A novel risk-adjusted metric to compare hospitals on their antibiotic-prescribing at hospital discharge.

BACKGROUND: Antibiotic overuse at hospital discharge is common, but there is no metric to evaluate hospital performance at this transition of care. We built a risk-adjusted metric for comparing hospitals on their overall post-discharge antibiotic use. METHODS: This was a retrospective study across all acute-care admissions within the Veterans Health Administration during 2018-2021. For patients discharged to home, we collected data on antibiotics and relevant covariates. We built a zero-inflated negative binomial mixed-model with two random intercepts for each hospital to predict post-discharge antibiotic exposure and length of therapy (LOT). Data were split into training and testing sets to evaluate model performance using absolute error. Hospital performance was determined by the predicted random intercepts. RESULTS: 1,804,300 patient-admissions across 129 hospitals were included. Antibiotics were prescribed to 41.5% while hospitalized and 19.5% at discharge. Median LOT among those prescribed post-discharge antibiotics was 7 (IQR 4-10). The predictive model detected post-discharge antibiotic use with fidelity, including accurate identification of any exposure (area under the precision-recall curve=0.97) and reliable prediction of post-discharge LOT (mean absolute error = 1.48). Based on this model, 39 (30.2%) hospitals prescribed antibiotics less often than expected at discharge and used shorter LOT than expected. Twenty-eight (21.7%) hospitals prescribed antibiotics more often at discharge and used longer LOT. CONCLUSION: A model using electronically-available data was able to predict antibiotic use prescribed at hospital discharge and showed that some hospitals were more successful in reducing antibiotic overuse at this transition of care. This metric may help hospitals identify opportunities for improved antibiotic stewardship at discharge.

Nonparametric predictive model for sparse and irregular longitudinal data.

We propose a kernel-based estimator to predict the mean response trajectory for sparse and irregularly measured longitudinal data. The kernel estimator is constructed by imposing weights based on the subject-wise similarity on L2 metric space between predictor trajectories, where we assume that an analogous fashion in predictor trajectories over time would result in a similar trend in the response trajectory among subjects. In order to deal with the curse of dimensionality caused by the multiple predictors, we propose an appealing multiplicative model with multivariate Gaussian kernels. This model is capable of achieving dimension reduction as well as selecting functional covariates with predictive significance. The asymptotic properties of the proposed nonparametric estimator are investigated under mild regularity conditions. We illustrate the robustness and flexibility of our proposed method via extensive simulation studies and an application to the Framingham Heart Study.

Impact of the Dopamine System on Long-Term Cognitive Impairment in Parkinson Disease: An Exploratory Study.

Background: Little is known about the impact of the dopamine system on development of cognitive impairment (CI) in Parkinson disease (PD). Objectives: We used data from a multi-site, international, prospective cohort study to explore the impact of dopamine system-related biomarkers on CI in PD. Methods: PD participants were assessed annually from disease onset out to 7 years, and CI determined by applying cut-offs to four measures: (1) Montreal Cognitive Assessment; (2) detailed neuropsychological test battery; (3) Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) cognition score; and (4) site investigator diagnosis of CI (mild cognitive impairment or dementia). The dopamine system was assessed by serial Iodine-123 Ioflupane dopamine transporter (DAT) imaging, genotyping, and levodopa equivalent daily dose (LEDD) recorded at each assessment. Multivariate longitudinal analyses, with adjustment for multiple comparisons, determined the association between dopamine system-related biomarkers and CI, including persistent impairment. Results: Demographic and clinical variables associated with CI were higher age, male sex, lower education, non-White race, higher depression and anxiety scores and higher MDS-UPDRS motor score. For the dopamine system, lower baseline mean striatum dopamine transporter values (P range 0.003-0.005) and higher LEDD over time (P range <0.001-0.01) were significantly associated with increased risk for CI. Conclusions: Our results provide preliminary evidence that alterations in the dopamine system predict development of clinically-relevant, cognitive impairment in Parkinson's disease. If replicated and determined to be causative, they demonstrate that the dopamine system is instrumental to cognitive health status throughout the disease course. TRIAL REGISTRATION: Parkinson's Progression Markers Initiative is registered with ClinicalTrials.gov (NCT01141023).

The use of telehealth-supported stewardship activities in acute-care and long-term care settings: An implementation effectiveness trial.

BACKGROUND: We assessed the implementation of telehealth-supported stewardship activities in acute-care units and long-term care (LTC) units in Veterans' Administration medical centers (VAMCs). DESIGN: Before-and-after, quasi-experimental implementation effectiveness study with a baseline period (2019-2020) and an intervention period (2021). SETTING: The study was conducted in 3 VAMCs without onsite infectious disease (ID) support. PARTICIPANTS: The study included inpatient providers at participating sites who prescribe antibiotics. INTERVENTION: During 2021, an ID physician met virtually 3 times per week with the stewardship pharmacist at each participating VAMC to review patients on antibiotics in acute-care units and LTC units. Real-time feedback on prescribing antibiotics was given to providers. Additional implementation strategies included stakeholder engagement, education, and quality monitoring. METHODS: The reach-effectiveness-adoption-implementation-maintenance (RE-AIM) framework was used for program evaluation. The primary outcome of effectiveness was antibiotic days of therapy (DOT) per 1,000 days present aggregated across all 3 sites. An interrupted time-series analysis was performed to compare this rate during the intervention and baseline periods. Electronic surveys, periodic reflections, and semistructured interviews were used to assess other RE-AIM outcomes. RESULTS: The telehealth program reviewed 502 unique patients and made 681 recommendations to 24 providers; 77% of recommendations were accepted. After program initiation, antibiotic DOT immediately decreased in the LTC units (-30%; P < .01) without a significant immediate change in the acute-care units (+16%; P = .22); thereafter DOT remained stable in both settings. Providers generally appreciated feedback and collaborative discussions. CONCLUSIONS: The implementation of our telehealth program was associated with reductions in antibiotic use in the LTC units but not in the smaller acute-care units. Overall, providers perceived the intervention as acceptable. Wider implementation of telehealth-supported stewardship activities may achieve reductions in antibiotic use.

Applying the Worker Well-Being Framework to Identify Factors that Impact Turnover Among Long-Haul Truck Drivers.

BACKGROUND: Drivers in the long-haul trucking industry have chronic health conditions, engage in unhealthy behaviors, and leave the industry at high rates. Previous work has not considered the health and safety outcomes resulting from the conditions of work in the trucking industry and their role in turnover. The goal of this study was to understand the expectations of an incoming workforce, explore how work conditions impact their well-being, and identify strategies for retention. METHODS: Semi-structured interviews were conducted among current long-haul drivers and supervisors at trucking companies, and students and instructors at trucking schools (n = 33). Participants were asked about why they decided to enter the industry, their health challenges related to being in the trucking industry and whether these challenges were related to turnover, and strategies for retention. FINDINGS: Health conditions, differences in job expectations, and work demands were associated with leaving the industry. Workplace policies and culture (e.g., lack of supervisor support, schedules that limited home time, company size, and lack of benefits) were associated with workers' intention to leave an organization. Strategies identified to improve retention included integrating health and wellness into onboarding, creating realistic job expectations for those entering the industry, establishing relationships with drivers and dispatchers, and developing policies to limit time away from family. CONCLUSION/APPLICATION TO PRACTICE: Turnover in the trucking industry is a persistent problem and leads to a shortage of skilled workers, increases the workload, and reduces productivity. Understanding the relationship between the conditions of work and well-being provides a more holistic approach to address the health, safety, and well-being of long-haul truck drivers. Health conditions, differences in job expectations, and work demands were associated with leaving the industry. Workplace policies and culture (e.g., supervisor support, schedules that limited home time, lack of benefits) were associated with workers' intention to leave an organization. These conditions provide an opportunity for occupational health interventions to promote the physical as well as psychological health of long-haul truck drivers.

The validity of hospital diagnostic and procedure codes reflecting morbidity in preterm neonates born <32 weeks gestation.

OBJECTIVE: To determine the validity of diagnostic hospital billing codes for complications of prematurity in neonates <32 weeks gestation. STUDY DESIGN: Retrospective cohort data from discharge summaries and clinical notes (n = 160) were reviewed by trained, blinded abstractors for the presence of intraventricular hemorrhage (IVH) grades 3 or 4, periventricular leukomalacia (PVL), necrotizing enterocolitis (NEC), stage 3 or higher, retinopathy of prematurity (ROP), and surgery for NEC or ROP. Data were compared to diagnostic billing codes from the neonatal electronic health record. RESULTS: IVH, PVL, ROP and ROP surgery had strong positive predictive values (PPV > 75%) and excellent negative predictive values (NPV > 95%). The PPVs for NEC (66.7%) and NEC surgery (37.1%) were low. CONCLUSION: Diagnostic hospital billing codes were observed to be a valid metric to evaluate preterm neonatal morbidities and surgeries except in the instance of more ambiguous diagnoses such as NEC and NEC surgery.

Bispectral EEG (BSEEG) Algorithm Captures High Mortality Risk Among 1,077 Patients: Its Relationship to Delirium Motor Subtype.

OBJECTIVE: Delirium is dangerous and a predictor of poor patient outcomes. We have previously reported the utility of the bispectral EEG (BSEEG) with a novel algorithm for the detection of delirium and prediction of patient outcomes including mortality. The present study employed a normalized BSEEG (nBSEEG) score to integrate the previous cohorts to combine their data to investigate the prediction of patient outcomes. We also aimed to test if the BSEEG method can be applicable regardless of age, and independent of delirium motor subtypes. METHODS: We calculated nBSEEG score from raw BSEEG data in each cohort and classified patients into BSEEG-positive and BSEEG-negative groups. We used log-rank test and Cox proportional hazards models to predict 90-day and 1-year outcomes for the BSEEG-positive and -negative groups in all subjects and motor subgroups. RESULTS: A total of 1,077 subjects, the BSEEG-positive group showed significantly higher 90-day (hazard ratio 1.33 [95% CI 1.16-1.52] and 1-year (hazard ratio 1.22 [95% CI 1.06-1.40] mortality rates than the negative group after adjustment for covariates such as age, sex, CCI, and delirium status. Among patients with different motor subtypes of delirium, the hypoactive group showed significantly higher 90-day (hazard ratio 1.41 [95% CI 1.12-1.76] and 1-year mortality rates (hazard ratio 1.32 [95% CI 1.05-1.67], which remained significant after adjustment for the same covariates. CONCLUSION: We found that the BSEEG method is capable of capturing patients at high mortality risk.

Anti-inflammatory medication use associated with reduced delirium risk and all-cause mortality: A retrospective cohort study.

OBJECTIVE: To investigate the relationship between history of anti-inflammatory medication use and delirium risk, as well as long-term mortality. METHODS: In this retrospective cohort study, subjects recruited between January 2016 and March 2020 were analyzed. Information about anti-inflammatory medication use history including aspirin, NSAIDs, glucosamine, and other anti-inflammatory drugs, was collected. Logistic regression analysis investigated the relationship between anti-inflammatory medications and delirium. Log-rank analysis and cox proportional hazards model investigated the relationship between anti-inflammatory medications and one-year mortality. RESULTS: The data from 1274 subjects were analyzed. The prevalence of delirium was significantly lower in subjects with NSAIDs usage (23.0%) than in those without NSAIDs usage (35.0%) (p < 0.001). Logistic regression analysis controlling for age, sex, dementia status, and hospitalization department showed that the risk of delirium tended to be reduced by a history of NSAIDs use (OR, 0.76 [95% CI, 0.55 to 1.03]). The one-year mortality in the subjects with NSAIDs (survival rate, 0.879 [95% CI, 0.845 to 0.906]) was significantly lower than in the subjects without NSAIDs (survival rate, 0.776 [95% CI, 0.746 to 0.803]) (p < 0.001). A history of NSAIDs use associated with the decreased risk of one-year mortality even after adjustment for age, sex, Charlson Comorbidity Index, delirium status, and hospitalization department (HR, 0.70 [95% CI, 0.51 to 0.96]). CONCLUSION: This study suggested that NSAIDs usage was associated with decreased delirium prevalence and lower one-year mortality. The potential benefit of NSAIDs on delirium risk and mortality were shown.

Metformin use history and genome-wide DNA methylation profile: potential molecular mechanism for aging and longevity.

BACKGROUND: Metformin, a commonly prescribed anti-diabetic medication, has repeatedly been shown to hinder aging in pre-clinical models and to be associated with lower mortality for humans. It is, however, not well understood how metformin can potentially prolong lifespan from a biological standpoint. We hypothesized that metformin's potential mechanism of action for longevity is through its epigenetic modifications. METHODS: To test our hypothesis, we conducted a post-hoc analysis of available genome-wide DNA methylation (DNAm) data obtained from whole blood collected from inpatients with and without a history of metformin use. We assessed the methylation profile of 171 patients (first run) and only among 63 diabetic patients (second run) and compared the DNAm rates between metformin users and nonusers. RESULTS: Enrichment analysis from the Kyoto Encyclopedia of Genes and Genome (KEGG) showed pathways relevant to metformin's mechanism of action, such as longevity, AMPK, and inflammatory pathways. We also identified several pathways related to delirium whose risk factor is aging. Moreover, top hits from the Gene Ontology (GO) included HIF-1α pathways. However, no individual CpG site showed genome-wide statistical significance (p < 5E-08). CONCLUSION: This study may elucidate metformin's potential role in longevity through epigenetic modifications and other possible mechanisms of action.

The genome-wide DNA methylation profiles among neurosurgery patients with and without post-operative delirium.

AIMS: There is no previous study demonstrating the differences of genome-wide DNA methylation (DNAm) profiles between patients with and without postoperative delirium (POD). We aimed to discover epigenetic (DNAm) markers that are associated with POD in blood obtained from patients before and after neurosurgery. METHODS: Pre- and post-surgical blood DNA samples from 37 patients, including 10 POD cases, were analyzed using the Illumina EPIC array genome-wide platform. We examined DNAm differences in blood from patients with and without POD. Enrichment analysis with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes terms were also conducted. RESULTS: When POD cases were tested for DNAm change before and after surgery, enrichment analyses showed many relevant signals with statistical significance in immune response related-pathways and inflammatory cytokine related-pathways such as "cellular response to cytokine stimulus", "regulation of immune system process", "regulation of cell activation", and "regulation of cytokine production". Furthermore, after excluding the potential effect of common factors related to surgery and anesthesia between POD cases and non-POD controls, the enrichment analyses showed significant signals such as "immune response" and "T cell activation", which are same pathways previously identified from an independent non-surgical inpatient cohort. CONCLUSIONS: Our first genome-wide DNAm investigation of POD showed promising signals related to immune response, inflammatory response and other relevant signals considered to be associated with delirium pathophysiology. Our data supports the hypothesis that epigenetics play an important role in the pathophysiological mechanism of delirium and suggest the potential usefulness of an epigenetics-based biomarker of POD.

The potential benefit of metformin to reduce delirium risk and mortality: a retrospective cohort study.

PURPOSE: Metformin has been reported to improve age-related disorders, including dementia, and to lower mortality. This study was conducted to investigate whether metformin use lower delirium risk, as well as long-term mortality. METHODS: In this retrospective cohort study, previously recruited 1,404 subjects were analyzed. The relationship between metformin use and delirium, and the relationship between metformin use and 3-year mortality were investigated. MAIN FINDINGS: 242 subjects were categorized into a type 2 diabetes mellitus (DM)-without-metformin group, and 264 subjects were categorized into a DM-with-metformin group. Prevalence of delirium was 36.0% in the DM-without-metformin group, and 29.2% in the DM-with-metformin group. A history of metformin use reduced the risk of delirium in patients with DM (OR, 0.50 [95% CI, 0.32 to 0.79]) after controlling for confounding factors. The 3-year mortality in the DM-without-metformin group (survival rate, 0.595 [95% CI, 0.512 to 0.669]) was higher than in the DM-with-metformin group (survival rate, 0.695 [95% CI, 0.604 to 0.770]) (p=0.035). A history of metformin use decreased the risk of 3-year mortality after adjustment for confounding factors (HR, 0.69 [95% CI, 0.48 to 0.98]). CONCLUSIONS: Metformin use may lower the risk of delirium and mortality in DM patients.

Genome-wide DNA methylation analysis of post-operative delirium with brain, blood, saliva, and buccal samples from neurosurgery patients.

OBJECTIVE: No previous study demonstrates the difference in the genome-wide DNA methylation status of post-operative delirium (POD) using human brain tissue obtained from neurosurgery and multiple peripheral tissues such as blood, saliva, and buccal samples from the same individuals. We aimed to identify epigenetic marks of DNA methylation in the brain and peripheral tissues to elucidate the potential pathophysiological mechanism of POD. METHODS: The four tissue types (brain, blood, saliva, buccal) of DNA samples from up to 40 patients, including 11 POD cases, were analyzed using Illumina EPIC array. DNAm differences between patients with and without POD were examined. We also conducted enrichment analysis based on the top DNAm signals. RESULTS: The most different CpG site between control and POD was found at cg16526133 near the ADAMTS9 gene from the brain tissue(p = 8.66E-08). However, there are no CpG sites to reach the genome-wide significant level. The enrichment analysis based on the 1000 top hit CpG site (p < 0.05) on the four tissues showed several intriguing pathways. In the brain, there are pathways including "positive regulation of glial cell differentiation". Blood samples showed also pathways related to immune function. Besides, both saliva and the buccal sample showed pathways related to circadian rhythm, although these findings were not FDR significant. CONCLUSION: Enrichment analysis found several intriguing pathways related to potential delirium pathophysiology. Present data may further support the role of epigenetics, especially DNA methylation, in the molecular mechanisms of delirium pathogenesis.

Longitudinal clinical and biomarker characteristics of non-manifesting LRRK2 G2019S carriers in the PPMI cohort.

We examined 2-year longitudinal change in clinical features and biomarkers in LRRK2 non-manifesting carriers (NMCs) versus healthy controls (HCs) enrolled in the Parkinson's Progression Markers Initiative (PPMI). We analyzed 2-year longitudinal data from 176 LRRK2 G2019S NMCs and 185 HCs. All participants were assessed annually with comprehensive motor and non-motor scales, dopamine transporter (DAT) imaging, and biofluid biomarkers. The latter included cerebrospinal fluid (CSF) Abeta, total tau and phospho-tau; serum urate and neurofilament light chain (NfL); and urine bis(monoacylglycerol) phosphate (BMP). At baseline, LRRK2 G2019S NMCs had a mean (SD) age of 62 (7.7) years and were 56% female. 13% had DAT deficit (defined as <65% of age/sex-expected lowest putamen SBR) and 11% had hyposmia (defined as ≤15th percentile for age and sex). Only 5 of 176 LRRK2 NMCs developed PD during follow-up. Although NMCs scored significantly worse on numerous clinical scales at baseline than HCs, there was no longitudinal change in any clinical measures over 2 years or in DAT binding. There were no longitudinal differences in CSF and serum biomarkers between NMCs and HCs. Urinary BMP was significantly elevated in NMCs at all time points but did not change longitudinally. Neither baseline biofluid biomarkers nor the presence of DAT deficit correlated with 2-year change in clinical outcomes. We observed no significant 2-year longitudinal change in clinical or biomarker measures in LRRK2 G2019S NMCs in this large, well-characterized cohort even in the participants with baseline DAT deficit. These findings highlight the essential need for further enrichment biomarker discovery in addition to DAT deficit and longer follow-up to enable the selection of NMCs at the highest risk for conversion to enable future prevention clinical trials.

The Perioperative Pain Self-Management (PePS) randomized controlled trial protocol: Preventing chronic post-surgical pain and prolonged opioid use.

BACKGROUND: Total joint arthroplasties are common orthopedic surgeries that carry risk for developing chronic post-surgical pain. In addition to pre- and post-operative pain severity, psychological distress (e.g., anxiety, pain catastrophizing) is a risk factor for chronic postsurgical pain. Cognitive behavioral therapy (CBT) for chronic pain is an empirically supported approach to managing chronic pain, functional impairment, and related distress. While CBT has been used extensively in patients with established chronic pain, using it as a preventive intervention targeting the transition from acute to chronic postsurgical pain is a novel application. OBJECTIVES: The Perioperative Pain Self-Management (PePS) program is a pain self-management intervention based on the principles of CBT. This innovative intervention is brief, flexible, and is delivered remotely. The current study aims to determine the efficacy of PePS compared to standard care on reducing the incidence of significant surgical site pain at 6-months post-surgery. The current study also aims to evaluate the context for subsequent implementation. METHODS: This study is a hybrid type I efficacy-preparing for implementation trial. It is a two-site, single-blind, two-arm, parallel, randomized control trial. Surgical patients will be randomized to either receive: 1) PePS plus standard care, or 2) Standard care. The primary end point will be surgical site pain severity at 6-months post-surgery. CONCLUSION: Results from this study are expected to result in support for a brief scalable intervention (PePS) that can prevent the development of chronic pain and prolonged post-surgical opioid use, as well as key details to inform subsequent implementation. CLINICALTRIALS: govIdentifier:NCT04979429.

Evaluation of heparinized syringes for measuring newborn metabolites in neonates with a central arterial line.

Newborn metabolic screening is emerging as a novel method for predicting neonatal morbidity and mortality in neonates born very preterm (<32 weeks gestation). The purpose of our study was to determine if blood collected by an electrolyte-balanced dry lithium heparin syringe, as is routine for blood gas measurements, affects targeted metabolite and biomarker levels. Two blood samples (one collected with a heparinized syringe and the other with a non-heparinized syringe) were obtained at the same time from 20 infants with a central arterial line and tested for 49 metabolites and biomarkers using standard procedures for newborn screening. Overall, the median metabolite levels did not significantly differ by syringe type. However, there was wide variability, particularly for amino acids and immunoreactive trypsinogen, for individual paired samples and therefore, consideration should be given to sample collection when using these metabolites in prediction models of neonatal morbidity and mortality.

Sex-Related Longitudinal Change of Motor, Non-Motor, and Biological Features in Early Parkinson's Disease.

BACKGROUND: Investigation of sex-related motor and non-motor differences and biological markers in Parkinson's disease (PD) may improve precision medicine approach. OBJECTIVE: To examine sex-related longitudinal changes in motor and non-motor features and biologic biomarkers in early PD. METHODS: We compared 5-year longitudinal changes in de novo, untreated PD men and women (at baseline N = 423; 65.5%male) of the Parkinson's Progression Markers Initiative (PPMI), assessing motor and non-motor manifestations of disease; and biologic measures in cerebrospinal fluid (CSF) and dopamine transporter deficit on DaTscanTM uptake. RESULTS: Men experienced greater longitudinal decline in self-reported motor (p < 0.001) and non-motor (p = 0.009) aspects of experiences of daily living, such that men had a yearly increase in MDS-UPDRS part II by a multiplicative factor of 1.27 compared to women at 0.7, while men had a yearly increase in MDS-UPDRS part I by a multiplicative factor of 0.98, compared to women at 0.67. Compared to women, men had more longitudinal progression in clinician-assessed motor features in the ON medication state (p = 0.010) and required higher dopaminergic medication dosages over time (p = 0.014). Time to reach specific disease milestones and longitudinal changes in CSF biomarkers and DaTscanTM uptake were not different by sex. CONCLUSION: Men showed higher self-assessed motor and non-motor burden of disease, with possible contributions from suboptimal dopaminergic therapeutic response in men. However, motor features of disease evaluated with clinician-based scales in the OFF medication state, as well as biological biomarkers do not show specific sex-related progression patterns.

Low soluble amyloid-ß 42 is associated with smaller brain volume in Parkinson's disease.

INTRODUCTION: We sought to examine whether levels of soluble alpha-synuclein (α-syn), amyloid-beta (Aß42), phosphorylated tau (p-tau), and total tau (t-tau), as measured in cerebrospinal fluid (CSF), are associated with changes in brain volume in Parkinson's disease. METHODS: We assessed the 4-year change in total brain volume (n = 99) and baseline CSF α-syn, Aß42, p-tau, and t-tau of Parkinson Progression Markers Initiative participants. We used linear mixed models to assess the longitudinal effect of baseline CSF biomarkers on total and regional brain volume and thickness as well as linear regression for cross-sectional analyses at baseline and year 2. All models were adjusted for age and gender; brain volume models also adjusted for baseline intracranial volume. Bonferroni correction was applied. RESULTS: The 4-year change in total brain volume was -21.2 mm3 (95% confidence interval, -26.1, -16.3). There were no significant associations between the 4-year change in total brain volume and baseline levels of any CSF biomarker (all p-values > 0.05). On cross-sectional analyses, CSF Aß42 was linearly associated with total brain volume at baseline (R2 = 0.60, p = 0.0004) and at year 2 (R2 = 0.66, p < 0.0001), with CSF Aß42 < 1100 pg/ml, the threshold for brain amyloid pathology, associated with smaller total brain volume at baseline (p = 0.0010) and at year 2 (p = 0.0002). CSF α-syn was linearly associated with total brain volume at baseline (R2 = 0.58, p = 0.0044) but not at year 2 (R2 = 0.58, p = 0.1342). CONCLUSION: Reduction in soluble Aß42 is associated with lower total brain volume in Parkinson's disease.

Predictive generalized varying-coefficient longitudinal model.

We propose a nonparametric bivariate varying coefficient generalized linear model to predict a mean response trajectory in the future given an individual's characteristics at present or an earlier time point in a longitudinal study. Given the measurement time of the predictors, the coefficients vary as functions of the future time over which the prediction of the mean response is concerned and illustrate the dynamic association between the future response and the earlier measured predictors. We use a nonparametric approach that takes advantage of features of both the kernel and the spline methods for estimation. The resulting coefficient estimator is asymptotically consistent under mild regularity conditions. We also develop a new bootstrap approach to construct simultaneous confidence bands for statistical inference about the coefficients and the predicted response trajectory based on the coverage rate of bootstrap estimates. We use the Framingham Heart Study to illustrate the methodology. The proposed procedure is applied to predict the probability trajectory of hypertension risk given individuals' health condition in early adulthood and to examine the impact of risk factors in early adulthood on a long-term risk of hypertension over several decades.

Mortality among patients with sepsis associated with a bispectral electroencephalography (BSEEG) score.

We have previously developed a bispectral electroencephalography (BSEEG) device, which was shown to be effective in detecting delirium and predicting patient outcomes. In this study we aimed to apply the BSEEG approach for a sepsis. This was a retrospective cohort study conducted at a single center. Sepsis-positive cases were identified based on retrospective chart review. EEG raw data and calculated BSEEG scores were obtained in the previous studies. The relationship between BSEEG scores and sepsis was analyzed, as well as the relationship among sepsis, BSEEG score, and mortality. Data were analyzed from 628 patients. The BSEEG score from the first encounter (1st BSEEG) showed a significant difference between patients with and without sepsis (p = 0.0062), although AUC was very small indicating that it is not suitable for detection purpose. Sepsis patients with high BSEEG scores showed the highest mortality, and non-sepsis patients with low BSEEG scores showed the lowest mortality. Mortality of non-sepsis patients with high BSEEG scores was as bad as that of sepsis patients with low BSEEG scores. Even adjusting for age, gender, comorbidity, and sepsis status, BSEEG remained a significant predictor of mortality (p = 0.008). These data are demonstrating its usefulness as a potential tool for identification of patients at high risk and management of sepsis.

Mortality prediction by bispectral electroencephalography among 502 patients: its role in dementia.

Complications of delirium and dementia increase mortality; however, it is difficult to diagnose delirium accurately, especially among dementia patients. The bispectral electroencephalography score can detect delirium and predict mortality in elderly patients. We aimed to develop an efficient and reliable bispectral electroencephalography device for high-throughput screening. We also hypothesized that bispectral electroencephalography score can predict mortality among dementia patients. A prospective cohort study was conducted between January 2016 and December 2018 to measure bispectral electroencephalography from elderly patients and correlate with outcomes. A total of 502 elderly (55 years old or older) patients with and without dementia were enrolled. For a replication of the utility of bispectral electroencephalography, mortalities between bispectral electroencephalography-positive and bispectral electroencephalography-negative group were compared. In addition, patients with and without dementia status were added to examine the utility of bispectral electroencephalography among dementia patients. The mortality within 180 days in the bispectral electroencephalography-positive group was higher than that of the bispectral electroencephalography-negative group in both the replication and the total cohorts. Mortality of those in the bispectral electroencephalography-positive group showed a dose-dependent increase in both cohorts. When the dementia patients showed bispectral electroencephalography positive, their mortality was significantly higher than those with dementia but who were bispectral electroencephalography-negative. Mortality within 30 days in the bispectral electroencephalography-positive group was significantly higher than that of the bispectral electroencephalography-negative group. The utility of the bispectral electroencephalography to predict mortality among large sample of 502 elderly patients was shown. The bispectral electroencephalography score can predict mortality among elderly patients in general, and even among dementia patients, as soon as 30 days.