Antiviral therapy substantially reduces HCC risk in patients with chronic hepatitis B infection in the indeterminate phase.

BACKGROUND AND AIMS: HCC risk in chronic hepatitis B (CHB) is higher in the indeterminate phase compared with the inactive phase. However, it is unclear if antiviral therapy reduces HCC risk in this population. We aimed to evaluate the association between antiviral therapy and HCC risk in the indeterminate phase. APPROACH AND RESULTS: We analyzed 855 adult (59% male), treatment-naïve patients with CHB infection without advanced fibrosis in the indeterminate phase at 14 centers (USA, Europe, and Asia). Inverse probability of treatment weighting (IPTW) was used to balance the treated (n = 405) and untreated (n = 450) groups. The primary outcome was HCC development. The mean age was 46±13 years, the median alanine transaminase was 38 (interquartile range, 24-52) U/L, the mean HBV DNA was 4.5±2.1 log 10 IU/mL, and 20% were HBeAg positive. The 2 groups were similar after IPTW. After IPTW (n = 819), the 5-, 10-, and 15-year cumulative HCC incidence was 3%, 4%, and 9% among treated patients (n = 394) versus 3%, 15%, and 19%, among untreated patients (n = 425), respectively ( p = 0.02), with consistent findings in subgroup analyses for age >35 years, males, HBeAg positive, HBV DNA>1000 IU/mL, and alanine transaminase

Co-design of a personalised digital intervention to improve vegetable intake in adults living in Australian rural communities.

BACKGROUND: Diets low in vegetables are a main contributor to the health burden experienced by Australians living in rural communities. Given the ubiquity of smartphones and access to the Internet, digital interventions may offer an accessible delivery model for a dietary intervention in rural communities. However, no digital interventions to address low vegetable intake have been co-designed with adults living in rural areas. This paper describes the co-design of a digital intervention to improve vegetable intake with rural community members and research partners. METHODS: Active participants in the co-design process were adults ≥ 18 years living in three rural Australian communities (total n = 57) and research partners (n = 4) representing three local rural governments and one peak non-government health organisation. An iterative co-design process was undertaken to understand the needs (pre-design phase) and ideas (generative phase) of the target population. Eight online workshops and a community survey were conducted between July and December 2021. The MoSCoW prioritisation method was used to help participants identify the 'Must-have, Should-have, Could-have, and Won't-have or will not have right now' features and functions of the digital intervention. Workshops were transcribed and inductively analysed using NVivo. Convergent and divergent themes were identified between the workshops and community survey to identify how to implement the digital intervention in the community. RESULTS: Consensus was reached on a concept for a digital intervention that addressed individual and food environment barriers to vegetable intake, specific to rural communities. Implementation recommendations centred on (i) food literacy approaches to improve skills via access to vegetable-rich recipes and healthy eating resources, (ii) access to personalisation options and behaviour change support, and (iii) improving the community food environment by providing information on and access to local food initiatives. CONCLUSIONS: Rural-dwelling adults expressed preferences for personalised intervention features that can enhance food literacy and engagement with community food environments. This research will inform the development of the prototyping (evaluation phase) and feasibility testing (post-design phase) of this intervention.

Novel identification and modulation of the mechanosensitive Piezo1 channel in human myometrium.

Approximately 10% of US births deliver preterm before 37 weeks of completed gestation. Premature infants are at risk for life-long debilitating morbidities and death, and spontaneous preterm labour explains 50% of preterm births. In all cases existing treatments are ineffective, and none are FDA approved. The mechanisms that initiate preterm labour are not well understood but may result from dysfunctional regulation of quiescence mechanisms. Human pregnancy is accompanied by large increases in blood flow, and the uterus must enlarge by orders of magnitude to accommodate the growing fetus. This mechanical strain suggests that stretch-activated channels may constitute a mechanism to explain gestational quiescence. Here we identify for the first time that Piezo1, a mechanosensitive cation channel, is present in the uterine smooth muscle and microvascular endothelium of pregnant myometrium. Piezo is downregulated during preterm labour, and stimulation of myometrial Piezo1 in an organ bath with the agonist Yoda1 relaxes the tissue in a dose-dependent fashion. Further, stimulation of Piezo1 while inhibiting protein kinase A, AKT, or endothelial nitric oxide synthase mutes the negative inotropic effects of Piezo1 activation, intimating that actions on the myocyte and endothelial nitric oxide signalling contribute to Piezo1-mediated contractile dynamics. Taken together, these data highlight the importance of stretch-activated channels in pregnancy maintenance and parturition, and identify Piezo1 as a tocolytic target of interest. KEY POINTS: Spontaneous preterm labour is a serious obstetric dilemma without a known cause or effective treatments. Piezo1 is a stretch-activated channel important to muscle contractile dynamics. Piezo1 is present in the myometrium and is dysregulated in women who experience preterm labour. Activation of Piezo1 by the agonist Yoda1 relaxes the myometrium in a dose-dependent fashion, indicating that Piezo1 modulation may have therapeutic benefits to treat preterm labour.

Global incidence of non-alcoholic fatty liver disease: A systematic review and meta-analysis of 63 studies and 1,201,807 persons.

BACKGROUND & AIMS: The prevalence of non-alcoholic fatty liver disease (NAFLD) is increasing. We aimed to estimate the pooled global NAFLD incidence. METHODS: We performed a systematic review and meta-analysis of cohort studies of adults without NAFLD at baseline to evaluate the global incidence of ultrasound-diagnosed NAFLD. RESULTS: A total of 63 eligible studies (1,201,807 persons) were analyzed. Studies were from Mainland China/Hong Kong (n = 26), South Korea (n = 22), Japan (n = 14), other (n = 2, Sri Lanka, Israel); 63.8% were clinical center studies; median study year 2000 to 2016; 87% were good quality. Among the 1,201,807 persons at risk, 242,568 persons developed NAFLD, with an incidence rate of 4,612.8 (95% CI 3,931.5-5,294.2) per 100,000 person-years and no statistically significant differences by study sample size (p = 0.90) or study setting (p = 0.055). Males had higher incidence vs. females (5,943.8 vs. 3,671.7, p = 0.0013). Both the obese (vs. non-obese) and the overweight/obese groups (vs. normal weight) were about threefold more likely to develop NAFLD (8,669.6 vs. 2,963.9 and 8,416.6 vs. 3,358.2, respectively) (both p <0.0001). Smokers had higher incidence than non-smokers (8,043.2 vs. 4,689.7, p = 0.046). By meta-regression, adjusting for study year, study setting, and study location, study period of 2010 or after and study setting were associated with increased incidence (p = 0.010 and p = 0.055, respectively). By country, China had a higher NAFLD incidence compared to non-China regions (p = 0.012) and Japan a lower incidence compared to non-Japan regions (p = 0.005). CONCLUSIONS: NAFLD incidence is increasing with a current estimate of 4,613 new cases per 100,000 person-years. Males and overweight/obese individuals had significantly higher incidence rates compared to females and those of normal weight. Public health interventions for prevention of NAFLD are needed with a special emphasis on males, overweight/obese individuals, and higher risk regions. IMPACT AND IMPLICATIONS: Non-alcoholic fatty liver disease (NAFLD) affects approximately 30% of people worldwide and appears to be increasing, but data to estimate the incidence rate are limited. In this meta-analytic study of over 1.2 million people, we estimated an incidence rate of NAFLD of 46.13 per 1,000 person-years with significant differences by sex, BMI, geography, and time-period. As treatment options for NAFLD remain limited, prevention of NAFLD should remain the focus of public health strategies. Studies such as these can help policy makers in determining which and whether their interventions are impactful.

Optimizing hepatitis B virus screening in the United States using a simple demographics-based model.

BACKGROUND AND AIMS: Chronic hepatitis B (CHB) affects >290 million persons globally, and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression (LR) and machine learning (ML; random forest) models to accurately identify patients with HBV, using only easily obtained demographic data from a population-based data set. APPROACH AND RESULTS: We identified participants with data on HBsAg, birth year, sex, race/ethnicity, and birthplace from 10 cycles of the National Health and Nutrition Examination Survey (1999-2018) and divided them into two cohorts: training (cycles 2, 3, 5, 6, 8, and 10; n = 39,119) and validation (cycles 1, 4, 7, and 9; n = 21,569). We then developed and tested our two models. The overall cohort was 49.2% male, 39.7% White, 23.2% Black, 29.6% Hispanic, and 7.5% Asian/other, with a median birth year of 1973. In multivariable logistic regression, the following factors were associated with HBV infection: birth year 1991 or after (adjusted OR [aOR], 0.28; p < 0.001); male sex (aOR, 1.49; p = 0.0080); Black and Asian/other versus White (aOR, 5.23 and 9.13; p < 0.001 for both); and being USA-born (vs. foreign-born; aOR, 0.14; p < 0.001). We found that the ML model consistently outperformed the LR model, with higher area under the receiver operating characteristic values (0.83 vs. 0.75 in validation cohort; p < 0.001) and better differentiation of high- and low-risk persons. CONCLUSIONS: Our ML model provides a simple, targeted approach to HBV screening, using only easily obtained demographic data.

Impaired in vivo feto-placental development is associated with neonatal neurobehavioral outcomes.

BACKGROUND: Fetal growth restriction (FGR) is a risk factor for neurodevelopmental problems, yet remains poorly understood. We sought to examine the relationship between intrauterine development and neonatal neurobehavior in pregnancies diagnosed with antenatal FGR. METHODS: We recruited women with singleton pregnancies diagnosed with FGR and measured placental and fetal brain volumes using MRI. NICU Network Neurobehavioral Scale (NNNS) assessments were performed at term equivalent age. Associations between intrauterine volumes and neurobehavioral outcomes were assessed using generalized estimating equation models. RESULTS: We enrolled 44 women diagnosed with FGR who underwent fetal MRI and 28 infants underwent NNNS assessments. Placental volumes were associated with increased self-regulation and decreased excitability; total brain, brainstem, cortical and subcortical gray matter (SCGM) volumes were positively associated with higher self-regulation; SCGM also was positively associated with higher quality of movement; increasing cerebellar volumes were positively associated with attention, decreased lethargy, non-optimal reflexes and need for special handling; brainstem volumes also were associated with decreased lethargy and non-optimal reflexes; cerebral and cortical white matter volumes were positively associated with hypotonicity. CONCLUSION: Disrupted intrauterine growth in pregnancies complicated by antenatally diagnosed FGR is associated with altered neonatal neurobehavior. Further work to determine long-term neurodevelopmental impacts is warranted. IMPACT: Fetal growth restriction is a risk factor for adverse neurodevelopment, but remains difficult to accurately identify. Intrauterine brain volumes are associated with infant neurobehavior. The antenatal diagnosis of fetal growth restriction is a risk factor for abnormal infant neurobehavior.

Digital behaviour change interventions to increase vegetable intake in adults: a systematic review.

BACKGROUND: Digital interventions may help address low vegetable intake in adults, however there is limited understanding of the features that make them effective. We systematically reviewed digital interventions to increase vegetable intake to 1) describe the effectiveness of the interventions; 2) examine links between effectiveness and use of co-design, personalisation, behavioural theories, and/or a policy framework; and 3) identify other features that contribute to effectiveness. METHODS: A systematic search strategy was used to identify eligible studies from MEDLINE, Embase, PsycINFO, Scopus, CINAHL, Cochrane Library, INFORMIT, IEEE Xplore and Clinical Trial Registries, published between January 2000 and August 2022. Digital interventions to increase vegetable intake were included, with effective interventions identified based on statistically significant improvement in vegetable intake. To identify policy-action gaps, studies were mapped across the three domains of the NOURISHING framework (i.e., behaviour change communication, food environment, and food system). Risk of bias was assessed using Cochrane tools for randomized, cluster randomized and non-randomized trials. RESULTS: Of the 1,347 records identified, 30 studies were included. Risk of bias was high or serious in most studies (n = 25/30; 83%). Approximately one quarter of the included interventions (n = 8) were effective at improving vegetable intake. While the features of effective and ineffective interventions were similar, embedding of behaviour change theories (89% vs 61%) and inclusion of stakeholders in the design of the intervention (50% vs 38%) were more common among effective interventions. Only one (ineffective) intervention used true co-design. Although fewer effective interventions included personalisation (67% vs 81%), the degree of personalisation varied considerably between studies. All interventions mapped across the NOURISHING framework behaviour change communication domain, with one ineffective intervention also mapping across the food environment domain. CONCLUSION: Few digital interventions identified in this review were effective for increasing vegetable intake. Embedding behaviour change theories and involving stakeholders in intervention design may increase the likelihood of success. The under-utilisation of comprehensive co-design methods presents an opportunity to ensure that personalisation approaches better meet the needs of target populations. Moreover, future digital interventions should address both behaviour change and food environment influences on vegetable intake.

EEG based automated seizure detection - A survey of medical professionals.

Diagnosing and managing seizures presents substantial challenges for clinicians caring for patients with epilepsy. Although machine learning (ML) has been proposed for automated seizure detection using EEG data, there is little evidence of these technologies being broadly adopted in clinical practice. Moreover, there is a noticeable lack of surveys investigating this topic from the perspective of medical practitioners, which limits the understanding of the obstacles for the development of effective automated seizure detection. Besides the issue of generalisability and replicability seen in a small amount of studies, obstacles to the adoption of automated seizure detection remain largely unknown. To understand the obstacles preventing the application of seizure detection tools in clinical practice, we conducted a survey targeting medical professionals involved in the management of epilepsy. Our study aimed to gather insights on various factors such as the clinical utility, professional sentiment, benchmark requirements, and perceived barriers associated with the use of automated seizure detection tools. Our key findings are: I) The minimum acceptable sensitivity reported by most of our respondents (80%) seems achievable based on studies reported from most currently available ML-based EEG seizure detection algorithms, but replication studies often fail to meet this minimum. II) Respondents are receptive to the adoption of ML seizure detection tools and willing to spend time in training. III) The top three barriers for usage of such tools in clinical practice are related to availability, lack of training, and the blackbox nature of ML algorithms. Based on our findings, we developed a guide that can serve as a basis for developing ML-based seizure detection tools that meet the requirements of medical professionals, and foster the integration of these tools into clinical practice.

Estimating Patient-Level Uncertainty in Seizure Detection Using Group-Specific Out-of-Distribution Detection Technique.

Epilepsy is a chronic neurological disorder affecting around 1% of the global population, characterized by recurrent epileptic seizures. Accurate diagnosis and treatment are crucial for reducing mortality rates. Recent advancements in machine learning (ML) algorithms have shown potential in aiding clinicians with seizure detection in electroencephalography (EEG) data. However, these algorithms face significant challenges due to the patient-specific variability in seizure patterns and the limited availability of high-quality EEG data for training, causing erratic predictions. These erratic predictions are harmful, especially for high-stake domains in healthcare, negatively affecting patients. Therefore, ensuring safety in AI is of the utmost importance. In this study, we propose a novel ensemble method for uncertainty quantification to identify patients with low-confidence predictions in ML-based seizure detection algorithms. Our approach aims to mitigate high-risk predictions in previously unseen seizure patients, thereby enhancing the robustness of existing seizure detection algorithms. Additionally, our method can be implemented with most of the deep learning (DL) models. We evaluated the proposed method against established uncertainty detection techniques, demonstrating its effectiveness in identifying patients for whom the model's predictions are less certain. Our proposed method managed to achieve 87%, 89% and 75% in accuracy, specificity and sensitivity, respectively. This study represents a novel attempt to improve the reliability and robustness of DL algorithms in the domain of seizure detection. This study underscores the value of integrating uncertainty quantification into ML algorithms for seizure detection, offering clinicians a practical tool to gauge the applicability of ML models for individual patients.

2019 Global NAFLD Prevalence: A Systematic Review and Meta-analysis.

BACKGROUND & AIMS: The increasing rates of obesity and type 2 diabetes mellitus may lead to increased prevalence of nonalcoholic fatty liver disease (NAFLD). We aimed to determine the current and recent trends on the global and regional prevalence of NAFLD. METHODS: Systematic search from inception to March 26, 2020 was performed without language restrictions. Two authors independently performed screening and data extraction. We performed meta-regression to determine trends in NAFLD prevalence. RESULTS: We identified 17,244 articles from literature search and included 245 eligible studies involving 5,399,254 individuals. The pooled global prevalence of NAFLD was 29.8% (95% confidence interval [CI], 28.6%-31.1%); of these, 82.5% of included articles used ultrasound to diagnose NAFLD, with prevalence of 30.6% (95% CI, 29.2%-32.0%). South America (3 studies, 5716 individuals) and North America (4 studies, 18,236 individuals) had the highest NAFLD prevalence at 35.7% (95% CI, 34.0%-37.5%) and 35.3% (95% CI, 25.4%-45.9%), respectively. From 1991 to 2019, trend analysis showed NAFLD increased from 21.9% to 37.3% (yearly increase of 0.7%, P < .0001), with South America showing the most rapid change of 2.7% per year, followed by Europe at 1.1%. CONCLUSIONS: Despite regional variation, the global prevalence of NAFLD is increasing overall. Policy makers must work toward reversing the current trends by increasing awareness of NAFLD and promoting healthy lifestyle environments.

Automatic brain segmentation in preterm infants with post-hemorrhagic hydrocephalus using 3D Bayesian U-Net.

Post-hemorrhagic hydrocephalus (PHH) is a severe complication of intraventricular hemorrhage (IVH) in very preterm infants. PHH monitoring and treatment decisions rely heavily on manual and subjective two-dimensional measurements of the ventricles. Automatic and reliable three-dimensional (3D) measurements of the ventricles may provide a more accurate assessment of PHH, and lead to improved monitoring and treatment decisions. To accurately and efficiently obtain these 3D measurements, automatic segmentation of the ventricles can be explored. However, this segmentation is challenging due to the large ventricular anatomical shape variability in preterm infants diagnosed with PHH. This study aims to (a) propose a Bayesian U-Net method using 3D spatial concrete dropout for automatic brain segmentation (with uncertainty assessment) of preterm infants with PHH; and (b) compare the Bayesian method to three reference methods: DenseNet, U-Net, and ensemble learning using DenseNets and U-Nets. A total of 41 T2 -weighted MRIs from 27 preterm infants were manually segmented into lateral ventricles, external CSF, white and cortical gray matter, brainstem, and cerebellum. These segmentations were used as ground truth for model evaluation. All methods were trained and evaluated using 4-fold cross-validation and segmentation endpoints, with additional uncertainty endpoints for the Bayesian method. In the lateral ventricles, segmentation endpoint values for the DenseNet, U-Net, ensemble learning, and Bayesian U-Net methods were mean Dice score = 0.814 ± 0.213, 0.944 ± 0.041, 0.942 ± 0.042, and 0.948 ± 0.034 respectively. Uncertainty endpoint values for the Bayesian U-Net were mean recall = 0.953 ± 0.037, mean  negative predictive value = 0.998 ± 0.005, mean accuracy = 0.906 ± 0.032, and mean AUC = 0.949 ± 0.031. To conclude, the Bayesian U-Net showed the best segmentation results across all methods and provided accurate uncertainty maps. This method may be used in clinical practice for automatic brain segmentation of preterm infants with PHH, and lead to better PHH monitoring and more informed treatment decisions.

In infants with congenital heart disease autonomic dysfunction is associated with pre-operative brain injury.

BACKGROUND: Brain injury is a serious and common complication of critical congenital heart disease (CHD). Impaired autonomic development (assessed by heart rate variability (HRV)) is associated with brain injury in other high-risk neonatal populations. OBJECTIVE: To determine whether impaired early neonatal HRV is associated with pre-operative brain injury in CHD. METHODS: In infants with critical CHD, we evaluated HRV during the first 24 h of cardiac ICU (CICU) admission using time-domain (RMS 1, RMS 2, and alpha 1) and frequency-domain metrics (LF, nLF, HF, nHF). Pre-operative brain magnetic resonance imaging (MRI) was scored for injury using an established system. Spearman's correlation coefficient was used to determine the association between HRV and pre-operative brain injury. RESULTS: We enrolled 34 infants with median birth gestational age of 38.8 weeks (IQR 38.1-39.1). Median postnatal age at pre-operative brain MRI was 2 days (IQR 1-3 days). Thirteen infants had MRI evidence of brain injury. RMS 1 and RMS 2 were inversely correlated with pre-operative brain injury. CONCLUSIONS: Time-domain metrics of autonomic function measured within the first 24 h of admission to the CICU are associated with pre-operative brain injury, and may perform better than frequency-domain metrics under non-stationary conditions such as critical illness. IMPACT: Autonomic dysfunction, measured by heart rate variability (HRV), in early transition is associated with pre-operative brain injury in neonates with critical congenital heart disease. These data extend our earlier findings by providing further evidence for (i) autonomic dysfunction in infants with CHD, and (ii) an association between autonomic dysfunction and brain injury in critically ill neonates. These data support the notion that further investigation of HRV as a biomarker for brain injury risk is warranted in infants with critical CHD.

Autonomic development in preterm infants is associated with morbidity of prematurity.

BACKGROUND: Previous studies have described an association between preterm birth and maturation of the autonomic nervous system (ANS); however, this may be impacted by multiple factors, including prematurity-related complications. Our aim was to evaluate for the effect of prematurity-related morbidity on ANS development in preterm infants in the NICU. METHODS: We compared time and frequency domains of heart rate variability (HRV) as a measure of ANS tone in 56 preterm infants from 2 NICUs (28 from each). One cohort was from a high-morbidity regional referral NICU, the other from a community-based inborn NICU with low prematurity-related morbidity. Propensity score matching was used to balance the groups by a 1:1 nearest neighbor design. ANS tone was analyzed. RESULTS: The two cohorts showed parallel maturational trajectory of the alpha 1 time-domain metric, with the cohort from the high-morbidity NICU having lower autonomic tone. The maturational trajectories between the two cohorts differed in all other time-domain metrics (alpha 2, RMS1, RMS2). There was no difference between groups by frequency-domain metrics. CONCLUSIONS: Prematurity-associated morbidities correlate with autonomic development in premature infants and may have a greater impact on the extrauterine maturation of this system than birth gestational age. IMPACT: Autonomic nervous system development measured by time-domain metrics of heart rate variability correlate with morbidities associated with premature birth. This study builds upon our previously published work that showed that development of autonomic tone was not impacted by gestational age at birth. This study adds to our understanding of autonomic nervous system development in a preterm extrauterine environment. Our study suggests that gestational age at birth may have less impact on autonomic nervous system development than previously thought.

Clinical Profiles of Asians with NAFLD: A Systematic Review and Meta-Analysis.

INTRODUCTION: NAFLD is increasingly prevalent in Asia, where people suffer more metabolic comorbidities at a lower body mass index (BMI), suggesting potential differences in their clinical profile. Therefore, we attempted to characterize the clinical profile of Asians with NAFLD via a meta-analytic approach. METHODS: We searched PubMed, EMBASE, and Cochrane databases from January 1, 2000, to January 17, 2019. Two authors independently reviewed and selected 104 articles (2,247,754 persons) that identified NAFLD in Asians and reported relevant data, especially BMI and ALT, and excluded individuals with other liver disease and excessive alcohol consumption. Individual patient-level data were obtained from seven cohorts in Asia to complement meta-analyzed data. RESULTS: Overall, the mean age was 52.07 (95% CI: 51.28-52.85) years, with those from Southeast Asia (42.66, 95% CI: 32.23-53.11) being significantly younger. The mean BMI was 26.2 kg/m2, higher in moderate-severe versus mild hepatic steatosis (28.3 vs. 25.7) patients and NFS ≥ -1.455 versus <-1.455 (27.09 vs. 26.02), with 34% having nonobese NAFLD. The mean ALT was 31.74 U/L, higher in NFS < -1.455 versus ≥-1.455 (33.74 vs. 27.83), though no differences were found by obesity or steatosis severity. The majority of males (85.7%) and females (60.7%) had normal to minimally elevated ALT (1-1.5 × 95% ULN). Individual patient-level data analysis (N = 7,668) demonstrated similar results. CONCLUSION: About one-third of Asians with NAFLD were nonobese, and the majority did not have markedly elevated ALT. Therefore, abnormal ALT or BMI is not recommended as a criterion for NAFLD screening in this population. Additionally, there were significant differences in the clinical profiles of NAFLD among the different regions of Asia.

Psychological impact of COVID-19 on nursing personnel: A regional online survey.

AIMS: This study investigated mental health reactions to dealing with COVID-19 in a population of nurses working in a variety of settings. The study attempted to expand our current understanding of the psychological reactions unique to nurses working during the highly stressful period of the COVID-19 pandemic. DESIGN: The study used an online questionnaire design. METHODS: Nurses were recruited using social media via an electronic link between July and September 2020. Of them, 112 nursing professionals completed the 66-item questionnaire. RESULTS: Significant findings included the presence of moderate or greater levels of anxiety (62%), depression (31%), and posttraumatic stress disorder (15%) and with significantly greater intrusive thoughts and memories for nurses who provided direct patient care than those who did not. Nurses with a prior history of anxiety or depression were found to be at greater risk for psychological distress. Results further highlighted concerns and fears related to coronavirus in both their daily personal and professional lives. CONCLUSION: The use of standard, commonly used, measures of psychological disorders allow for a more precise comparison among studies both for this population at the time of the survey and over a period of time. IMPACT: Suggestions for helping nursing professionals identify nurses at risk and improved ways to cope and deal with adverse psychological effects are discussed.

"The Mental Health Piece is Huge": perspectives on developing a prenatal maternal psychological intervention for congenital heart disease.

OBJECTIVES: Women carrying a fetus diagnosed with congenital heart disease often experience significant distress because of their medical diagnosis. Given the well-documented impact associated with elevated prenatal stress and critical importance of developing targeted interventions, this study aims to examine stressors, coping and resilience resources, and mental health treatment preferences in pregnant women receiving a congenital heart disease diagnosis to inform the development of a psychological intervention to reduce maternal distress prenatally. METHODS: Three groups of participants were included consisting of two pregnant women carrying a fetus with congenital heart disease, five women of children (4-16 months) with congenital heart disease, and five paediatric cardiology medical providers. Responses were gathered via semi-structured interviews and analysed using qualitative thematic analysis. RESULTS: Information regarding four broad areas were analysed of emotional distress during pregnancy; experience of initial diagnosis; coping and resilience; and perspectives on a mental health intervention in pregnancy. Anxiety regarding baby's future, guilt following diagnosis, and various coping strategies emerged as primary themes among the participant sample. Medical staff corroborated mothers' heightened anxiety and viewed a psychotherapeutic intervention during the prenatal period as essential and complimentary to standard of care. CONCLUSION: We identified salient themes and preferred components for a future psychological intervention delivered prenatally. PRACTICE IMPLICATIONS: Patients' and providers' perspectives regarding the nature of maternal distress, resilience and treatment preferences can inform the development of interventions to support the emotional well-being of pregnant women carrying a fetus with congenital heart disease to optimise care and potentially improve outcomes for fetal brain development.

Disparities in Pediatric Scoliosis: The Impact of Race and Insurance Type on Access to Nonoperative Treatment for Adolescent Idiopathic Scoliosis.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) has evidence-based, nonoperative treatments proven to be effective with early diagnosis and prompt treatment. The purpose of this study was to identify potential disparities in access to nonoperative treatment for AIS. Specifically, we sought to determine the interaction of socioeconomic factors on a major curve magnitude and recommend treatment at the initial presentation. METHODS: A retrospective review of AIS patients who underwent surgery at a single tertiary pediatric hospital between January 1, 2013 and December 31, 2018 was conducted. Patients were divided into 2 groups for comparison: patients with public insurance (PUB) and those with private insurance (PRV). Primary variables analyzed were patient race, Area Deprivation Index (ADI), major curve magnitude, and treatment recommendation at the initial presentation. Univariate and multivariate analyses were conducted to identify the predictors of the major curve magnitude at presentation. RESULTS: A total of 341 patients met the inclusion criteria; PUB and PRV groups consisted of 182 (53.4%) and 159 (46.6%) children, respectively. Overall, the major curve magnitude at presentation was significantly higher in PUB compared with PRV patients (50.0° vs. 45.1°; P =0.004) and higher in Black patients compared to White patients (51.8 vs. 47.0, P =0.042). Surgery was recommended for 49.7% of the PUB group and 43.7% of the PRV group. A lesser number of PUB patients had curve magnitudes within the range of brace indications (≤40°) compared to PRV patients (22.5% vs. 35.2%, respectively; P =0.010). The odds of having an initial major curve magnitude <40 degrees were 67% lower among Black patients with public insurance compared to Black patients with private insurance (OR=0.33; 95% CI: 0.13-0.83; P =0.019). CONCLUSION: This study demonstrated disparity in access to nonoperative treatment for pediatric scoliosis. Black patients with public insurance were the most at-risk to present with curve magnitudes exceeding brace indications. Future work focused on understanding the reasons for this significant disparity may help to promote more equitable access to effective nonoperative treatment for adolescent idiopathic scoliosis. LEVEL OF EVIDENCE: III.

The Feasibility of Utilizing Malunion Criteria to Limit Radiographs After Spica Casting for Pediatric Femur Fractures.

BACKGROUND: There are no existing guidelines regarding the timing or frequency of postoperative radiographs following spica casting for pediatric femur fractures. The purpose of this study was to evaluate established femoral malunion criteria as a potential screening tool to limit postoperative radiographs by identifying patients at risk for unacceptable alignment in the early treatment period. METHODS: A retrospective chart review was conducted for pediatric femoral shaft fractures presenting to a tertiary pediatric referral hospital from 2012 to 2017. Pediatric femur malunion criteria were applied to radiographs at initial presentation, first follow-up visit, and final follow-up visit. The primary outcome was a change in management based on radiographic findings in the early postoperative period. Secondary outcomes included radiographic measures, number of follow-up visits, and complications. RESULTS: Of 449 consecutive pediatric femur fractures treated at our center, 149 patients aged 1 to 4 years (mean age: 2.5±1.6 y) met inclusion criteria. At initial presentation, 36.9% (55/149) of patients met malunion criteria. Only 4.0% (6/149) of patients had a change in management following initial closed reduction and spica cast application due to radiographic findings at subsequent follow-up. Of these patients, 67% (4/6) were identified on preoperative imaging, and 83.3% (5/6) were identified by their first clinic appointment. Four of the 149 patients were converted to definitive surgical fixation, and 2 patients required cast wedging due to either unacceptable fracture shortening or coronal/sagittal angulation. CONCLUSIONS: Routine early postoperative radiographs may not be necessary for all pediatric femur fractures managed with closed reduction and spica casting. The value of this study is that it is the first to demonstrate the feasibility of limiting postoperative radiographs using a preoperative screening tool. However, the established femoral malunion criteria utilized in this study were limited in their predictive value, and further work is necessary to improve the sensitivity and specificity before widespread clinical application. LEVEL OF EVIDENCE: Level IV.

Effect of Nanoscale Ce0.8Gd0.2O2-δ Infiltrant and Steam Content on Ni-(Y2O3)0.08(ZrO2)0.92 Fuel Electrode Degradation during High-Temperature Electrolysis.

Studies of Ni-yttria-stabilized zirconia (YSZ) fuel electrode degradation mechanisms in solid oxide electrolysis cells (SOECs) are complicated by the different possible Ni-YSZ microstructures and compositions, and the variations in the H2/H2O ratio encountered in an electrolysis stack. Here we describe a life testing scheme aimed at providing survey results on degradation as a function of the H2O-H2 composition, with life tests carried out at five different steam contents from 90% to 10%. A Ni-YSZ-supported symmetric cell geometry is employed both with and without infiltrated nanoscale gadolinia-doped ceria (GDC). Impedance spectroscopy is utilized to observe changes in electrochemical characteristics during the life test, and a transmission-line-based equivalent circuit is used to model the data. Post-test electrode microstructures were observed. The results suggest that the GDC infiltrant reduces the electrode polarization resistance and provides more stable electrode polarization over a range of conditions.

Association Between Fatty Liver and Cirrhosis, Hepatocellular Carcinoma, and Hepatitis B Surface Antigen Seroclearance in Chronic Hepatitis B.

BACKGROUND: Chronic hepatitis B (CHB) and fatty liver (FL) are common, natural history data on concurrent FL and CHB (FL-CHB) are limited. This study aimed to evaluate the effect of FL on cirrhosis, hepatocellular carcinoma (HCC), and hepatitis B surface antigen (HBsAg) seroclearance incidence in CHB patients. METHODS: In a retrospective cohort study of 6786 adult CHB patients, we used propensity score matching (PSM) to balance the FL-CHB and non-FL CHB groups. Kaplan-Meier methods were used to compare cumulative cirrhosis, HCC, and HBsAg seroclearance rates between subgroups. RESULTS: Before PSM, compared to non-FL CHB, FL-CHB patients had lower 10-year cumulative rates of cirrhosis, HCC, and a higher HBsAg seroclearance rate. Similar results were found in the matched FL-CHB and non-FL CHB patients, as well as in the antiviral-treated PSM cohort. Cox proportional hazards model indicated FL to remain significantly and strongly associated with lower risk of cirrhosis and HCC (hazard ratio [HR], 0.19 [95% confidence interval {CI}, .12-.33], P < .001 and HR, 0.21 [95% CI, .09-.51], P = .001, respectively) in antiviral-treated patients but not in untreated patients. CONCLUSIONS: FL was significantly associated with lower cirrhosis and HCC risk and higher HBsAg seroclearance. Further studies are needed to confirm our funding and investigate the mechanisms underlying the impact of FL on CHB.