42 research outputs found
Acute Sleep Deprivation and Circadian Misalignment Associated with Transition onto the First Night of Work Impairs Visual Selective Attention
Background: Overnight operations pose a challenge because our circadian biology promotes sleepiness and dissipates wakefulness at night. Since the circadian effect on cognitive functions magnifies with increasing sleep pressure, cognitive deficits associated with night work are likely to be most acute with extended wakefulness, such as during the transition from a day shift to night shift. Methodology/Principal Findings: To test this hypothesis we measured selective attention (with visual search), vigilance (with Psychomotor Vigilance Task [PVT]) and alertness (with a visual analog scale) in a shift work simulation protocol, which included four day shifts followed by three night shifts. There was a nocturnal decline in cognitive processes, some of which were most pronounced on the first night shift. The nighttime decrease in visual search sensitivity was most pronounced on the first night compared with subsequent nights (pâ=â.04), and this was accompanied by a trend towards selective attention becoming âfast and sloppyâ. The nighttime increase in attentional lapses on the PVT was significantly greater on the first night compared to subsequent nights (p<.05) indicating an impaired ability to sustain focus. The nighttime decrease in subjective alertness was also greatest on the first night compared with subsequent nights (p<.05). Conclusions/Significance: These nocturnal deficits in attention and alertness offer some insight into why occupational errors, accidents, and injuries are pronounced during night work compared to day work. Examination of the nighttime vulnerabilities underlying the deployment of attention can be informative for the design of optimal work schedules and the implementation of effective countermeasures for performance deficits during night work
Opportunistic Detection of Type 2 Diabetes Using Deep Learning From Frontal Chest Radiographs
Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulatory chest radiographs (CXRs) frequently ordered, we investigated detecting type 2 diabetes (T2D) by combining radiographic and EHR data using a DL model. Our model, developed from 271,065 CXRs and 160,244 patients, was tested on a prospective dataset of 9,943 CXRs. Here we show the model effectively detected T2D with a ROC AUC of 0.84 and a 16% prevalence. The algorithm flagged 1,381 cases (14%) as suspicious for T2D. External validation at a distinct institution yielded a ROC AUC of 0.77, with 5% of patients subsequently diagnosed with T2D. Explainable AI techniques revealed correlations between specific adiposity measures and high predictivity, suggesting CXRs\u27 potential for enhanced T2D screening
A multi-level system quality improvement intervention to reduce racial disparities in hypertension care and control: study protocol
BACKGROUND: Racial disparities in blood pressure control have been well documented in the United States. Research suggests that many factors contribute to this disparity, including barriers to care at patient, clinician, healthcare system, and community levels. To date, few interventions aimed at reducing hypertension disparities have addressed factors at all of these levels. This paper describes the design of Project ReD CHiP (Reducing Disparities and Controlling Hypertension in Primary Care), a multi-level system quality improvement project. By intervening on multiple levels, this project aims to reduce disparities in blood pressure control and improve guideline concordant hypertension care. METHODS: Using a pragmatic trial design, we are implementing three complementary multi-level interventions designed to improve blood pressure measurement, provide patient care management services and offer expanded provider education resources in six primary care clinics in Baltimore, Maryland. We are staggering the introduction of the interventions and will use Statistical Process Control (SPC) charting to determine if there are changes in outcomes at each clinic after implementation of each intervention. The main hypothesis is that each intervention will have an additive effect on improvements in guideline concordant care and reductions in hypertension disparities, but the combination of all three interventions will result in the greatest impact, followed by blood pressure measurement with care management support, blood pressure measurement with provider education, and blood pressure measurement only. This study also examines how organizational functioning and cultural competence affect the success of the interventions. DISCUSSION: As a quality improvement project, Project ReD CHiP employs a novel study design that specifically targets multi-level factors known to contribute to hypertension disparities. To facilitate its implementation and improve its sustainability, we have incorporated stakeholder input and tailored components of the interventions to meet the specific needs of the involved clinics and communities. Results from this study will provide knowledge about how integrated multi-level interventions can improve hypertension care and reduce disparities. TRIAL REGISTRATION: ClinicalTrials.gov NCT0156686
COVID-19 first lockdown as a window into language acquisition : associations between caregiver-child activities and vocabulary gains
The COVID-19 pandemic, and the resulting closure of daycare centers worldwide, led to unprecedented changes in childrenâs learning environments. This period of increased time at home with caregivers, with limited access to external sources (e.g., daycares) provides a unique opportunity to examine the associations between the caregiver-child activities and childrenâs language development. The vocabularies of 1742 children aged8-36 months across 13 countries and 12 languages were evaluated at the beginning and end of the first lockdown period in their respective countries(from March to September 2020). Children who had less passive screen exposure and whose caregivers read more to them showed larger gains in vocabulary development during lockdown, after controlling for SES and other caregiver-child activities. Children also gained more words than expected (based on normative data) during lockdown; either caregivers were more aware of their childâs development or vocabulary development benefited from intense caregiver-child interaction during lockdown
COVID-19 first lockdown as a window into language acquisition: Associations between caregiver-child activities and vocabulary gains
The COVID-19 pandemic, and the resulting closure of daycare centers worldwide, led to unprecedented changes in childrenâs learning environments. This period of increased time at home with caregivers, with limited access to external sources (e.g., daycares) provides a unique opportunity to examine the associations between the caregiver-child activities and childrenâs language development. The vocabularies of 1742 children aged 8-36 months across 13 countries and 12 languages were evaluated at the beginning and end of the first lockdown period in their respective countries (from March to September 2020). Children who had less passive screen exposure and whose caregivers read more to them showed larger gains in vocabulary development during lockdown, after controlling for SES and other caregiver-child activities. Children also gained more words than expected (based on normative data) during lockdown; either caregivers were more aware of their childâs development or vocabulary development benefited from intense caregiver-child interaction during lockdown