Expert-level sleep staging using an electrocardiography-only feed-forward neural network.

Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep stage classification is polysomnography (PSG). Unfortunately, PSG is an expensive and cumbersome process involving numerous electrodes, often conducted in an unfamiliar clinic and annotated by a professional. Although commercial devices like smartwatches track sleep, their performance is well below PSG. To address these disadvantages, we present a feed-forward neural network that achieves gold-standard levels of agreement using only a single lead of electrocardiography (ECG) data. Specifically, the median five-stage Cohen's kappa is 0.725 on a large, diverse dataset of 5 to 90-year-old subjects. Comparisons with a comprehensive meta-analysis of between-human inter-rater agreement confirm the non-inferior performance of our model. Finally, we developed a novel loss function to align the training objective with Cohen's kappa. Our method offers an inexpensive, automated, and convenient alternative for sleep stage classification-further enhanced by a real-time scoring option. Cardiosomnography, or a sleep study conducted with ECG only, could take expert-level sleep studies outside the confines of clinics and laboratories and into realistic settings. This advancement democratizes access to high-quality sleep studies, considerably enhancing the field of sleep medicine and neuroscience. It makes less-expensive, higher-quality studies accessible to a broader community, enabling improved sleep research and more personalized, accessible sleep-related healthcare interventions.

Changing patterns of the prevalence of burnout and secondary traumatic stress in health-system pharmacists throughout the COVID-19 pandemic.

Introduction: The demands posed during the coronavirus disease 2019 (COVID-19) pandemic have led to greater stress and frustration, which in turn can fuel exhaustion, cynicism, secondary traumatic stress (STS), and burnout. More evidence is needed regarding the prevalence of burnout and STS throughout the pandemic. Objectives: The aim of this study was to describe the changing pattern of the prevalence of burnout and STS in health-system pharmacists throughout the pandemic (early to 20 months into the pandemic). Methods: A cross-sectional, listserv-based online survey was conducted in health-system pharmacists. The survey was administered between April and May 2020 (early group) and again between October and December 2021 (20-month group). The survey questionnaire included demographics, employment characteristics, COVID-19-related questions, survey of respondent's perceptions of prevalence and severity of burnout, and Professional Quality of Life Scale (ProQOL) which assessed compassion satisfaction and fatigue (burnout and STS). Results: A total of 1126 health-system pharmacists completed the survey (484 in the early group and 642 in the 20-month group). Based on respondents' self-rating of burnout, significantly more respondents reported feeling burned out in the 20-month group vs the early group (69% vs 47.7%; P < .001). Based on ProQOL, significantly more respondents were identified with moderate-high likelihood of burnout (83.8% vs 65.3%; P < .001) and moderate-high probability of STS (63.2% vs 51.4%; P < .001) in the 20-month group vs the early group. Approximately 99% of respondents in both groups were identified with moderate-high probability of compassion satisfaction. Conclusion: Twenty months into the COVID-19 pandemic, almost 83% of health-system pharmacist respondents were identified with burnout, 63% with STS, and 99% with compassion satisfaction. These rates are significantly higher compared with rates early in the pandemic. Unfortunately, the development of burnout and STS in these pharmacists may lead to several work-related consequences (eg, increase risk of medical errors); therefore, further studies are critical to develop and assess effective interventions to address the long-term effects of the pandemic and well-being of health-system pharmacists.

A model for self-organization of sensorimotor function: the spinal monosynaptic loop.

Recent spinal cord literature abounds with descriptions of genetic preprogramming and the molecular control of circuit formation. In this paper, we explore to what extent circuit formation based on learning rather than preprogramming could explain the selective formation of the monosynaptic projections between muscle spindle primary afferents and homonymous motoneurons. We adjusted the initially randomized gains in the neural network according to a Hebbian plasticity rule while exercising the model system with spontaneous muscle activity patterns similar to those observed during early fetal development. Normal connectivity patterns developed only when we modeled ß motoneurons, which are known to innervate both intrafusal and extrafusal muscle fibers in vertebrate muscles but were not considered in previous literature regarding selective formation of these synapses in animals with paralyzed muscles. It was also helpful to correctly model the greatly reduced contractility of extrafusal muscle fibers during early development. Stronger and more coordinated muscle activity patterns such as observed later during neonatal locomotion impaired projection selectivity. These findings imply a generic functionality of a musculoskeletal system to imprint important aspects of its mechanical dynamics onto a neural network, without specific preprogramming other than setting a critical period for the formation and maturation of this general pattern of connectivity. Such functionality would facilitate the successful evolution of new species with altered musculoskeletal anatomy, and it may help to explain patterns of connectivity and associated reflexes that appear during abnormal development.NEW & NOTEWORTHY A novel model of self-organization of early spinal circuitry based on a biologically realistic plant, sensors, and neuronal plasticity in conjunction with empirical observations of fetal development. Without explicit need for guiding genetic rules, connection matrices emerge that support functional self-organization of the mature pattern of Ia to motoneuron connectivity in the spinal circuitry.

Survey of Health-System Pharmacy Leadership Pathways: A 10-Year Revisit.

OBJECTIVE: To compare health-system pharmacy leadership pathways and opinions in the last decade. METHODS: A 33 question survey was recreated from the 2009 survey of health-system pharmacy leadership pathways and reviewed and modified by the original creators. In November 2019, investigators sent two invites to complete a QualtricsXM survey to individuals listed on the ASHP Connect Pharmacy Practice Leaders listserver. The survey closed on December 15, 2019. RESULTS: Two-hundred-thirteen pharmacy leaders responded to the survey. Survey respondents identified completing a pharmacy practice (PGY1) residency as the most common health-system pharmacy leadership pathway. Respondents stated on-the-job experience contributed most to their leadership development. Interpersonal skills (20%), human resource management (19%), and finance and budget management (13%) were classified as the most valuable skill-sets to a health-systems leader. Thirty-nine percent of eligible respondents stated they were interested in seeking a health-system pharmacy director position and 23% stated they may be interested. The majority of directors stated that they preferred to hire those with previous on-the job experience into leadership positions. CONCLUSION: Regardless of leadership pathway, those interested in pursuing health-system pharmacy leadership positions should pursue as much on-the-job experience as possible, build relationships through networking, and find a strong, helpful mentor.

Burnout and secondary traumatic stress in health-system pharmacists during the COVID-19 pandemic.

PURPOSE: To describe the prevalence of burnout and secondary traumatic stress (STS) in health-system pharmacists during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: A cross-sectional, professional pharmacy organization listserver-based online survey of a target group of health-system pharmacists across the United States was conducted. The survey was sent out through professional organization listservers and was anonymous and voluntary. The survey questionnaire included items regarding demographics and employment characteristics, COVID-19-related questions, a survey of respondents' perceptions of the prevalence and severity of burnout, and the Professional Quality of Life Scale (ProQOL). The ProQOL assessed respondents for compassion satisfaction (subcategorized as burnout and STS) and compassion fatigue. Descriptive statistics was used to assess the prevalence of burnout and STS. RESULTS: Four hundred eighty-four health-system pharmacists completed the survey. Based on respondents' self-ratings of burnout, 47% were identified as having current burnout and 81% as having a history of burnout. Based on ProQOL scoring, 65.3% of respondents were identified as having a moderate or high likelihood of burnout, which was a prevalence higher than that indicated by respondents' self-ratings. Additionally, 51.4% of respondents were identified as having a moderate or high probability of STS and 99.4% as having a moderate or high probability of compassion satisfaction. CONCLUSION: The survey found that over half of health-system pharmacists were affected with burnout, half with STS, and all with compassion satisfaction during the COVID-19 pandemic. Unfortunately, the development of burnout and STS in these health-system pharmacists may lead to several work-related consequences (eg, increase risk of medical errors, depression); therefore, addressing burnout and STS is crucial. Further studies of the consequences of burnout and STS during the COVID-19 pandemic are needed.

Racetrack resonator as a loss measurement platform for photonic components.

This work represents the first complete analysis of the use of a racetrack resonator to measure the insertion loss of efficient, compact photonic components. Beginning with an in-depth analysis of potential error sources and a discussion of the calibration procedure, the technique is used to estimate the insertion loss of waveguide width tapers of varying geometry with a resulting 95% confidence interval of 0.007 dB. The work concludes with a performance comparison of the analyzed tapers with results presented for four taper profiles and three taper lengths.

Ultra-low crosstalk, CMOS compatible waveguide crossings for densely integrated photonic interconnection networks.

We explore the design space for optimizing CMOS compatible waveguide crossings on a silicon photonics platform. This paper presents simulated and experimental excess loss and crosstalk suppression data for vertically integrated silicon nitride over silicon-on-insulator waveguide crossings. Experimental results show crosstalk suppression exceeding -49/-44 dB with simulation results as low as -65/-60 dB for the TE/TM mode in a waveguide crossing with a 410 nm vertical gap.