Maine Medical Center

Neonatal encephalopathy (NE)-including hypoxic-ischemic encephalopathy (HIE)-is associated with significant morbidity and mortality worldwide. While data registries provide hypothesis-generating data, aid in quality improvement, and track management/outcomes over time, we recently demonstrated that only 4 of 1,281 (0.3%) variables were collected by all 22 international NE/HIE registries: birth weight, gestational age, and 1- and 5-minute Apgar scores. In response, our team set out to develop a set of common inpatient data elements to enable future harmonization of NE/HIE registry data. Using a modified Delphi method, a panel of 14 international NE experts voted to separate the 1,281 variables from our previous study into "core elements," "supplemental elements," or those that "do not need to be collected." Based on the anonymous survey results, we created draft lists of core and supplemental common data elements (CDEs). These lists were further revised through group consensus meetings and external feedback from global registry leaders and attendants at 2 international conferences. The final data forms include 164 core elements and 225 supplemental elements stratified into 11 domains: demographics; pregnancy, labor, and delivery; delivery room; transport; acid-base; therapeutic hypothermia; neuromonitoring and seizures; neuroimaging; laboratory values (other than acid-base); hospital course; and discharge. The CDEs are the first of several important steps to further standardize research and reporting of NE/HIE investigations to perform more efficient and powerful clinical research in the field moving forward. Future studies need to establish a clinical and research definition of HIE and develop CDEs for collecting long-term, family-centered follow-up data postdischarge.

Introduction: Temperature control (TC) after cardiac arrest remains controversial, with varying temperatures and different effects based on illness severity. Brown adipose tissue (BAT) appears cardioprotective; shivering, heat transmission, and BAT activity remain understudied after cardiac arrest. Methods: This pilot retrospective study evaluated post-cardiac arrest comatose subjects treated with TC at 33-37°C using the Becton Dickinson Arctic Sun (AS). Suppression Ratio 6-hours (SR6) after recovery of spontaneous circulation (ROSC) and Shivering Events (SE) from surface EMG were obtained from the Medtronic BIS Monitor. Shivering intensity was based on EMG SE (minimal, moderate, robust, or HiEMG). Heat Index (HI), Heat Transfer (HT), and Work-to-Cool (W2C) were calculated from AS water temperature and flow data during induction and maintenance phases of TC. Activity of BAT was estimated from peak plasma 12,13-diHOME (1213dH) drawn 6-168 hours post-ROSC. Cerebral Performance Category (CPC) score at 6-months was dichotomized into good (CPC 1-2) and poor (CPC 3-5) categories. Results: 35 subjects were included, with a median age of 63 (55-71) years, 24 (68%) male, 26 (74%) witnessed arrest, 10 (28%) shockable rhythm, and SR6 was 88% (33-98). Target temperature was 33°C in 22 (63%) and 35-37°C in 13 (37%). Good outcome was attained by 7 subjects (20%). Shivering intensity was minimal in 10/32 (31%), moderate in 7 (22%), and robust in 9 (28%). Heat transmittance was greater during induction than maintenance (all p< 0.001). During induction, mean HI was greater for 33°C (15.4 vs 11.5, p=0.002). During maintenance, heat transmittance was greater for 33°C for HI (6.7 vs 3.9, p=0.004), W2C (220 vs 97, p< 0.001), and HT (130 vs 39, p=0.002). The median peak 1213dH was 6.8 (4.2-11.1) ng/ml, was 7.6 (5.2-14.4) ng/ml for minimal shivering vs 4.4 (1.7-8.4, p=0.11) for robust shivering, and was >4.5 ng/ml in 8/10 (80%) minimal shivering vs 4/9 (44%) robust shivering (p=0.17). Conclusions: Heat transmittance was greater during TC induction, and for target temperatures of 33°C vs 35-37°C. While BAT may generate heat and reduce shivering after cardiac arrest, 12,13-diHOME was not lower among robust shivering patients in this small retrospective cohort. Future studies with larger cohorts are needed to test this hypothesis.

Autistic children are at increased risk for psychiatric hospitalization for challenging behaviors. Sleep problems may increase this risk due to the added strain they place on caregivers and their ability to maintain safety at home. We evaluate if caregiver-reported sleep problems in autistic children at the time of the child's hospital admission predict caregiver reported stress and self-efficacy, above and beyond the severity of the child's challenging behaviors. Participants included 598 autistic children (ages 4-20) admitted to specialized psychiatric inpatient units and a primary caregiver. Caregivers reported if their child had sleep initiation and/or sleep maintenance problems. Caregivers completed the Parenting Stress Index-Short Form and Difficult Behavior Self-Efficacy Scale. Hierarchical linear regression models examined associations between sleep problems and caregiver outcomes, controlling for child irritability, and both household- and child-level characteristics. Fifty-nine percent of children had a caregiver-reported sleep problem. Sleep maintenance problems were significantly associated with increased parental distress, more dysfunctional parent-child interactions, and greater perception of the child as difficult to manage, above and beyond challenging behavior severity and other covariates. Sleep initiation problems were unrelated to caregiver outcomes. Self-efficacy in single caregivers and those in lower-income households was more negatively impacted by sleep problems than other caregivers. Sleep maintenance problems may independently contribute to caregiver strain above and beyond challenging behaviors. Social and financial resources may buffer against the negative effect of sleep problems. Preventative interventions targeting sleep may provide needed support for vulnerable families.

We sought to evaluate whether rotating night shift work increases the risk of type 2 diabetes, particularly among women with a history of gestational diabetes mellitus (GDM). We included 50 122 Nurses' Health Study II participants who were parous at baseline in 1989 or at any time during follow-up through 2019. Using multivariable-adjusted Cox proportional hazards models, we estimated the HRs and 95% CIs for the associations between cumulative years of rotating night shift work and incident type 2 diabetes, overall, and by history of GDM. Compared with participants who never engaged in rotating night shift work, we observed a graded increase in the risk of type 2 diabetes with cumulative years of rotating night shift work: HR (95% CI) 1.14 (1.04 to 1.24) for <5 years, 1.32 (1.17 to 1.49) for 5-10 years and 1.32 (1.16 to 1.50) for >10 years (p-linear trend <0.001). Stratifying by history of GDM, we observed a similar pattern of associations among participants without a history of GDM, but not among those with a history of GDM (p-interaction=0.02). History of GDM was strongly associated with risk of incident type 2 diabetes in all women, including those who never worked rotating night shifts: HR (95% CI) 4.76 (3.90 to 5.81). Cumulative years of rotating night shift work were modestly associated with a higher risk of type 2 diabetes, overall, and among nurses without a history of GDM. Rotating night shift work was not associated with risk of type 2 diabetes among individuals with a history of GDM, an exceptionally high-risk subgroup for type 2 diabetes.

In this time of rapidly-changing science, technology, healthcare and society, the education of aspiring professionals and the training of seasoned practitioners must intentionally place human relationships at the centre of service delivery. Reflecting on our own experiences, gained over many years in practice, we argue that despite the proliferation of technology in every aspect of our lives, both patients and practitioners ultimately desire a human-centric approach. To consider the impact of such a paradigm on the future education needs of those working in data-driven and technology-enabled care, a multifactorial approach is required consisting of seven different dimensions: the changing nature of healthcare relationships; addressing disparities; human-centred design and innovation; effective digital technology education; prioritising professionals' wellbeing through systemic change; working with governments, institutions and other stakeholders; and the implications, ethics and stewardship of shared data. The authors examine each of these areas and propose specific steps that evolving healthcare systems can take to prioritise human relationships and optimise technology to support those relationships. We acknowledge that our gaze is somewhat tinted, reflecting our work in healthcare and the global north. Yet our aim is universal: to celebrate human connections and the art of caring in a digital age.