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IntroductionMore payers are closely linking reimbursement to high-value care outcomes such as immunisation rates. Despite this, there remain high rates of pneumonia and influenza-related hospitalisations generating hospital expenditures as high as $11 000 per hospitalisation. Vaccinating the public is an integral part of preventing poor health and utilisation outcomes and is particularly relevant to high-risk patients. As part of a multidisciplinary effort between family and internal medicine residency programmes, our goal was to improve vaccination rates to an average of 76% of eligible Medicaid, low-income and uninsured (MLIU) patients at an academic primary care practice.MethodsThe quality improvement project was completed over 3 months by three primary care resident groups. The setting was a suburban academic primary care practice and eligible patients were 18 years of age or older. Our aim was to increase immunisation rates of pneumococcal, influenza, varicella, herpes zoster virus and tetanus and diphtheria vaccination. There were 1690 patients eligible for the vaccination composite metric. Data were derived from the electronic health record and administrative data.InterventionsCohort 1 developed an initial intervention that consisted of a vaccine questionnaire for patients to complete while in the waiting room. Cohort 2 modified questionnaire after reviewing results from initial intervention. Cohort 3 recommended elimination of questionnaire and implementation of a bundled intervention approach.ResultsThere were minimal improvements in patient immunisation rates after using a patient-directed paper questionnaire. After implementation of multiple interventions via an improvement bundle, there were improvements in immunisation rates which were sustained and the result of special cause variation.ConclusionA key to improving immunisation rates for MLIU patients in this clinic was developing relationships with faculty and staff stakeholders. We received feedback from all the medical staff and then applied it to the interventions and made an impact in the average of vaccinations.

Cancer is a leading cause of death in the United States and across the globe. Cancer screening is an effective preventive measure that can reduce cancer incidence and mortality. While cancer screening is integral to cancer control and prevention, due to the COVID-19 outbreak many screenings have either been canceled or postponed, leaving a vast number of patients without access to recommended health care services. This disruption to cancer screening services may have a significant impact on patients, health care practitioners, and health systems. In this paper, we aim to offer a comprehensive view of the impact of COVID-19 on cancer screening. We present the challenges COVID-19 has exerted on patients, health care practitioners, and health systems as well as potential opportunities that could help address these challenges.

Background: Hospitalized patients are frequently unprepared to care for themselves after discharge often leading to unplanned hospital readmission. One strategy to reduce readmission rates is improving the quality of patient education and preparation before hospital discharge. The ReEngineered Discharge (RED) is a standardized hospital-based program designed to provide patients and caregivers the information they need to continue care at home. Objectives: We sought to study the impact of the RED intervention on posthospitalization adult patient experience scores in an urban academic safety-net hospital. Methods: We conducted a descriptive study of a pilot program that compared posthospitalization survey responses to the Press Ganey survey item “Instructions were given about how to care for yourself at home.” We compared the survey results for 3 groups of adult patients: those receiving the RED program, those receiving a standard discharge on the same hospital unit, and those receiving a standard discharge on other hospital units. Results: A greater percentage of adult patients who received the RED discharge program rated the quality of their discharge as “very good” as compared to those receiving a standard discharge on the same hospital unit and those receiving a standard discharge on other hospital units (61%, 35%, and 41%, respectively, P = .0001). Conclusion: Delivery of a standardized hospital discharge program resulted in a larger proportion of top-box “very good” responses on a Press Ganey posthospitalization survey. Future research should examine whether hospital-based transition programs can sustain improvement in patient experience measures and whether these improvements can be observed in other patient populations.

A growing body of evidence indicates a pivotal role of cognition and in particular executive function in gait control and fall prevention. In a recent gait study using electroencephalographic (EEG) imaging, we provided direct proof for cortical top-down inhibitory control in step adaptation. A crucial part of motor inhibition is recognizing stimuli that signal the need to inhibit or adjust motor actions such as steps during walking. One of the EEG signatures of performance monitoring in response to events signaling the need to adjust motor responses, are error-related potential (error-ERP) features. To examine whether error-ERP features may index executive control during gait adaptation, we analyzed high-density (108-channel) EEG data from an auditory gait pacing study. Participants (N = 18) walking on a steadily moving treadmill were asked to step in time to an auditory cue tone sequence, and then to quickly adapt their step length and rate, to regain step-cue synchrony following occasional unexpected shifts in the pacing cue train to a faster or slower cue tempo. Decomposition of the continuous EEG data by independent component analysis revealed a negative deflection in the source-resolved event-related potential (ERP) time locked to ‘late’ cue tones marking a shift to a slower cue tempo. This vertex-negative ERP feature, localized primarily to posterior medial frontal cortex (pMFC) and peaking 250 ms after the onset of the tempo-shift cue, we here refer to as the step-cue delay negativity (SDN). SDN source, timing, and polarity resemble other error-related ERP features, e.g., the Error-Related Negativity (ERN) and Feedback-Related Negativity (FRN) in (seated) button press response tasks. In single trials, SDN amplitude varied with the magnitude of the cue latency deviation (the time interval between the expected and actual cue onsets). Regression analysis also identified linear coupling between SDN amplitude and the subsequent speed of gait tempo adaptation (as measured by the increase in length of the ensuing adaptation step). The SDN in this paradigm thus seems both to index the perceived need for and the subsequent magnitude of the immediate gait adjustment, consistent with performance-monitoring models. Future research might investigate relationships of these control processes to the impairment of gait adjustment in motor disorders and cognitive decline, for example to develop a biomarker for fall risk prediction in early-stage Parkinson's. •Participants walked on a treadmill in synchrony with a pacing cue train.•Occasional ‘late’ cue tones announced a shift to a slower pacing tempo.•These ‘late’ cues evoked a negative-going ERP peaking 250 ms after cue onset.•This peak indexed both the need for and magnitude of subsequent gait adjustment.•Adapting gait to external challenges involves cortical performance monitoring.

Camouflaging, a phenomenon observed in autistic individuals, refers to the conscious or unconscious strategies that individuals employ to mask, assimilate, or compensate for their autistic characteristics in social settings, in order to blend in or avoid stigmatization. These strategies may include suppression of behaviors considered atypical, imitation of neurotypical behaviors, and use of social scripts to navigate social interactions. While these behaviors have an adaptive goal, they have been linked with mental health issues. Our study examines the two assessment: Methods the Camouflaging Autistic Traits Questionnaire and the discrepancy method. Also examining differences based on sex and diagnosis. We conducted 17 independent meta-analyses, revealing significant differences between autistic individuals, with females displaying consistently higher scores. Autistic individuals showed higher scores when compared to their neurotypical counterparts. Meta-regression analysis suggests age as a relevant moderating factor, impacting comparisons between neurotypical groups. We discuss the differences in the assessment of camouflaging behaviors and the current strengths and limitations of both methods.

Here we demonstrate the suitability of a local mutual information measure for estimating the temporal dynamics of cross-frequency coupling (CFC) in brain electrophysiological signals. In CFC, concurrent activity streams in different frequency ranges interact and transiently couple. A particular form of CFC, phase-amplitude coupling (PAC), has raised interest given the growing amount of evidence of its possible role in healthy and pathological brain information processing. Although several methods have been proposed for PAC estimation, only a few have addressed the estimation of the temporal evolution of PAC, and these typically require a large number of experimental trials to return a reliable estimate. Here we explore the use of mutual information to estimate a PAC measure (MIPAC) in both continuous and event-related multi-trial data. To validate these two applications of the proposed method, we first apply it to a set of simulated phase-amplitude modulated signals and show that MIPAC can successfully recover the temporal dynamics of the simulated coupling in either continuous or multi-trial data. Finally, to explore the use of MIPAC to analyze data from human event-related paradigms, we apply it to an actual event-related human electrocorticographic (ECoG) data set that exhibits strong PAC, demonstrating that the MIPAC estimator can be used to successfully characterize amplitude-modulation dynamics in electrophysiological data. •We propose a new information theory based approach (MIPAC), to estimate dynamic changes in phase-amplitude coupling of electrophysiological signals.•MIPAC is model-free and can capture nonlinear interactions between phase and amplitude of a signal.•Results from simulations and applications to real data suggest that MIPAC may be suitable for application in pathologies such as epilepsy, where the timevarying nature of PAC is crucial.

Reproducibility is a cornerstone of scientific communication without which one cannot build upon each other’s work. Because modern human brain imaging relies on many integrated steps with a variety of possible algorithms, it has, however, become impossible to report every detail of a data processing workflow. In response to this analytical complexity, community recommendations are to share data analysis pipelines (scripts that implement workflows). Here we show that this can easily be done using EEGLAB and tools built around it. BIDS tools allow importing all the necessary information and create a study from electroencephalography (EEG)-Brain Imaging Data Structure compliant data. From there preprocessing can be carried out in only a few steps using EEGLAB and statistical analyses performed using the LIMO EEG plug-in. Using Wakeman and Henson (2015) face dataset, we illustrate how to prepare data and build different statistical models, a standard factorial design (faces ∗ repetition), and a more modern trial-based regression approach for the stimulus repetition effect, all in a few reproducible command lines.

EEGLAB signal processing environment is currently the leading open-source software for processing electroencephalographic (EEG) data. The Neuroscience Gateway (NSG, nsgportal.org) is a web and API-based portal allowing users to easily run a variety of neuroscience-related software on high-performance computing (HPC) resources in the U.S. XSEDE network. We have reported recently (Delorme et al., 2019) on the Open EEGLAB Portal expansion of the free NSG services to allow the neuroscience community to build and run MATLAB pipelines using the EEGLAB tool environment. We are now releasing an EEGLAB plug-in, nsgportal, that interfaces EEGLAB with NSG directly from within EEGLAB running on MATLAB on any personal lab computer. The plug-in features a flexible MATLAB graphical user interface (GUI) that allows users to easily submit, interact with, and manage NSG jobs, and to retrieve and examine their results. Command line nsgportal tools supporting these GUI functionalities allow EEGLAB users and plug-in tool developers to build largely automated functions and workflows that include optional NSG job submission and processing. Here we present details on nsgportal implementation and documentation, provide user tutorials on example applications, and show sample test results comparing computation times using HPC versus laptop processing.

In this report we present a mobile brain/body imaging (MoBI) dataset that allows study of source-resolved cortical dynamics supporting coordinated gait movements in a rhythmic auditory cueing paradigm. Use of an auditory pacing stimulus stream has been recommended to identify deficits and treat gait impairments in neurologic populations. Here, the rhythmic cueing paradigm required healthy young participants to walk on a treadmill (constant speed) while attempting to maintain step synchrony with an auditory pacing stream and to adapt their step length and rate to unanticipated shifts in tempo of the pacing stimuli (e.g., sudden shifts to a faster or slower tempo). High-density electroencephalography (EEG, 108 channels), surface electromyography (EMG, bilateral tibialis anterior), pressure sensors on the heel (to register timing of heel strikes), and goniometers (knee, hip, and ankle joint angles) were concurrently recorded in 20 participants. The data is provided in the Brain Imaging Data Structure (BIDS) format to promote data sharing and reuse, and allow the inclusion of the data into fully automated data analysis workflows.

Tuberculosis (TB) is a bacterial infection caused by ( ). B cells are the central mediator of the humoral response; they are responsible for producing antibodies in addition to mediating other functions. The role of the cellular response during the TB spectrum by B cells is still controversial. In this study, we evaluated the distribution of the circulating B cell subsets in patients with active and latent TB (ATB and LTB, respectively) and how they respond to stimuli of protein or lipid from Here, we show that ATB patients show an immune fingerprinting. However, patients with drug-sensitive- (DS-TB) or drug-resistant- (DR-TB) TB have altered frequencies of circulating B cells. DS-TB and DR-TB display a unique profile characterized by high systemic levels of IFN-γ, IL-10, IgG, IgG/IgM ratio, and total B cells. Moreover, B cells from DR-TB are less efficient in producing IL-10, and both DS-TB and DR-TB produce less IFN-γ in response to antigens. These results provide new insights into the population dynamics of the cellular immune response by B cells against and suggest a fingerprinting to characterize the B-cell response on DR-TB.