj","middleName":"","lastName":"Shahramian","suffix":""},{"id":290802398,"identity":"604a7bec-7b2a-40d9-b939-0c074fbab199","order_by":1,"name":"Mohammad Hassan Mohammadi","email":"","orcid":"","institution":"Zabol University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"Hassan","lastName":"Mohammadi","suffix":""},{"id":290802399,"identity":"3763470a-34f8-40b6-8c90-76b3310431a5","order_by":2,"name":"Alireza Aminisefat","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYBACNhCRwCDBwMB8gIHhA0iEnYAWfrgWtgTGxhkgLcwEtEg2wO1LYGzmATEIaTE4wPx0w8MdFvb8bMzPH9v82ibPx8zA+OFjDj4tbGY3Es9IJM5sYzNszu27bdjGzMAsOXMbPi0MQC1tEgkG9xuAWnpuMwK1sDHz4tFif4D9G0iLvf0x9o/Nlj237QlqMTjAA7aFcQMbj2Ezw4/biYS1HOYpA2lJnHGMp3Bmb8Pt5DZmxmb8fjnevu3mz7Y6e/429g0ffvy5bTu/vfngh494tKDGAmMbmGzAox4D/CFF8SgYBaNgFIwUAAAYDVFWeWlJkgAAAABJRU5ErkJggg==","orcid":"","institution":"Zabol University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Alireza","middleName":"","lastName":"Aminisefat","suffix":""},{"id":290802400,"identity":"fbd125f3-3127-4b91-a053-181dd0dcef45","order_by":3,"name":"Negar shafiei sabet","email":"","orcid":"","institution":"Zabol University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Negar","middleName":"shafiei","lastName":"sabet","suffix":""},{"id":290802401,"identity":"7519f301-3422-4b18-9bf2-bedd2d07b089","order_by":4,"name":"Maryam Ataollahi","email":"","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"","lastName":"Ataollahi","suffix":""},{"id":290802402,"identity":"7623bc5b-2d28-4aa7-bbbb-a831d5403ab0","order_by":5,"name":"Mahdi Afshari","email":"","orcid":"","institution":"Zabol University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mahdi","middleName":"","lastName":"Afshari","suffix":""}],"badges":[],"createdAt":"2024-04-07 19:14:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4232587/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4232587/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56958056,"identity":"8c28c4a1-101f-416a-a6d0-d33637a0501f","added_by":"auto","created_at":"2024-05-22 16:32:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":452503,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4232587/v1/ed67b515-22a7-4eb4-875e-18e111798025.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Electroencephalogram in cirrhotic children without clinical encephalopathy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCirrhosis is the terminal stage of chronic liver disease of various etiologies and causes more than 1\u0026nbsp;million deaths worldwide each year (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Cirrhosis of the liver is a serious health problem, affecting approximately 160\u0026nbsp;million people in 2017 alone. Today, the prevalence of this disease is increasing, with the highest annual incidence in East Asia (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The most common causes of chronic liver disease in children include neonatal liver disease, alpha-1 antitrypsin deficiency, autoimmune liver disease, cystic fibrosis, chronic viral hepatitis (hepatitis B), and nonalcoholic fatty liver disease (NAFLD), metabolic liver disease (galactosemia, fructosemia), Wilson's disease (\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHepatic cirrhosis often accompanies portal hypertension, which is the most common cause of gastroesophageal varices, with a prevalence of 40\u0026ndash;85% in cirrhotic patients. Also, visceral bleeding is one of the severe complications associated with cirrhosis and portal hypertension, with a prevalence of 20\u0026ndash;76% (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Cirrhosis can also lead to cognitive dysfunction. This association is linked to brain atrophy. Interestingly, studies have shown that both cerebral atrophy and abnormal EEG findings can independently predict cognitive decline in cirrhotic patients (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEEG is a sensitive and fast method to identify brain disorders by recording brain electrical signals. Evidence has shown that EEG can be used as a sensitive and reliable method for screening brain and nerve disorders (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Many studies have mentioned EEG abnormality as a primary diagnostic sign for brain dysfunction in the absence of overt hepatic encephalopathy (OHE) or minimal hepatic encephalopathy (MHE) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). MHE is the mildest form of hepatic encephalopathy in which patients do not have obvious symptoms; but may have subtle and mild motor deficits along with cognitive impairment and impairment in neuropsychological tests, studies have shown that more than 50% of children with chronic liver disease have MHE, which in turn, it harms brain function and their activity in school, So these cases suggest the need for early identification and treatment(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The evidence shows that even in milder types of HE, the quality-of-life pattern, sleep and wakefulness pattern, balance, and interpersonal relationships of the patient are affected (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, although several strategies are available to describe HE in the early stages, there is limited data to predict OHE, and many of them are impractical in clinical practice (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). However, some studies have shown that performing EEG as patient follow-up has prognostic value for the occurrence of OHE attacks and mortality in cirrhotic patients (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). So, in patients with hepatic cirrhosis, changes in EEG are significantly associated with the severity of liver disease and the occurrence of HE, and it may be possible to use EEG in determining the prognosis of patients (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, although EEG has been widely studied and used in clinical practice, studies have also shown that this clinical tool is not useful for early detection of HE, as typical EEG changes occur only in patients with severe HE. It should also be noted that these changes are not specific to HE and are also observed in other metabolic diseases such as hyponatremia and uremic encephalopathy (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTherefore, the present study was conducted to investigate EEG changes in children with liver cirrhosis and no clinical encephalopathy.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Patients\u003c/h2\u003e \u003cp\u003eThe present study was conducted in an observational-analytical manner at Amir-al-momenin Hospital, Zabol University of Medical Sciences, Zabol, Iran, from March 2022 to January 2022. All children with hepatic cirrhosis who visited the hospital\u0026rsquo;s pediatric clinic during this period were evaluated. Inclusion criteria included age under 18 years, hepatic cirrhosis confirmed based on clinical examinations, biochemical findings, ultrasound and liver biopsy, absence of symptoms in favor of hepatic encephalopathy, and personal consent of the patient to perform EEG.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Exclusion Criteria\u003c/h2\u003e \u003cp\u003eChildren with Chronic lung disease or any type of lung disease with respiratory failure (PaO2\u0026thinsp;\u0026lt;\u0026thinsp;60 mmHg and/or PaCo2\u0026thinsp;\u0026gt;\u0026thinsp;50 mmHg), renal failure (serum creatinine level\u0026thinsp;\u0026gt;\u0026thinsp;200 \u0026micro;mol/L), heart disease of any cause, history of focal neurological episode or any type of neurological diseases, psychiatric disorders, use of neuropsychiatric drugs in the past 6 months, various metabolic disorders such as hyponatremia or uremic encephalopathy, and lack of consent for EEG were excluded from the study.\u003c/p\u003e \u003cp\u003eFinally, 50 children with cirrhosis were included in the study. At the same time, a control group of 50 healthy children was also tested. The Pediatric End-Stage Liver Disease (PELD) scoring system was used to determine disease severity and predict patient survival. The PELD score was calculated based on each patient's age, bilirubin, albumin, and INR. Patients with a score of 20 or more were included in the severe cirrhosis group, and patients with a score of less than 20 were included in the non-severe cirrhosis group. In addition, the project manager recorded the patient's demographic and anthropometric information, comorbidities, required laboratory information, and additional information using the developed checklist and entered it into the questionnaire.\u003c/p\u003e \u003cp\u003e This project was approved by the Ethics Committee of Zabol University of medical sciences. The study method was explained to all subjects and/or partners and obtained written consent from them.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. EEG assessment\u003c/h2\u003e \u003cp\u003eEEG was performed in rest condition while the patients were awake and closed-eyes using Neurofax EEG-4518, as previously described. The 10\u0026ndash;20 international system was applied. Five electrodes were attached to the skin surface at T3, T4, O1, O2, and locations. The evaluation was performed for 100 seconds at frequencies from 0.53 to 35 Hz.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical Analysis\u003c/h2\u003e \u003cp\u003eData were collected using SPSS 22 software and percentages, means, and standard deviations were calculated after describing the data in frequency form. Chi-square and independent samples Student's t test were used for univariate analysis. A significant value of 0.05 was considered.\u003c/p\u003e "},{"header":"Results","content":"\u003cp\u003eIn the present study, 50 children with hepatic cirrhosis and 50 healthy children were studied in the control group.\u003c/p\u003e \u003cp\u003eThe mean and standard deviation of the age of children with hepatic cirrhosis and healthy children were 65.4\u0026thinsp;\u0026plusmn;\u0026thinsp;83.0 and 48.3\u0026thinsp;\u0026plusmn;\u0026thinsp;69.2 months, respectively, which were not statistically significant. Also, 24 children with hepatic cirrhosis and 18 healthy children were boys. The mean and standard deviation of the PELD score among children with hepatic cirrhosis was 17.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8. The lowest and highest PELD scores were 12 and 27, respectively. The results of the study showed that the most common etiology of hepatic cirrhosis in the studied children was genetic-metabolic diseases (13 patients, 26%), Wilson disease (11 patients, 22%), and autoimmune hepatitis (10 patients, 20%). Also, 7 patients (14%) were diagnosed with cryptogenic cirrhosis, 6 patients (12%) with biliary atresia, and pancreatic cancer with liver metastases in 3 patients (6%). Additionally this study investigated that the serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALK P), total bilirubin, direct bilirubin, albumin, total protein, prothrombin time(PT), and partial thromboplastin time(PTT) were significantly different between cirrhotic and healthy children (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOut of a total of 50 children with hepatic cirrhosis, 21 children (42%) had abnormal findings in EEG, while none of the children in the healthy group had abnormal findings in EEG. Irregular spikes along with alpha waves were the most common EEG findings reported in 8 patients (16%). After that, fast waves (4 patients, 8%), slow and high voltage (4 patients, 8%), and slow with frequent epileptic discharge (2 patients, 4%) were the most frequent among the EEG findings in the studied patients. Also, irregular spikes along with delta and triphasic waves were observed in 4% and 2% of children with hepatic cirrhosis, respectively.\u003c/p\u003e \u003cp\u003ePatients with abnormal EEG patterns had a significantly higher average age (62.1\u0026thinsp;\u0026plusmn;\u0026thinsp;117.19 months) than patients with normal EEG (56.9\u0026thinsp;\u0026plusmn;\u0026thinsp;58.3) (P\u0026thinsp;=\u0026thinsp;0.001). We also observed that among the children with abnormal EEG findings, 16 (76.1%) were older than 7 years and only 5 (23.8%) were younger than 7 years. Abnormal EEG findings had no statistically significant association with patient gender (P\u0026thinsp;=\u0026thinsp;0.578). Children with cirrhosis with abnormal EEG findings had a higher mean PELD score (18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1) than patients with normal EEG findings (17.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7). The results also showed that 70% (7 patients) of patients with PELD score\u0026thinsp;\u0026ge;\u0026thinsp;20 had abnormal EEG findings, but these findings were not statistically significant (P\u0026thinsp;=\u0026thinsp;0.073). The sensitivity of EEG for predicting the severity of cirrhosis was estimated to be 70% and the specificity to be 65%.\u003c/p\u003e \u003cp\u003eA significant percentage of patients with abnormal EEG findings had abnormal serum levels of AST (13 patients, 61.9%) and ALT (47.6%). The mean serum levels of AST and ALT in patients with abnormal EEG findings (140.3\u0026thinsp;\u0026plusmn;\u0026thinsp;256.5 and 135.3\u0026thinsp;\u0026plusmn;\u0026thinsp;190.5) were significantly higher than in patients with normal EEG findings (135.4\u0026thinsp;\u0026plusmn;\u0026thinsp;215.1 and 130.5\u0026thinsp;\u0026plusmn;\u0026thinsp;157.3) (P\u0026thinsp;=\u0026thinsp;0.010 and P\u0026thinsp;=\u0026thinsp;0.030). Also, the results indicated that there is a statistically significant relationship between abnormal EEG findings and serum levels of ALK P (P\u0026thinsp;=\u0026thinsp;0.464), Bili T (P\u0026thinsp;=\u0026thinsp;0.774), D (P\u0026thinsp;=\u0026thinsp;0.774), and Alb (P\u0026thinsp;=\u0026thinsp;0.686). T.Pro (P\u0026thinsp;=\u0026thinsp;0.549), PT (P\u0026thinsp;=\u0026thinsp;0.171), and PTT (0.243) did not exist (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBy examining the etiology of hepatic cirrhosis in the studied patients, it was found that among the patients with abnormal EEG findings, 8 patients (38%) were suffering from Autoimmune Hepatitis. 80% of patients with autoimmune hepatitis had abnormal findings in EEG(P\u0026thinsp;=\u0026thinsp;0.011). No significant statistical association was observed between other types of cirrhosis etiology and abnormal EEG findings (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\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\u003eBaseline and Demographic Characteristics of Children with Cirrhosis and Their Controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCirrhotic Children (N\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHealthy Children (N\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinimum - Maximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMinimum - Maximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (mon)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83.0(65.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2-204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69.2(48.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2-156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePELD score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.6(3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u0026ndash;27\u003c/p\u003e \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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspartate amino transferase (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e232.5(121.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u0026ndash;419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.5(9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlanine aminotransferase (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e171.3(116)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u0026ndash;366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.6(7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026ndash;38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlkaline phosphatase (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e877.6(619.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e141\u0026ndash;2060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e389(123.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e211\u0026ndash;575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.2(14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirect bilirubin (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.7(5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.29 (0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.8(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7\u0026ndash;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.4 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.2\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal protein (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.0(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4-6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.8\u0026ndash;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProthrombin time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.6(9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u0026ndash;41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.6 (1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u0026ndash;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartial thromboplastin time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.8(12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u0026ndash;66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.7 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \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\u003eA Comparison of Different Clinical and Laboratory Parameters Between Cirrhotic Children with Normal and Abnormal EEG Profiles\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 \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eElectroencephalography\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal(N\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAbnormal(N\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 \u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 \u0026le;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(76.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(51.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(42.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(48.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(57.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePELD score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 \u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(89.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(66.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 \u0026le;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAspartate amino transferase (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(75.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(38.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(24.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(61.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlanine aminotransferase (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(82.7%)T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(52.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(47.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlkaline phosphatase (IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(86.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(76.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(23.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlbumin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(55.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(66.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(44.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal protein (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(82.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(85.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(14.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal bilirubin (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(62.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(66.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(37.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDirect bilirubin (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(62.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(66.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(37.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eProthrombin time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(82.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(80.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(19.04%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePartial thromboplastin time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (93.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(85.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(14.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\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\u003eA Comparison of Different Etiology of Cirrhosis Between Cirrhotic Children with Normal and Abnormal EEG Profiles\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eEtiology of Cirrhosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eElectroencephalography\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal(N\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAbnormal(N\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGenetic-Metabolic diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(37.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(62.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(90.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWilson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(28.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(82.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(71.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAutoimmune Hepatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(38.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(93.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(61.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCryptogenic cirrhosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(82.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(90.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBiliary atresia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(82.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(95.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePancreatic cancer with metastasis to the liver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28(96.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(90.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"Discussion","content":" \u003cp\u003eCirrhosis is one of the most common causes of hospitalization and death in children, and prevention of progressive liver damage such as HE is critical for children. In addition to overt HE, SHE and MHE are stages of HE that can only be diagnosed by psychometric and neurophysiological tests, and early diagnosis and treatment improve patients' daily functioning (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Therefore, this study aimed to determine the EEG findings in children with cirrhosis without clinical encephalopathy.\u003c/p\u003e \u003cp\u003eMany studies have shown that EEG is a targeted and quantitative tool for diagnosing and evaluating treatment response in patients with hepatic cirrhosis with MHE, which improves the diagnosis of MHE by providing quantitative parameters of brain dysfunction (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Little information is available on EEG findings in children with hepatic cirrhosis. In the present study, of a total of 50 children with hepatic cirrhosis, 21 children (42%) had abnormal EEG findings. The results of this study indicated that abnormal EEG findings in children with hepatic cirrhosis were significantly related to older age, underlying autoimmune hepatitis, and abnormal and elevated serum levels of liver enzymes AST and ALT. In line with the findings of the present study, Amodio et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) in their study evaluated 296 patients with hepatic cirrhosis and showed that abnormal EEG findings were observed in 38% of patients, and there was no significant relationship between abnormal EEG findings and the etiology of hepatic cirrhosis. This study introduced EEG as a suitable tool to predict the occurrence and mortality of overt HE. Also, Quero et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) showed in a study that the frequency of abnormal EEG findings in patients with liver cirrhosis was approximately 17%. In this study, the occurrence of SHE and abnormal EEG findings was significantly associated with the severity of liver disease and older age of the patient. Formentin et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) also showed in a study that neuropsychological tests, including EEG, may play an important role in predicting HE. In this study, it was observed that patients with a history of HE suffered from significantly more severe liver dysfunction.\u003c/p\u003e \u003cp\u003eEEG findings in children with cirrhosis showed that irregular spikes with alpha waves (8 patients, 16%) were the most common abnormal EEG finding. Additionally, alpha wave slowing was observed in 6 patients (12%). 8% of patients (4 patients) had a rapid background, and 4% of patients (2 patients) had epileptiform discharges. Consistent with the above findings, Patel et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) showed in their study that the changes in frequency and amplitude of alpha waves in patients with hepatic cirrhosis were significantly higher than in the control group. This study found that slowing of alpha waves in the EEG is considered the first finding of MHE. One of the earliest findings of HE is a loss of alpha rhythm frequency, which causes the onset of a progressively slower rhythm. Marchetti et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) also showed that the average incidence of overt HE patients was much slower than that of his MHE patients. Also, Assem et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) showed in their evaluation that the frequency of EEG slowing in patients with liver cirrhosis was approximately 30%, and a significant association was observed between the severity of EEG slowing and the duration and severity of liver disease.\u003c/p\u003e \u003cp\u003eGenerally, EEG changes in HE can occur in the form of increased amplitude, low frequency waves, and triphasic waves. However, in the present study, only 2% of patients had triphasic waves.\u003c/p\u003e \u003cp\u003eDespite the mentioned cases, there have been reports of HE manifests in the form of generalized seizures (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). The incidence of nonconvulsive status epilepticus in patients with liver cirrhosis is rare. However, there is evidence that it is important to consider the possibility of nonconvulsive status epilepticus, especially in high-grade HE (\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Studies have also shown that cerebral dysrhythmias often appear on the EEG as focal or generalized spikes/sharp wave discharges that resemble epileptic discharges. Mitra et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) The study also showed that the frequency of cerebral dysrhythmias in patients with cirrhosis was approximately 24%. children with cirrhosis with abnormal EEG findings had a higher mean PELD score (18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1) than patients with normal EEG findings (17.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7). The results also showed that 70% (7 patients) of patients with a PELD score of 20 or higher had abnormal EEG findings, but these findings were not statistically significant.\u003c/p\u003e \u003cp\u003eMitra et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) By studying patients with liver cirrhosis and HE, it was shown that EEG findings may have an effective relationship with the severity of liver disease. Therefore, patients with abnormal brain waves were found to have significantly higher end-stage liver disease (MELD) scales than those with normal brain waves. Dasgupta et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) Also, their study showed that EEG can be used as an available and inexpensive diagnostic tool in MHE and was positively correlated with CTP class severity and higher MELD score. Also, Montagnese et al. (37) showed in a study that performing electroencephalography in patients with liver cirrhosis in combination with MELD could improve the prognostic accuracy of the MELD score. Therefore, the combination of EEG and MELD score may be a suitable option for patients with liver cirrhosis. Yoo et al. (38) in contrast to the materials mentioned above Their research on patients with liver cirrhosis revealed a weak correlation between MELD score and HE. In cases of HE and ascites, relying solely on the MELD score for a liver transplant may result in a delay or even failure to receive the transplant in a timely manner.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eThe outcomes of the study showed that although this limited sample size did not allow us to detect the high specificity of EEG, the higher sensitivity of EEG compared to the specificity in predicting the severity of cirrhosis indicates that EEG is more useful to ruling out severe cirrhosis or to screen cirrhosis patients at risk of deterioration rather than confirming its diagnosis. Furthermore, the results of this study demonstrate that implementing EEG as a useful and targeted tool along with clinical and biochemical tests may be an appropriate option for the evaluation and follow-up of children with cirrhosis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e The project was found to be in accordance to the ethical principles and the national norms and standards for conducting Medical Research in Iran and evaluated by Research Ethics Committees of Zabol University of Medical Sciences.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eNotes\u003c/h2\u003e \u003cp\u003eThe authors declare no competing financial interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAmini sefat and shafiei sabet collected data and wrote the main parts. Afshari analyzed the data and statistics. Mohammadi helped to interpret eeg. Shahramian and ataollahi surveyed the whole study and guided us as gastroenterologists to make a sensible correlation between datas.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thanks to zabol University of medical sciences and Amir Al Momenin Hospital for allowing us to collect data. We would like to express our sincere gratitude to the patients and their families.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStroffolini T, Sagnelli E, Gaeta GB, Sagnelli C, Andriulli A, Brancaccio G, Pirisi M, Colloredo G, Morisco F, Furlan C, Almasio PL (2017) Characteristics of liver cirrhosis in Italy: evidence for a decreasing role of HCV etiology. Eur J Intern Med 38:68\u0026ndash;72\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNault JC, Ningarhari M, Rebouissou S, Zucman-Rossi J (2019) The role of telomeres and telomerase in cirrhosis and liver cancer. Nat Reviews Gastroenterol Hepatol 16(9):544\u0026ndash;558\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhai M, Long J, Liu S, Liu C, Li L, Yang L, Li Y, Shu B (2021) The burden of liver cirrhosis and underlying etiologies: results from the global burden of disease study 2017. Aging 13(1):279\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkhan O, Akpinar E, Karcaaltincaba M, Haliloglu M, Akata D, Karaosmanoglu AD, Ozmen M (2009) Imaging findings of liver involvement of Wilson's disease. Eur J Radiol 69(1):147\u0026ndash;155\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGoogan KE, Smith PB, Choi SS, Berman W, Jhaveri R (2010) Performance of the AST to platelet ratio index (APRI) as a noninvasive marker of fibrosis in pediatric patients with chronic viral hepatitis. J Pediatr Gastroenterol Nutr 50(3):344\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLebensztejn DM, Skiba E, Sobaniec-Lotowska M, Kaczmarski M (2005) A simple noninvasive index (APRI) predicts advanced liver fibrosis in children with chronic hepatitis B. Hepatology 41(6):1434\u0026ndash;1435\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKelly D The Child with Chronic Liver Disease. InAtlas of Pediatric Hepatology 2018 (pp. 71\u0026ndash;80). Springer, Cham\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahmani P, Farahmand F, Heidari G, Sayarifard A (2021) Noninvasive markers for esophageal varices in children with cirrhosis. Clin Experimental Pediatr 64(1):31\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmodio P, Pellegrini A, Amista P, Luise S, Del Piccolo F, Mapelli D, Montagnese S, Musto C, Valenti P, Gatta A (2003) Neuropsychological\u0026ndash;neurophysiological alterations and brain atrophy in cirrhotic patients. Metab Brain Dis 18(1):63\u0026ndash;78\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShahramian I, Mohammadi MH, Akbari A, Sargazi A, Delaramnasab M, Bazi A (2019) Electroencephalogram Abnormalities in Very Young Children with Acute Hepatitis A Infection: A Cross-Sectional Study. J Compr Pediatr. ;10(3)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorgan MY, Amodio P, Cook NA, Jackson CD, Kircheis G, Lauridsen MM, Montagnese S, Schiff S, Weissenborn K (2016) Qualifying and quantifying minimal hepatic encephalopathy. Metab Brain Dis 31(6):1217\u0026ndash;1229\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDirekze S, Jalan R (2015) Diagnosis and treatment of low-grade hepatic encephalopathy. Dig Dis 33(4):562\u0026ndash;569\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSrivastava A, Chaturvedi S, Gupta RK, Malik R, Mathias A, Jagannathan NR, Jain S, Pandey CM, Yachha SK, Rathore RK (2017) Minimal hepatic encephalopathy in children with chronic liver disease: prevalence, pathogenesis, and magnetic resonance-based diagnosis. J Hepatol 66(3):528\u0026ndash;536\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMack CL, Zelko FA, Lokar J, Superina R, Alonso EM, Blei AT, Whitington PF (2006) Surgically restoring portal blood flow to the liver in children with primary extrahepatic portal vein thrombosis improves fluid neurocognitive ability. Pediatrics 117(3):e405\u0026ndash;e412\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMontagnese S, Bajaj JS (2019) Impact of hepatic encephalopathy in cirrhosis on quality-of-life issues. Drugs 79(1):11\u0026ndash;16\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTapper EB (2019) Predicting overt hepatic encephalopathy for the population with cirrhosis. Hepatology 70(1):403\u0026ndash;409\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmodio P, Del Piccolo F, Petten\u0026ograve; E, Mapelli D, Angeli P, Iemmolo R, Muraca M, Musto C, Gerunda G, Rizzo C, Merkel C (2001) Prevalence and prognostic value of quantified electroencephalogram (EEG) alterations in cirrhotic patients. J Hepatol 35(1):37\u0026ndash;45\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarchetti P, D'Avanzo C, Orsato R, Montagnese S, Schiff S, Kaplan PW, Piccione F, Merkel C, Gatta A, Sparacino G, Toffolo GM (2011) Electroencephalography in patients with cirrhosis. Gastroenterology 141(5):1680\u0026ndash;1689\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuerit JM, Amantini A, Fischer C, Kaplan PW, Mecarelli O, Schnitzler A, Ubiali E, Amodio P (2009) members of the ISHEN Commission on Neurophysiological Investigations. Neurophysiological investigations of hepatic encephalopathy: ISHEN practice guidelines. Liver Int 29(6):789\u0026ndash;796\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu XY, Ding HG, Li WG, Jia JD, Wei L, Duan ZP, Liu YL, Ling-Hu EQ, Zhuang H, Chinese Medical Association (2019) Chinese guidelines on management of hepatic encephalopathy in cirrhosis. World J Gastroenterol 25(36):5403\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSahney A, Wadhawan M (2022) Encephalopathy in cirrhosis: prevention and management. J Clin Experimental Hepatol 12(3):927\u0026ndash;936\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDehghani SM, Imanieh MH, Haghighat M, Malekpour A, Falizkar Z (2013) Etiology and complications of liver cirrhosis in children: report of a single center from southern Iran. Middle East J Dig Dis (MEJDD) 5(1):41\u0026ndash;46\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh J, Sharma BC, Maharshi S, Puri V, Srivastava S (2016) Spectral electroencephalogram in liver cirrhosis with minimal hepatic encephalopathy before and after lactulose therapy. J Gastroenterol Hepatol 31(6):1203\u0026ndash;1209\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuero JC, Hartmann IJ, Meulstee J, Hop WC, Schalm SW (1996) The diagnosis of subclinical hepatic encephalopathy in patients with cirrhosis using neuropsychological tests and automated electroencephalogram analysis. Hepatology 24(3):556\u0026ndash;560\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFormentin C, Zarantonello L, Mangini C, Frigo AC, Montagnese S, Merkel C (2021) Clinical, neuropsychological and neurophysiological indices and predictors of hepatic encephalopathy (HE). Liver Int 41(5):1070\u0026ndash;1082\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatel NP, Chafekar ND, Sonwane PB (2019 Jun) Slowing of Alpha Waves on EEG, an Early Marker of Minimal Hepatic Encephalopathy. MVP J Med Sci 1:60\u0026ndash;65\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eASSEM, Sharif EI et al (2007) Diagnosis of subclinical hepatic encephalopathy in patients with liver cirrhosis\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTanaka H, Ueda H, Kida Y, Hamagami H, Tsuji T, Ichinose M (2006) Hepatic encephalopathy with status epileptics: a case report. World J gastroenterology: WJG 12(11):1793\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFicker DM, Westmoreland BF, Sharbrough FW (1997) Epileptiform abnormalities in hepatic encephalopathy. J Clin Neurophysiol 14(3):230\u0026ndash;234\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEleftheriadis N, Fourla E, Eleftheriadis D, Karlovasitou A (2003) Status epilepticus as a manifestation of hepatic encephalopathy. Acta Neurol Scand 107(2):142\u0026ndash;144\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJo YM, Lee SW, Han SY, Baek YH, Ahn JH, Choi WJ, Lee JY, Kim SH, Yoon BA (2015) Nonconvulsive status epilepticus disguising as hepatic encephalopathy. World J Gastroenterology: WJG 21(16):5105\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewey CR, George P, Sarwal A, So N, Hantus S (2018) Electro-Radiological Observations of Grade III/IV Hepatic Encephalopathy Patients with Seizures. Neurocrit Care 28:97\u0026ndash;103\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitra LG, Rajput G, Saluja V, Kumar G (2021) EEG abnormality as a prognostic factor in cirrhotic patients with Grade III-IV hepatic encephalopathy requiring mechanical ventilation: A retrospective analysis. J Clin Translational Res 7(4):467\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDasgupta A, Debbarma A, Choudhury SK (2019) Evaluation of the Role of Electroencephalography in the Early Diagnosis of Minimal Hepatic Encephalopathy in Patients with Cirrhosis of Liver. J Evid Based Med Healthc 6:2945\u0026ndash;2949\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMontagnese S, De Rui M, Schiff S, Ceranto E, Valenti P, Angeli P, Cillo U, Zanus G, Gatta A, Amodio P, Merkel C (2015) Prognostic benefit of the addition of a quantitative index of hepatic encephalopathy to the MELD score: the MELD-EEG. Liver Int 35(1):58\u0026ndash;64\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoo HY, Edwin D PJ Thuluvath - The American journal of gastroenterology, 2003 \u0026ndash; Elsevier\u003c/span\u003e\u003c/li\u003e\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":"Hepatic cirrhosis, Electroencephalogram, Children","lastPublishedDoi":"10.21203/rs.3.rs-4232587/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4232587/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction\u003c/h2\u003e \u003cp\u003eCirrhosis is one of the most common causes of hospitalization and death in children, so prevention of progressive liver diseases such as hepatic encephalopathy (HE) is critical. In addition to overt HE, subclinical hepatic encephalopathy (SHE) and mild hepatic encephalopathy (MHE) are stages of HE that can only be diagnosed by psychometric and neurophysiological tests, and with early diagnosis and treatment, daily functioning of patients will improve. Therefore, purpose of this study is determining electroencephalogram (EEG) findings in children with cirrhosis without clinical encephalopathy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study was conducted observationally at Amir Al Momenin Zabol Hospital, Zabol University of Medical Sciences, Iran. In this study, 50 children with cirrhosis without encephalopathy symptoms and 50 healthy children were examined for abnormal electroencephalogram findings. Finally, the data were analyzed using SPSS V22 software.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean and standard deviation of study population age was 57.6\u0026thinsp;\u0026plusmn;\u0026thinsp;76.17 months. Of a total of 50 children with cirrhosis, 21 (42%) had abnormal EEG findings, whereas no child in the healthy group had abnormal EEG findings. There was a significant association between abnormal EEG findings and older age (P\u0026thinsp;=\u0026thinsp;0.001), underlying autoimmune hepatitis disease (P\u0026thinsp;=\u0026thinsp;0.011), and abnormal (elevated) serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) .Children with cirrhosis who had abnormal EEG findings had a higher mean Pediatric End-Stage Liver Disease (PELD) score (18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1) than patients with normal EEG findings (17.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7), but these findings was not statistically significant or remarkable ( P\u0026thinsp;=\u0026thinsp;0.073). The sensitivity of EEG for predicting the severity of cirrhosis was estimated to be 70% and the specificity to be 65%.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe results of this study demonstrate that the higher sensitivity of EEG compared to the specificity in predicting the severity of cirrhosis indicates that EEG can be used to exclude severe cirrhosis or to screen cirrhotic patients at risk of deterioration than in confirming its diagnosis.\u003c/p\u003e","manuscriptTitle":"Electroencephalogram in cirrhotic children without clinical encephalopathy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-16 19:09:30","doi":"10.21203/rs.3.rs-4232587/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":"b716db16-2db9-4172-a879-5f9ef1047ccd","owner":[],"postedDate":"April 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-22T16:24:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-16 19:09:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4232587","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4232587","identity":"rs-4232587","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}