Post-Operative Cognitive Dysfunction in Elderly Patients Receiving Propofol Sedation for Gastrointestinal Endoscopies: An Observational Study Utilizing Processed Electroencephalography.

BACKGROUND: Propofol sedation is commonly administered during gastrointestinal (GI) procedures. The Patient State Index (PSI) is a processed electroencephalography (EEG) parameter obtained with the SedLine® Sedation Monitoring system (Masimo Corporation, Irvine, CA). When used to objectively assess the patient's level of consciousness, PSI may provide a more effective, safer titration of sedation during GI procedures. We hypothesize that having more or longer episodes of deep sedation as assessed by PSI (i.e., PSI<26) would correlate with developing new-onset or worsening post-operative cognitive dysfunction (POCD). METHODS: This was a pragmatic, double-blinded observational study of 400 patients aged ≥65 years undergoing upper GI endoscopy, lower GI endoscopy, or a combined procedure utilizing propofol sedation at a tertiary-care [A1] academic medical center. The patients were monitored with the SedLine® Brain Function Monitor, software version 2 (Masimo Corporation, Irvine, CA), throughout the case, starting at baseline (i.e., before administration of propofol) and stopping at case end. We assessed the subjects' cognitive function via an in-person interview at baseline (pre-procedure) and telephone interviews at 1, 7 (±1), and 90 days after study enrollment. Cognitive function was assessed by administering the short blessed test (SBT), which is a validated brief cognitive screening appropriate for in-person and telephone administration. RESULTS: The correlations between the change in SBT score and the pre-defined parameters of PSI were not significant (all p-values >5%). There was a significant drop in SBT scores on day seven. Higher age was also significantly associated with a drop in SBT from baseline. Deep sedation, as evidenced by the number of times PSI was lower than 26, was not predictive of the change in SBT, nor was gender, total propofol dose, or vasoactive drug use during the procedure. CONCLUSIONS: The observed incidence of POCD after GI procedures with propofol sedation was low (1.3% at seven days and 2.95% at 90 days) and lower than at the baseline. Age was associated with a greater average decline in SBT score, although the absolute change was small (-0.067 per year of age increase). Deeper sedation, as documented by the PSI score, was not associated with a change in POCD measured with the SBT.

Early Detection of Alzheimer's Disease-Related Pathology Using a Multi-Disease Diagnostic Platform Employing Autoantibodies as Blood-Based Biomarkers.

BACKGROUND: Evidence for the universal presence of IgG autoantibodies in blood and their potential utility for the diagnosis of Alzheimer's disease (AD) and other neurodegenerative diseases has been extensively demonstrated by our laboratory. The fact that AD-related neuropathological changes in the brain can begin more than a decade before tell-tale symptoms emerge has made it difficult to develop diagnostic tests useful for detecting the earliest stages of AD pathogenesis. OBJECTIVE: To determine the utility of a panel of autoantibodies for detecting the presence of AD-related pathology along the early AD continuum, including at pre-symptomatic [an average of 4 years before the transition to mild cognitive impairment (MCI)/AD)], prodromal AD (MCI), and mild-moderate AD stages. METHODS: A total of 328 serum samples from multiple cohorts, including ADNI subjects with confirmed pre-symptomatic, prodromal, and mild-moderate AD, were screened using Luminex xMAP® technology to predict the probability of the presence of AD-related pathology. A panel of eight autoantibodies with age as a covariate was evaluated using randomForest and receiver operating characteristic (ROC) curves. RESULTS: Autoantibody biomarkers alone predicted the probability of the presence of AD-related pathology with 81.0% accuracy and an area under the curve (AUC) of 0.84 (95% CI = 0.78-0.91). Inclusion of age as a parameter to the model improved the AUC (0.96; 95% CI = 0.93-0.99) and overall accuracy (93.0%). CONCLUSION: Blood-based autoantibodies can be used as an accurate, non-invasive, inexpensive, and widely accessible diagnostic screener for detecting AD-related pathology at pre-symptomatic and prodromal AD stages that could aid clinicians in diagnosing AD.

Autoantibodies as diagnostic biomarkers for the detection and subtyping of multiple sclerosis.

The goal of this preliminary proof-of-concept study was to use human protein microarrays to identify blood-based autoantibody biomarkers capable of diagnosing multiple sclerosis (MS). Using sera from 112 subjects, including 51 MS subjects, autoantibody biomarkers effectively differentiated MS subjects from age- and gender-matched normal and breast cancer controls with 95.0% and 100% overall accuracy, but not from subjects with Parkinson's disease. Autoantibody biomarkers were also useful in distinguishing subjects with the relapsing-remitting form of MS from those with the secondary progressive subtype. These results demonstrate that autoantibodies can be used as noninvasive blood-based biomarkers for the detection and subtyping of MS.

Detection of Alzheimer's disease at mild cognitive impairment and disease progression using autoantibodies as blood-based biomarkers.

INTRODUCTION: There is an urgent need to identify biomarkers that can accurately detect and diagnose Alzheimer's disease (AD). Autoantibodies are abundant and ubiquitous in human sera and have been previously demonstrated as disease-specific biomarkers capable of accurately diagnosing mild-moderate stages of AD and Parkinson's disease. METHODS: Sera from 236 subjects, including 50 mild cognitive impairment (MCI) subjects with confirmed low CSF Aß42 levels, were screened with human protein microarrays to identify potential biomarkers for MCI. Autoantibody biomarker performance was evaluated using Random Forest and Receiver Operating Characteristic curves. RESULTS: Autoantibody biomarkers can differentiate MCI patients from age-matched and gender-matched controls with an overall accuracy, sensitivity, and specificity of 100.0%. They were also capable of differentiating MCI patients from those with mild-moderate AD and other neurologic and non-neurologic controls with high accuracy. DISCUSSION: Autoantibodies can be used as noninvasive and effective blood-based biomarkers for early diagnosis and staging of AD.

Potential utility of autoantibodies as blood-based biomarkers for early detection and diagnosis of Parkinson's disease.

INTRODUCTION: There is a great need to identify readily accessible, blood-based biomarkers for Parkinson's disease (PD) that are useful for accurate early detection and diagnosis. This advancement would allow early patient treatment and enrollment into clinical trials, both of which would greatly facilitate the development of new therapies for PD. METHODS: Sera from a total of 398 subjects, including 103 early-stage PD subjects derived from the Deprenyl and Tocopherol Antioxidative Therapy of Parkinsonism (DATATOP) study, were screened with human protein microarrays containing 9,486 potential antigen targets to identify autoantibodies potentially useful as biomarkers for PD. A panel of selected autoantibodies with a higher prevalence in early-stage PD was identified and tested using Random Forest for its ability to distinguish early-stage PD subjects from controls and from individuals with other neurodegenerative and non-neurodegenerative diseases. RESULTS: Results demonstrate that a panel of selected, blood-borne autoantibody biomarkers can distinguish early-stage PD subjects (90% confidence in diagnosis) from age- and sex-matched controls with an overall accuracy of 87.9%, a sensitivity of 94.1% and specificity of 85.5%. These biomarkers were also capable of differentiating patients with early-stage PD from those with more advanced (mild-moderate) PD with an overall accuracy of 97.5%, and could distinguish subjects with early-stage PD from those with other neurological (e.g., Alzheimer's disease and multiple sclerosis) and non-neurological (e.g., breast cancer) diseases. CONCLUSION: These results demonstrate, for the first time, that a panel of selected autoantibodies may prove to be useful as effective blood-based biomarkers for the diagnosis of early-stage PD.

The development of the Lifestyle and Habits Questionnaire-brief version: relationship to quality of life and stress in college students.

The authors describe the development and preliminary evaluation of the Lifestyle and Habits Questionnaire-brief version (LHQ-B). Three hundred seventy-seven undergraduate students (ages 18-25) participated. Responses were collected through either a web-based or face-to-face survey. Data reductive procedures were used with a preexisting lifestyle inventory to create an abbreviated measure. The relationship between lifestyle domains and indicators of wellbeing (levels of stress and quality of life (QOL)) were also examined. Eight lifestyle domains, encompassing 42 items, were identified and found to have good psychometric properties. The resulting LHQ-B measure can be self-administered/scored and contains norm-referenced feedback. The domains of psychological health, physical health and exercise, and sense of purpose were the best predictors of QOL while psychological health, social concern, and the accident prevention domains predicted levels of stress. The results support the use of the LHQ-B in lifestyle research or as a self-administered measure promoting self-awareness of lifestyle behaviors/attitudes in young adults (18-25 years).