scholarly journals Cerebrospinal Fluid Apolipoprotein E Levels in Delirium

2017 ◽  
Vol 7 (2) ◽  
pp. 240-248 ◽  
Author(s):  
Gideon A. Caplan ◽  
JIan Tai ◽  
Fazrul Mohd Hanizan ◽  
Catherine L. McVeigh ◽  
Mark A. Hill ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cerebrospinal Fluid ◽  
Apolipoprotein E ◽  
Late Onset ◽  
The Elderly ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Apolipoprotein A1 ◽  
Ε4 Allele ◽  
State Examination

Background/Aims: Delirium and the apolipoprotein E ε4 allele are risk factors for late-onset Alzheimer disease (LOAD), but the connection is unclear. We looked for an association. Methods: Inpatients with delirium (n = 18) were compared with LOAD outpatients (n = 19), assaying blood and cerebrospinal fluid (CSF) using multiplex ELISA. Results: The patients with delirium had a higher Confusion Assessment Method (CAM) score (5.6 ± 1.2 vs. 0.0 ± 0.0; p < 0.001) and Delirium Index (13.1 ± 4.0 vs. 2.9 ± 1.2; p = 0.001) but a lower Mini-Mental State Examination (MMSE) score (14.3 ± 6.8 vs. 20.8 ± 4.6; p = 0.003). There was a reduction in absolute CSF apolipoprotein E level during delirium (median [interquartile range]: 9.55 μg/mL [5.65–15.05] vs. 16.86 μg/mL [14.82–20.88]; p = 0.016) but no differences in apolipoprotein A1, B, C3, H, and J. There were no differences in blood apolipoprotein levels, and no correlations between blood and CSF apolipoprotein levels. CSF apolipoprotein E correlated negatively with the CAM score (r = –0.354; p = 0.034) and Delirium Index (r = –0.341; p = 0.042) but not with the Acute Physiology and Chronic Health Evaluation (APACHE) index, or the MMSE or Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). Conclusion: Reduced CSF apolipoprotein E levels during delirium may be a mechanistic link between two important risk factors for LOAD.

scholarly journals Preoperative Cerebrospinal Fluid Cortisol and the Risk of Postoperative Delirium: A Prospective Study of Older Hip Fracture Patients

2020 ◽  
Vol 49 (6) ◽  
pp. 604-610
Author(s):  
Joost Witlox ◽  
Dimitrios Adamis ◽  
Leo Koenderman ◽  
Kees Kalisvaart ◽  
Jos F.M. de Jonghe ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cerebrospinal Fluid ◽  
Hip Fracture ◽  
Postoperative Delirium ◽  
Rating Scale ◽  
The Elderly ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Cortisol Levels ◽  
A Prospective Study

<b><i>Background:</i></b> Ageing, depression, and neurodegenerative disease are common risk factors for delirium in the elderly. These risk factors are associated with dysregulation of the hypothalamic-pituitary-adrenal axis, resulting in higher levels of cortisol under normal and stressed conditions and a slower return to baseline. <b><i>Objectives:</i></b> We investigated whether elevated preoperative cerebrospinal fluid (CSF) cortisol levels are associated with the onset of postoperative delirium. <b><i>Methods:</i></b> In a prospective cohort study CSF samples were collected after cannulation for the introduction of spinal anesthesia of 75 patients aged 75 years and older admitted for surgical repair of acute hip fracture. Delirium was assessed with the confusion assessment method (CAM) and the Delirium Rating Scale-Revised-98 (DRS-R98). Because the CAM and DRS-R98 were available for time of admission and 5 postoperative days, we used generalized estimating equations and linear mixed modeling to examine the association between preoperative CSF cortisol levels and the onset of postoperative delirium. <b><i>Results:</i></b> Mean age was 83.5 (SD 5.06) years, and prefracture cognitive decline was present in one-third of the patients (24 [33%]). Postoperative delirium developed in 27 (36%) patients. We found no association between preoperative CSF cortisol levels and onset or severity of postoperative delirium. <b><i>Conclusions:</i></b> These findings do not support the hypothesis that higher preoperative CSF cortisol levels are associated with the onset of postoperative delirium in elderly hip fracture patients.

scholarly journals Postoperative Delirium after Urological Surgery: A Literature Review

2019 ◽  
Vol 13 (3) ◽  
pp. 133-140 ◽  
Author(s):  
Ioannis Leotsakos ◽  
Ioannis Katafigiotis ◽  
Ofer N. Gofrit ◽  
Mordechai Duvdevani ◽  
Dionysios Mitropoulos
Keyword(s):  
Risk Factors ◽  
Literature Search ◽  
Postoperative Delirium ◽  
Mini Mental State Examination ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Factors Associated ◽  
Confusion Assessment ◽  
Urological Surgery ◽  
State Examination

Purpose: We aimed to thoroughly search and identify studies referring to risk factors associated with postoperative delirium (POD) in patients undergoing open as well as en-doscopic urological surgery. Methods: The review after a systematic literature search included 5 studies. Results: The incidence of POD was reported to be between 7.8 and 30% depending on the type of the urologic surgery, while in the majority of the studies the onset happened on the first postoperative day and the symptoms lasted 3 ± 0.8 days. Seventeen different risk factors for POD were identified and presented in detail. Conclusion: The Mini-Mental State Examination score and older age were significantly associated with the development of POD. However, the Confusion Assessment Method is very well validated against the diagnosis of delirium from the specialists.

scholarly journals Twelve-Month Mortality Among Delirium Subtypes

2011 ◽  
Vol 20 (4) ◽  
pp. 404-421 ◽  
Author(s):  
Susan K. DeCrane ◽  
Kennith R. Culp ◽  
Bonnie Wakefield
Keyword(s):  
Statistical Significance ◽  
The Elderly ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Term Care ◽  
International Classification Of Disease ◽  
Subsyndromal Delirium ◽  
Icd 10 ◽  
Underlying Cause Of Death ◽  
State Examination

This study used data from the Delirium Among the Elderly in Rural Long-Term Care Facilities Study and data from the National Death Index (NDI) to examine mortality among 320 individuals. Individuals were grouped into noncases, subsyndromal cases, hypoactive delirium, hyperactive delirium, and mixed delirium on the basis of scoring using the Confusion Assessment Method (CAM), NEECHAM Scale, Mini-Mental State Examination (MMSE), Clinical Assessment of Confusion-A (CAC-A), and Vigilance A instruments. Risk ratios of mortality using “days of survival” did not reach statistical significance (α = .05) for any subgroup. Underlying cause of death (UCD) using International Classification of Disease, 10th version (ICD-10), showed typical UCD among older adults. There appeared to be clinical differences in UCD between delirium subgroups. Findings supported the conclusion that careful monitoring of patients with delirium and subsyndromal delirium is needed to avoid complications and injuries that could increase mortality.

scholarly journals Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) completion on an acute care ward for the elderly: a brief study of informant characteristics

2012 ◽  
Vol 24 (10) ◽  
pp. 1700-1701 ◽  
Author(s):  
K. Bloomfield ◽  
N. John
Keyword(s):  
Cognitive Impairment ◽  
Cognitive Decline ◽  
The Elderly ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Cognitive Screening ◽  
Screening Algorithm ◽  
Drawing Task ◽  
The Uk ◽  
State Examination

Over recent years in the UK, emphasis has been placed on appropriate diagnosis and referral of patients with dementia. In guidelines published by the British Geriatrics Society (BGS) and Faculty of Old Age Psychiatrists consensus group (Forsyth et al., 2006), a cognitive screening algorithm was developed, which consists of initial screening for cognitive impairment with the Mini-Mental State Examination (MMSE) and CLOX1 (an executive clock drawing task). If the scores meet cut-off points indicated in the algorithm (MMSE <24 or CLOX1 <11), further assessments with the Confusion Assessment Method (CAM) and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) are applied with the aim to differentiate between delirium (CAM positive, IQCODE negative), delirium and chronic impairment (CAM positive, IQCODE positive), or chronic cognitive impairment (CAM negative, IQCODE positive).

scholarly journals Elevated Procalcitonin and Depression As Risk Factors For Postoperative Delirium In The Elderly After Cardiac Surgery – A Prospective Observational Study.

2020 ◽  
Author(s):  
Anna Kupiec ◽  
Barbara Adamik ◽  
Natalia Kozera ◽  
Waldemar Gozdzik
Keyword(s):  
Risk Factors ◽  
Cardiac Surgery ◽  
Elderly Patients ◽  
Postoperative Delirium ◽  
Inflammatory Marker ◽  
Functional Decline ◽  
The Elderly ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Multivariable Logistic Regression Model

Abstract Background One of the most common complications after cardiac surgery is delirium. Determining the origin of this complication from possible pathomechanisms is difficult. The activation of an inflammatory response during surgery has been suggested as one possible mechanism of delirium. The usefulness of the inflammatory marker procalcitonin (PCT) as a predictor of delirium after cardiac surgery with cardiopulmonary bypass (CBP) has not yet been investigated. Methods The purpose of this study was to prospectively investigate the risk of developing postoperative delirium in a group of elderly patients using a multivariate assessment of preoperative (PCT, comorbidities, functional decline, depression) and intraoperative risk factors. 149 elderly patients were included. Delirium was assessed using the Confusion Assessment Method for the ICU. Results Thirty patients (20%) developed post-operative delirium: hypoactive in 50%, hyperactive in 33%, mixed in 17%. Preoperative PCT above the reference range (> 0.05 ng/mL) was recorded more often in patients who postoperatively developed delirium than in the non-delirium group (50% vs. 27%, p=0.019). After surgery, PCT was significantly higher in the delirium than the non-delirium group: ICU admission after surgery: 0.08 ng/mL, IQR 0.03-0.15 vs. 0.05 ng/mL, IQR 0.02-0.09, p=0.011), and for consecutive days (day 1: 0.59 ng/mL, IQR 0.25-1.55 vs. 0.25 ng/mL, IQR 0.14-0.54, p=0.003; day 2: 1.21 ng/mL, IQR 0.24-3.29 vs. 0.36 ng/mL, IQR 0.16-0.76, p=0.006; day 3: 0.76 ng/mL, IQR 0.48-2.34 vs. 0.34 ng/mL, IQR 0.14-0.66, p=0.001). Patients with delirium were older (74 years, IQR 70 – 76 vs. 69 years, IQR 67 – 74; p=0.038) and more often had functional decline (47% vs. 28%, p=0.041). There was no difference in comorbidities with the exception of anaemia (43% vs. 19%, p=0.006). Depression was detected in 40% of patients with delirium and in 17% without delirium (p=0.005). In a multivariable logistic regression model of preoperative procalcitonin (OR= 3.05; IQR 1.02-9.19), depression (OR=5.02, IQR 1.67-15.10), age (OR=1.14; IQR 1.02-1.26), functional decline (OR=0.76; IQR 0.63-0.91) along with CPB time (OR=1.04; IQR 1.02-1.06) were significant predictors of postoperative delirium. Conclusion A preoperative PCT test and assessment of functional decline and depression may help identify patients at risk for developing delirium after cardiac surgery.

Validity of the Confusion Assessment Method in Detecting Postoperative Delirium in the Elderly

1999 ◽  
Vol 11 (4) ◽  
pp. 431-438 ◽  
Author(s):  
Darryl B. Rolfson ◽  
Janet E. McElhaney ◽  
Gian S. Jhangri ◽  
Kenneth Rockwood
Keyword(s):  
Postoperative Delirium ◽  
The Elderly ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Health Record ◽  
Confusion Assessment ◽  
Before And After ◽  
Training Background ◽  
Record Review ◽  
State Examination

In this prospective cohort of 71 elderly patients undergoing cardiac surgery, each subject was interviewed before and after surgery to detect incident delirium using the Confusion Assessment Method (CAM), the Mini-Mental State Examination (MMSE), the Clock Test, and a health record review. The first 41 were assessed by a physician and the remaining 30 by two study nurses. Delirium was then diagnosed by a physician using DSM-III-R criteria. Delirium was present in 23 subjects (32.4%). The sensitivity of the CAM differed significantly when administered by physicians compared to nurses (1.00 vs. .13). When standard cutoffs were used, neither the MMSE nor the Clock Test were found to be sensitive markers for delirium (.30 and .09, respectively). Recognition of delirium by charting was superior in nurses compared to physicians (.83 vs. .30). We conclude that the sensitivity of markers for delirium, such as the CAM and health record documentation, is dependent on the training background of the operator.

Molecular Genetics of Early- and Late-Onset Alzheimer’s Disease

2020 ◽  
Vol 20 ◽  
Author(s):  
Md. Sahab Uddin ◽  
Sharifa Hasana ◽  
Md. Farhad Hossain ◽  
Md. Siddiqul Islam ◽  
Tapan Behl ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Massively Parallel Sequencing ◽  
Late Onset ◽  
Current Knowledge ◽  
The Elderly ◽  
Apoe Ε4 ◽  
Sequencing Technologies ◽  
Genetic Components ◽  
Ε4 Allele

: Alzheimer’s disease (AD) is the most common form of dementia in the elderly and this complex disorder is associated with environmental as well as genetic components. Early-onset AD (EOAD) and late-onset AD (LOAD, more common) are major identified types of AD. The genetics of EOAD is extensively understood with three genes variants such as APP, PSEN1, and PSEN2 leading to disease. On the other hand, some common alleles including APOE are effectively associated with LOAD identified but the genetics of LOAD is not clear to date. It has been accounted that about 5% to 10% of EOAD patients can be explained through mutations in the three familiar genes of EOAD. The APOE ε4 allele augmented the severity of EOAD risk in carriers, and APOE ε4 allele was considered as a hallmark of EOAD. A great number of EOAD patients, who are not genetically explained, indicate that it is not possible to identify disease- triggering genes yet. Although several genes have been identified through using the technology of next-generation sequencing in EOAD families including SORL1, TYROBP, and NOTCH3. A number of TYROBP variants were identified through exome sequencing in EOAD patients and these TYROBP variants may increase the pathogenesis of EOAD. The existence of ε4 allele is responsible for increasing the severity of EOAD. However, several ε4 allele carriers live into their 90s that propose the presence of other LOAD genetic as well as environmental risk factors that are not identified yet. It is urgent to find out missing genetics of EOAD and LOAD etiology to discover new potential genetics facets which will assist to understand the pathological mechanism of AD. These investigations should contribute to developing a new therapeutic candidate for alleviating, reversing and preventing AD. This article based on current knowledge represents the overview of the susceptible genes of EOAD, and LOAD. Next, we represent the probable molecular mechanism which might elucidate the genetic etiology of AD and highlight the role of massively parallel sequencing technologies for novel gene discoveries.

scholarly journals A Systematic Review and Pooled Prevalence of Paediatric Delirium in Critically Ill Children

2021 ◽  
Vol 29 (Supplement_1) ◽  
pp. i31-i32
Author(s):  
D Semple ◽  
M M Howlett ◽  
J D Strawbridge ◽  
C V Breatnach ◽  
J C Hayden
Keyword(s):  
Risk Factors ◽  
Critical Care ◽  
Critically Ill ◽  
Observational Studies ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Critically Ill Children ◽  
Confusion Assessment ◽  
Pooled Prevalence

Abstract Introduction Paediatric Delirium (PD) is a neuropsychiatric complication that occurs during the management of children in the critical care environment (Paediatric Intensive Care (PICU) and Neonatal Intensive Care (NICU). Delirium can be classified as hypoactive (decreased responsiveness and withdrawal), hyperactive (agitation and restlessness), and mixed (combined) (1). PD can be assessed using a number of assessment tools. PD has been historically underdiagnosed or misdiagnosed, having many overlapping symptoms with other syndrome such as pain and iatrogenic withdrawal syndrome (2). An appreciation of the extent of PD would help clinicians and policy makers drive interventions to improve recognition, prevention and management of PD in clinical practice. Aim To estimate the pooled prevalence of PD using validated assessment tools, and to identify risk factors including patient-related, critical-care related and pharmacological factors. Methods A systematic search of PubMed, EMBASE and CINAHL databases was undertaken. Eligible articles included observational studies or trials that estimated a prevalence of PD in a NICU/PICU population using a validated PD assessment tool. Validated tools are the paediatric Confusion Assessment Method-ICU (pCAM-ICU), the Cornell Assessment of Pediatric Delirium (CAPD), the PreSchool Confusion Assessment Method for the ICU (psCAM-ICU), pCAM-ICU severity scale (sspCAM-ICU), and the Sophia Observation Withdrawal Symptoms scale Paediatric Delirium scale (SOS-PD) (1). Only full text studies were included. No language restrictions were applied. Two reviewers independently screened records. Data was extracted using a pre-piloted form and independently verified by another reviewer. Quality was assessed using tools from the National Institutes of Health. A pooled prevalence was calculated from the studies that estimated PD prevalence using the most commonly applied tool, the CAPD (1). Results Data from 23 observational studies describing prevalence and risk factors for PD in critically ill children were included (Figure 1). Variability in study design and outcome reporting was found. Study quality was generally good. Using the validated tools prevalence ranged from 10–66% of patients. Hypoactive delirium was the most prevalent sub-class identified. Using the 13 studies that used the CAPD tool, a pooled prevalence of 35% (27%-43% 95%CI) was calculated. Younger ages, particularly less than two years old, sicker patients, particularly those undergoing mechanical and respiratory ventilatory support were more at risk for PD. Restraints, the number of sedative medications, including the cumulative use of benzodiazepines and opioids were identified as risk factors for the development of PD. PD was associated with longer durations of mechanical ventilation, longer stays and increased costs. Data on association with increased mortality risk is limited and conflicting. Conclusion PD affects one third of critical care admissions and is resource intense. Routine assessment in clinical practice may facilitate earlier detection and management strategies. Modifiable risk factors such as the class and number of sedative and analgesic medications used may contribute to the development of PD. Early mobility and lessening use of these medications present strategies to prevent PD occurrence. Longitudinal prospective multi-institutional studies to further investigate the presentations of the different delirium subtypes and modifiable risk factors that potentially contribute to the development of PD, are required. References 1. Semple D (2020) A systematic review and pooled prevalence of PD, including identification of the risk factors for the development of delirium in critically ill children. doi: 10.17605/OSF.IO/5KFZ8 2. Ista E, te Beest H, van Rosmalen J, de Hoog M, Tibboel D, van Beusekom B, et al. Sophia Observation withdrawal Symptoms-Paediatric Delirium scale: A tool for early screening of delirium in the PICU. Australian Critical Care. 2018;31(5):266–73

scholarly journals Do we know if our Patients are Delirious?

2008 ◽  
Vol 9 (3) ◽  
pp. 269-269
Author(s):  
Callum Kaye
Keyword(s):  
Risk Factors ◽  
Intensive Care Unit ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Critically Ill Patient ◽  
Confusion Assessment ◽  
Surgical Icu ◽  
Symptoms And Signs

Delirium in the intensive care unit (ICU) setting is a significant cause of morbidity, mortality and increases ICU, as well as hospital length of stay1,2. Furthermore, with so many of the risk factors being present in the critically ill patient in the ICU environment, it's not surprising that other studies have found that up to 80% of patients will be delirious at some point during admission3,4. We performed a small study in a Toronto Medical-Surgical ICU using the Confusion Assessment Method for the ICU (CAM-ICU)5 to determine the prevalence of delirium in this unit. We concurrently reviewed medical and nursing notes to identify documentation of symptoms and signs that could indicate possible delirium during routine clinical assessment of the patient.

The Role of Apolipoprotein E ε4 in Early and Late Mild Cognitive Impairment

2021 ◽  
Vol 84 (6) ◽  
pp. 472-480
Author(s):  
Yulin Luo ◽  
Li Tan ◽  
Joseph Therriault ◽  
Hua Zhang ◽  
Ying Gao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Apolipoprotein E ◽  
Amyloid Β ◽  
Disease Assessment ◽  
Tau Pathology ◽  
Ε4 Allele ◽  
State Examination

<b><i>Background:</i></b> Apolipoprotein E (<i>APOE</i>) ε4 is highly associated with mild cognitive impairment (MCI). However, the specific influence of <i>APOE</i> ε4 status on tau pathology and cognitive decline in early MCI (EMCI) and late MCI (LMCI) is poorly understood. Our goal was to evaluate the association of <i>APOE</i> ε4 with cerebrospinal fluid (CSF) tau levels and cognition in EMCI and LMCI patients in the Alzheimer’s Disease Neuroimaging Initiative database, and whether this association was mediated by amyloid-β (Aβ). <b><i>Methods:</i></b> Participants were 269 cognitively normal (CN), 262 EMCI, and 344 LMCI patients. They underwent CSF Aβ42 and tau detection, <i>APOE</i> ε4 genotyping, Mini-Mental State Examination, (MMSE), and Alzheimer’s disease assessment scale (ADAS)-cog assessments. Linear regressions were used to examine the relation of <i>APOE</i> ε4 and CSF tau levels and cognitive scores in persons with and without Aβ deposition (Aβ+ and Aβ−). <b><i>Results:</i></b> The prevalence of <i>APOE</i> ε4 is higher in EMCI and LMCI than in CN (<i>p</i> &#x3c; 0.001 for both), and in LMCI than in EMCI (<i>p</i> = 0.001). <i>APOE</i> ε4 allele was significantly higher in Aβ+ subjects than in Aβ− subjects (<i>p</i> &#x3c; 0.001). Subjects who had a lower CSF Aβ42 level and were <i>APOE</i> ε4-positive experienced higher levels of CSF tau and cognitive scores in EMCI and/or LMCI. <b><i>Conclusions:</i></b> An <i>APOE</i> ε4 allele is associated with increased CSF tau and worse cognition in both EMCI and LMCI, and this association may be mediated by Aβ. We conclude that <i>APOE</i> ε4 may be an important mediator of tau pathology and cognition in the early stages of AD.

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