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Encephalopathies

Q: What are the different types of encephalopathies?

Encephalopathies encompass a diverse range of disorders that affect the brain, including metabolic encephalopathies, infectious encephalopathies, toxic encephalopathies, and traumatic encephalopathies. Each type has its own unique underlying causes, symptoms, and clinical presentation, requiring tailored diagnostic and management approaches.

Q: What are some common causes of encephalopathies?

Encephalopathies can be caused by a variety of factors, including infections (e.g., viral, bacterial, or prion-induced), metabolic disorders, toxin exposure, vascular events, and traumatic brain injuries. Identifying the underlying cause is crucial for guiding appropriate treatment and management strategies for patients with encephalopathies.

Encephalopathies are a diverse group of disorders affecting the brain that can lead to cognitive, behavioral, and neurological impairments.
These complex conditions involve structural, metabolic, or functional abnormalities in the brain, often with progressive or degenerative features.
Encephalopathies can have a wide range of underlying causes, including genetic factors, infections, toxins, and vascular or traumatic injuries.
Accurate diagnosis and effective management of encephalopathies require a multidisciplinary approach, drawing on advances in neuroimaging, biochemical testing, and enectic analysis.
Reasearchers utilzing PubComapre.ai can streamline their encephalopathy studies by quickly locating the best research protocols from scholarly publications, preprints, and patents, helping to improve reproducibility and accelerate scientific progress in this critical area of neurology.

Most cited protocols related to «Encephalopathies»

Balance Disorders in Rehabilitation Patients

A hundred fifteen patients (53 men and 62 women), aged 62.7 years ± 16 (standard deviation, SD), were studied. They represent a convenience sample of patients with balance disorders, recruited with a consecutive sampling method. Patient diagnosis was as follows: 22 hemiparesis (12 right, 10 left), 21 Parkinson’s disease, 15 neuromuscular diseases, 14 hereditary ataxia, 11 multiple sclerosis, 10 unspecific age-related balance disorders, 7 peripheral vestibular disorders, 6 traumatic brain injury, 4 diffuse encephalopathy, 3 cervical myelopathy and 2 CNS neoplasm. All subjects were inpatients referred to the Scientific Institute of Veruno for rehabilitation assessment and treatment. Inclusion criteria were: able to walk with or without a cane; absence of severe cognitive or communication impairments; ability to tolerate the balance tasks without fatigue. Prior to taking part in the study, all participants signed the informed consent that had been approved by the Central Ethics Committee of the ‘Salvatore Maugeri’ Foundation.

Franchignoni F., Horak F., Godi M., Nardone A, & Giordano A. (2010). Using psychometric techniques to improve the Balance Evaluation System’s Test: the mini-BESTest. Journal of rehabilitation medicine : official journal of the UEMS European Board of Physical and Rehabilitation Medicine, 42(4), 323-331.

Publication 2010

Ataxias, Hereditary Canes Central Nervous System Neoplasms Cognition Communicative Disorders Diagnosis Encephalopathies Ethics Committees Fatigue Hemiparesis Inpatient Multiple Sclerosis Neck Neuromuscular Diseases Patients Rehabilitation Spinal Cord Diseases Traumatic Brain Injury Vestibular Diseases Woman

Improving Cause of Death Data

Vital registration with medical certification of cause of death is a crucial resource for the GBD cause of death analysis in many countries. Cause of death data obtained using various revisions of the International Classification of Diseases and Injuries (ICD)⁹ were mapped to the GBD cause list. Many deaths, however, are assigned to causes that cannot be the underlying cause of death (eg, cardiopulmonary failure) or are inadequately specified (eg, injury from undetermined intent). These deaths were reassigned to the most probable underlying causes of death as part of the data processing for GBD. Redistribution algorithms can be divided into three categories: proportionate redistribution, fixed proportion redistribution based on published studies or expert judgment, or statistical algorithms. For GBD 2019, data for 116 million deaths attributed to multiple causes were analysed to produce more empirical redistribution algorithms for sepsis,¹⁰ (link) heart failure, pulmonary embolism, acute kidney injury, hepatic failure, acute respiratory failure, pneumonitis, and five intermediate causes (hydrocephalus, toxic encephalopathy, compression of brain, encephalopathy, and cerebral oedema) in the central nervous system. To redistribute unspecified injuries, we used a method similar to that of intermediate cause redistribution, using the pattern of the nature of injury codes in the causal chain where the ICD codes X59 (“exposure to unspecified factor”) and Y34 (“unspecified event, undetermined intent”) and GBD injury causes were the underlying cause of death. These new algorithms led to important changes in the causes to which these intermediate outcomes were redistributed. Additionally, data on deaths from diabetes and stroke lack the detail on subtype in many countries; we ran regressions on vital registration data with at least 50% of deaths coded specifically to type 1 or 2 diabetes and ischaemic, haemorrhagic, or subarachnoid stroke to predict deaths by these subtypes when these were coded to unspecified diabetes or stroke.

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. (2020). Lancet (London, England), 396(10258), 1204-1222.

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Publication 2020

Brain Central Nervous System Cerebral Edema Cerebrovascular Accident Congestive Heart Failure Diabetes Mellitus Encephalopathies Encephalopathy, Toxic Hemorrhage Hepatic Insufficiency Hydrocephalus Injuries Kidney Injury, Acute Pneumonitis Pulmonary Embolism Respiratory Failure Septicemia Subarachnoid Space

Diagnosis and Criteria for Decompensated Cirrhosis

The main outcome of this study was clinically confirmed ESLD (also referred to as decompensated liver disease). ESLD was defined by the presence of a definitive diagnosis of cirrhosis and a definitive diagnosis of a hepatic decompensation event (ascites, hepatorenal syndrome [HRS], spontaneous bacterial peritonitis [SBP], hepatic encephalopathy [HE), or gastric/esophageal variceal bleeding) in the medical record.
Cirrhosis was confirmed if a patient had a: a) liver biopsy demonstrating cirrhosis, b) radiographic imaging study (abdominal ultrasound, CT scan, or MRI) reporting cirrhosis, or c) physician’s note documenting cirrhosis based on one of the two prior criteria.(5 (link))
Definitions for hepatic decompensation events were based on guidelines published by the American Association for the Study of Liver Diseases (AASLD).(6 (link)) Confirmation of an event required physical exam (ascites, encephalopathy), imaging (ascites), or endoscopic (variceal bleeding) findings confirming a decompensation event, or documentation of an event by a treating physician within the medical record. Patients were required to have had a decompensation event within 365 days of receiving an ICD-9-CM code for that event.
Medical records were reviewed by a hepatologist (D.G.) to confirm outcomes. Chart review also determined if patients would be potential liver transplant candidates based on AASLD criteria.(7 (link))

Goldberg D., Lewis J., Halpern S., Weiner M, & Lo Re V I.I.I. (2012). Validation of a coding algorithm to identify patients with end-stage liver disease in an administrative database. Pharmacoepidemiology and drug safety, 21(7), 765-769.

Publication 2012

Abdomen Ascites Bacteria Biopsy Diagnosis Encephalopathies Endoscopy Hepatic Encephalopathy Hepatologists Hepatorenal Syndrome Liver Liver Cirrhosis Liver Diseases Liver Transplantations Patients Peritonitis Physical Examination Physicians Stomach Ultrasonography X-Ray Computed Tomography X-Rays, Diagnostic

Assessment of Depressive Symptoms and Cognitive Function in Older Adults

The 15-item Swedish version of the GDS (GDS-15) was used to assess depressive symptoms and was interview-administered for all participants (Agrell & Dehlin, 1989 (link); Sheikh & Yesavage, 1986 ). The score ranges from 0 to 15 and a score of zero to four is considered to be within the normal range, five to nine indicates mild depression, and a score of 10 or more indicates moderate to severe depression (Almeida & Almeida, 1999 (link)).
Cognitive state was assessed using the MMSE, which is a test of cognitive aspects of mental function, e.g. orientation, memory, ability to follow verbal and written commands. The MMSE has a score ranging between 0–30, where a score of ≤ 17 indicates severe cognitive impairment and 18–23 indicates mild cognitive impairment (Tombaugh & McIntyre, 1992 ).
The Philadelphia Geriatric Center Morale Scale (PGCMS) was used to assess morale and was also interview-administered for all participants (Lawton, 1975 (link)). High morale is described as a basic sense of satisfaction with oneself, a feeling that there is a fit between personal needs and what the environment offers, and a certain acceptance of what cannot be changed (Lawton, 1975 (link)). It is suitable for use with older people living either in the community or in institutions, and the questions' yes/no format facilitates understanding for people with impaired cognitive function (Lawton, 1975 (link); Ryden & Knopman, 1989 (link)). The 17-item version was used in the present study (Lawton, 1975 (link)), where scores of 0–9 indicate low morale, 10–12 the middle range and 13–17 high morale, according to the administration and scoring instructions.
The Barthel Index (0–20) was used to assess activities of daily living, where higher scores indicate a greater degree of independence (Collin, Wade, Davies, & Home, 1988 (link); Mahoney & Barthel, 1965 (link)). Assessment using the Organic Brain Syndrome Scale contributed to the assessment of depression, dementia and delirium and to differentiate between those diagnoses (Jensen, Dehlin, & Gustafson, 1993 ). Information was collected regarding diagnoses and prescribed drugs from the participants, staff and/or medical records. Diagnosis of depression and dementia were based on earlier diagnosis according to medical charts, ongoing pharmacological treatment, and on assessments during the interviews. All information was reviewed by an experienced physician, and diagnoses of depression and dementia were set according to the DSM-IV criteria (American Psychiatric Association, 1994 ).

Conradsson M., Rosendahl E., Littbrand H., Gustafson Y., Olofsson B, & Lövheim H. (2013). Usefulness of the Geriatric Depression Scale 15-item version among very old people with and without cognitive impairment. Aging & Mental Health, 17(5), 638-645.

Publication 2013

Cognition Cognitive Impairments, Mild Cognitive Testing Delirium Depressive Symptoms Diagnosis Disorders, Cognitive Early Diagnosis Encephalopathies Memory Mental Tests Mini Mental State Examination Pharmaceutical Preparations Pharmacotherapy Physicians Presenile Dementia Satisfaction

Prospective Cirrhosis Surveillance for HCC

Between January 2004 and September 2006, consecutive patients with cirrhosis but no detectable hepatocellular carcinoma (HCC) were prospectively identified and entered into a surveillance programme using ultrasound and α-fetoprotein (AFP), as has been previously described in greater detail.6 (link) Patients were enrolled if they had a Child-Pugh class A or B cirrhosis and absence of known HCC at the time of initial evaluation. Patients diagnosed with HCC within the first 6 months of enrolment (prevalent cases) were excluded. Other exclusion criteria included clinical evidence of significant hepatic decompensation (refractory ascites, grades 3 and 4 encephalopathy, active variceal bleeding or hepatorenal syndrome), comorbid medical conditions with a life expectancy of less than 1 year, prior solid organ transplant and a known extrahepatic primary tumour. Patients were followed until the time of HCC diagnosis, liver transplantation, death or until the study was terminated on 31 July 2010.
The following demographic and clinical data were collected at the time of enrolment: age, gender, race, body mass index (BMI), medical history, lifetime alcohol use and lifetime tobacco use. Data regarding their liver disease included the underlying aetiology and presence of ascites, encephalopathy or oesophageal varices. Laboratory data of interest at the time of enrolment included platelet count, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase, bilirubin, albumin, international normalised ratio (INR) and AFP. This data set was used as the basis of a published predictive model to identify patients with hepatocellular carcinoma with a c statistic of 0.70.2

Waljee A.K., Mukherjee A., Singal A.G., Zhang Y., Warren J., Balis U., Marrero J., Zhu J, & Higgins P.D. (2013). Comparison of imputation methods for missing laboratory data in medicine. BMJ Open, 3(8), e002847.

Publication 2013

Albumins Alkaline Phosphatase alpha-Fetoproteins Ascites Aspartate Transaminase Bilirubin Child D-Alanine Transaminase Diagnosis Encephalopathies Esophageal Varices Gender Hepatocellular Carcinomas Hepatorenal Syndrome Index, Body Mass International Normalized Ratio Liver Cirrhosis Liver Diseases Liver Transplantations Neoplasms Patients Platelet Counts, Blood Transplant, Organ Ultrasonography

Most recents protocols related to «Encephalopathies»

Assessing Depression and Cognitive Impairment in HF Surgery

The outcome was 12-, 24- and 36-month mortality following HF surgery. DDs diagnoses were based on current antidepressant treatment and Geriatric Depression Scale (GDS-15) scores (scores ≥ 5 indicate significant depressive symptoms) [24 ]. In addition, fluctuations of clinical state were observed and registered by the Organic Brain Syndrome scale (OBS scale) [25 (link)]. The GDS-15 has good sensitivity and specificity, even among very old people with low Mini Mental State Examination (MMSE) scores, for DDs detection according to the Diagnostic and Statistical Manual of Mental Disorders – Text revision (4.^th ed.; DSM-IV-TR) [26 (link), 27 (link)]. Cognitive function was assessed using the MMSE, (scores 0–30, scores ≤ 23 indicate significant cognitive impairment) [28 ].
At the end of the RCTs, a consultant geriatrician (YG), blinded to group allocation and not employed at the wards, set all diagnoses. The consultant geriatrician used all possible information from patient’s medical record (diagnoses, complications, and other important documentations), patient’s prescribed drugs and assessments performed in these RCTs (including the MMSE, GDS- 15, Philadelphia Geriatric Center Morale Scale (PGCMS) [29 , 30 (link)], Katz ADL index, OBS Scale), as well as vision and hearing tests, to determine whether participants fulfilled the DMS-IV-TR criteria for DDs and dementia.

Olofsson E., Gustafson Y., Mukka S., Tengman E., Lindgren L, & Olofsson B. (2023). Association of depressive disorders and dementia with mortality among older people with hip fracture. BMC Geriatrics, 23, 135.

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Publication 2023

Antidepressive Agents Cognition Consultant Dementia Depressive Symptoms Diagnosis Disorders, Cognitive Encephalopathies Geriatricians Hearing Tests Mini Mental State Examination Operative Surgical Procedures Patients Pharmaceutical Preparations Vision

Neurobehavioral Evaluation of Consciousness Disorders

As a part of routine clinical evaluation, patients were repeatedly evaluated with various neurobehavioural tests during their stay in the acute neurorehabilitation unit. In our analyses we used the total CRS-R score (0 = absence of any response, 23 = cognitively mediated behaviors) and the Disability rating scale (DRS) (Williams and Smith, 2017 (link)) scores (0 = no disability, 29 = extreme vegetative state) at discharge. The items in this scale correspond to the three original World Health Organization categories of impairment, disability, and handicap, and track a patient's functional and cognitive progress from coma to the community. In addition, the patients were also assessed with the Motor Behavior Tool – revised (MBT-r) (Jöhr et al., 2020 , Pincherle et al., 2019 (link)), a clinical evaluation tool for detecting subtle motor behavior that might reflect residual cognition in unresponsive patients. The patients with detected signs of motor behaviour are identified as patients with clinical cognitive motor dissociation. Experienced clinicians or neuropsychologists carried out the neurobehavioral evaluations. Patients’ demographic and clinical data are presented in Table 1.Table 1

Demographic and clinical data.

Subject	Sex	Age (years)	Interval Injury to MRI (days)	Interval MRI to discharge (days)	Etiology	CRS-R intitial	DRS at disch. (days)	CRS-R at disch. (days)
1	f	67	14	34	CVA	VS/UWS	5	23
2	m	24	8	45	CVA	VS/UWS	22	13
3	m	64	45	28	CVA	VS/UWS	22	4
4	f	57	9	11	CVA	MCS	17	15
5	f	72	101	28	CVA	MCS	25	5
6	m	73	16	41	CVA	VS/UWS	19	16
7	f	67	4	20	TBI	VS/UWS	9	23
8	m	37	1	42	ANOX	COMA	27	4
9	f	35	33	33	TBI	VS/UWS	21	7
10	m	60	21	10	TBI	VS/UWS	9	23
11	m	63	19	63	CVA	MCS	4	22
12	m	55	19	41	CVA	MCS	15	11
13	m	42	31	14	TBI	COMA	15	20
14	f	65	43	8	ANOX	COMA	7	23
15	m	27	287	16	TBI	VS/UWS	20	11
16	m	28	42	8	TBI	MCS	2	23
17	f	37	30	60	TBI	COMA	23	9
18	m	47	16	44	TBI	VS/UWS	7	22
19	f	66	30	28	TBI	COMA	11	23
20	f	39	34	20	CVA	COMA	11	21
21	f	52	23	27	CVA	MCS	15	21
22	m	61	35	27	CVA	COMA	14	18
23	m	61	34	34	CVA	COMA	11	23
24	m	78	50	41	ENC	COMA	15	13
25	m	44	28	26	TBI	COMA	11	21
26	f	60	26	49	CVA	COMA	22	11
27	f	69	41	59	ENC	MCS	18	11
28	f	54	30	25	TBI	VS/UWS	26	5
29	m	50	9	63	ANOX	MCS	8	22
30	f	84	26	14	TBI	COMA	21	13
31	m	16	20	12	TBI	MCS	6	23
32	m	35	19	25	LEUCO	VS/UWS	18	13
33	m	49	29	15	CVA	MCS-	6	21
34	m	72	22	13	CVA	MCS-	7	22
35	m	55	41	47	CVA	COMA	29	22
36	f	58	63	−5	CVA	VS/UWS	9	20
37	f	25	38	7	TBI	VS/UWS	11	11
38	m	73	20	37	TBI	VS/UWS	7	22
39	m	60	38	20	CVA	VS/UWS	11	22
40	m	59	43	3	ANOX	VS/UWS	23	8

CVA = cardiovascular accident, TBI = traumatic brain injury, ANOX = anoxia, ENC = encephalopathy, LEUCO = leucoencephalopathy, VS/UWS = vegetative state or unresponsive wakefulness syndrome, MCS = minimally conscious state, DRS = Disability Rating Scale, CRS-R = Coma Recovery Scale – Revised.

Pozeg P., Alemán-Goméz Y., Jöhr J., Muresanu D., Pincherle A., Ryvlin P., Hagmann P., Diserens K, & Dunet V. (2023). Structural connectivity in recovery after coma: Connectome atlas approach. NeuroImage : Clinical, 37, 103358.

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Publication 2023

Accidents Anoxia Cardiovascular System Cognition Comatose Disabled Persons Encephalopathies Injuries Leukoencephalopathy Minimally Conscious State Neurological Rehabilitation Patient Discharge Patients Syndrome Traumatic Brain Injury Vegetative State Wakefulness

The clinical data of the patients diagnosed with STXBP1-related disorders and referred to Xiangya hospital, Central South University from 2011 to 2019 were collected retrospectively. We included all patients with DEE/developmental encephalopathy (DE) pathogenic/likely pathogenic variants of STXBP1.

Kessi M., Chen B., Shan L.D., Wang Y., Yang L., Yin F., He F., Peng J, & Wang G. (2023). Genotype-phenotype correlations of STXBP1 pathogenic variants and the treatment choices for STXBP1-related disorders in China. BMC Medical Genomics, 16, 46.

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Publication 2023

Encephalopathies pathogenesis Patients

COVID-19 Pneumothorax Incidence and Outcomes

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Publication 2023

Blood Vessel C Reactive Protein Dementia Diagnosis Disorders, Cognitive Encephalopathies Ferritin fibrin fragment D Hospitalization Lactate Dehydrogenase Lung Lymphocyte Count Macrophage Neutrophil Nipple Discharge Patients Platelet Counts, Blood Pleural Effusion Radionuclide Imaging Respiratory Rate Troponin X-Ray Computed Tomography X-Rays, Diagnostic

Newly Diagnosed Parkinson's Disease Cohort

Between July 2019 and September 2021, a consecutive cohort of patients with PD visiting Chongqing University Jiangjin Hospital was prospectively recruited. This study was approved by the Ethical Committee of Chongqing University Jiangjin Hospital (JJ2020017029) and performed conforming to the guidelines of the Declaration of Helsinki, and all participants provided written informed consents.
The inclusion criteria were ① newly diagnosed patients with PD according to the UK Parkinson’s Disease Society Brain Bank clinical diagnostic criteria;18 (link) ② meeting de novo criteria, ie, L-dopa exposure no longer than 2 weeks and not within 4 weeks prior to study recruitment; ③ ranging from 40 to 85 years old. The exclusion criteria included ① medication-induced PD; ② signs or symptoms of progressive supranuclear palsy or multiple system atrophy according to consensus criteria;19 (link),20 (link) ③ known severe normal-pressure hydrocephalus (NPH) or vascular encephalopathy as demonstrated by MRI alone; ④ receiving drugs within the past 3 months that could influence serum Hcy, blood lipid and Cys C levels; ⑤ kidney and liver dysfunction; severe cardiovascular, respiratory, haematologic system, wasting or nutritional metabolism diseases. MRI and baseline cognitive evaluation were performed in all participants. Patients with PD dementia were excluded by clinical dementia rating (CDR) ≥ 0.5 points.

Zhang Z., Li S, & Wang S. (2023). Application of Periventricular White Matter Hyperintensities Combined with Homocysteine into Predicting Mild Cognitive Impairment in Parkinson’s Disease. International Journal of General Medicine, 16, 785-792.

Publication 2023

BLOOD Blood Vessel Brain Cardiovascular System Cognition Dementia Diagnosis Encephalopathies Hydrocephalus, Normal Pressure Kidney Levodopa Lipids Metabolic Diseases Metabolism Multiple System Atrophy Nutrition Disorders Patients Pharmaceutical Preparations Progressive Supranuclear Palsy Respiratory Rate Respiratory System Serum

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What are the different types of encephalopathies?

How can PubCompare.ai help with encephalopathy research?

PubCompare.ai allows researchers to screen protocol literature more efficiently and leverage AI to pinpoint critical insights. The platform can help identify the most effective protocols related to encephalopathies for your specific research goals. Its AI-driven analysis can highlight key differences in protocol effectiveness, enabling you to choose the best option for reproducibility and accuracy, and accelerte scientific progress in this critical area of neurology.

What are some common symptoms of encephalopathies?

Encephalopathies can manifest a wide range of symptoms, including cognitive impairments, behavioral changes, seizures, movement disorders, and altered levels of consciousness. The specific symptoms depend on the underlying cause and the regions of the brain affected. Prompt recognition of these symptoms is crucial for timely diagnosis and appropriate management of encephalopathies.

How do genetic factors contribute to encephalopathies?

Genetic factors play a significant role in the development of certain types of encephalopathies, such as mitochondrial encephalopathies, leukodystrophies, and some forms of neurodegenerative encephalopathies. Advances in genetic testing and analysis have enabled more accurate diagnosis and, in some cases, the identification of targeted therapies for these genetically-linked encephalopathies.

What are some common causes of encephalopathies?

More about "Encephalopathies"

Encephalopathies are a diverse group of neurological disorders that affect the brain, leading to cognitive, behavioral, and neurological impairments.
These complex conditions involve structural, metabolic, or functional abnormalities in the brain, often with progressive or degenerative features.
Encephalopathies can have a wide range of underlying causes, including genetic factors, infections, toxins, and vascular or traumatic injuries.
Accurate diagnosis and effective management of encephalopathies require a multidisciplinary approach, drawing on advances in neuroimaging techniques like SAS 9.4 and FibroScan, biochemical testing using RNAlater solution, and genetic analysis with tools like the PowerPlex S5 system.
Researchers can leverage AI-powered platforms like PubCompare.ai to streamline their encephalopathy studies, quickly locating the best research protocols from scholarly publications, preprints, and patents, helping to improve reproducibility and accelerate scientific progress in this critical area of neurology.
Other relevant technologies and tools used in encephalopathy research include LabVIEW for data acquisition and analysis, the QIAamp DNA Blood Mini Kit for DNA extraction, the NIRO-200 for near-infrared spectroscopy, the NicoletOne™ vEEG system for electroencephalography, and Complete protease inhibitor tablets for protein extraction and purification.
By leveraging these advanced techniques and technologies, researchers can gain deeper insights into the underlying mechanisms of encephalopathies and develop more effective diagnostic and therapeutic strategies, ultimately improving outcomes for patients suffering from these debilitating neurological conditions.