OBJECTIVE: To improve neonatal outcomes through the implementation of an eat, sleep, console (ESC) assessment and change in hospital policy regarding the monitoring requirements for pharmacologic treatment of neonates with neonatal abstinence syndrome (NAS).
METHODS: Retrospective chart review and descriptive survey design.
METHODS: A hospital in Northwestern Ontario decided to implement an evidence-informed practice change to better care for neonates with NAS.
METHODS: Neonates being screened for NAS during the Modified Finnegan Neonatal Abstinence Syndrome Scoring System (MFNASSS) protocol (n = 75) and ESC protocol (n = 40). Nurses working in the departments after the implementation of ESC were surveyed.
METHODS: Length of stay (LOS) and morphine administration by intervention status using unadjusted hazard and risk ratios, respectively. Descriptive statistics are also presented. A one-sample t test was completed for the nurses\' perspectives survey questions.
RESULTS: Reduced rate of LOS (HR = 1.66, 95% confidence interval [1.1, 2.51]) was observed for participants receiving the ESC intervention (4.53, SD = 1.94), compared to the MFNASSS control (7.45, SD = 6.35). Although the ESC group appeared to have a greater proportion of neonates administered morphine (42.5% ESC vs. 26.7% MFNASSS), the relative risk was not statistically significant (RR = 1.28, 95% confidence interval [0.95, 1.72]). Morphine doses per day were reduced in the ESC group (0.37, SD = 1.50) compared to the MFNASSS group (5.16, SD = 1.02). Overall, the nurses had a positive perspective on the policy change.
CONCLUSIONS: ESC was successfully implemented in a Northwestern Ontario hospital. The overall LOS of neonates with NAS decreased. Nurses found the policy change to be safe and attainable.

UNASSIGNED: Recent studies have shown that epicardial adipose tissue (EAT) is an independent atrial fibrillation (AF) prognostic marker and has influence on the myocardial function. In computed tomography (CT), EAT volume (EATv) and density (EATd) are parameters that are often used to quantify EAT. While increased EATv has been found to correlate with the prevalence and the recurrence of AF after ablation therapy, higher EATd correlates with inflammation due to arrest of lipid maturation and with high risk of plaque presence and plaque progression. Automation of the quantification task diminishes the variability in readings introduced by different observers in manual quantification and results in high reproducibility of studies and less time-consuming analysis. Our objective is to develop a fully automated quantification of EATv and EATd using a deep learning (DL) framework.
UNASSIGNED: We proposed a framework that consists of image classification and segmentation DL models and performs the task of selecting images with EAT from all the CT images acquired for a patient, and the task of segmenting the EAT from the output images of the preceding task. EATv and EATd are estimated using the segmentation masks to define the region of interest. For our experiments, a 300-patient dataset was divided into two subsets, each consisting of 150 patients: Dataset 1 (41,979 CT slices) for training the DL models, and Dataset 2 (36,428 CT slices) for evaluating the quantification of EATv and EATd.
UNASSIGNED: The classification model achieved accuracies of 98% for precision, recall and F 1 scores, and the segmentation model achieved accuracies in terms of mean ( ± std.) and median dice similarity coefficient scores of 0.844 ( ± 0.19) and 0.84, respectively. Using the evaluation set (Dataset 2), our approach resulted in a Pearson correlation coefficient of 0.971 ( R 2 = 0.943) between the label and predicted EATv, and the correlation coefficient of 0.972 ( R 2 = 0.945) between the label and predicted EATd.
UNASSIGNED: We proposed a framework that provides a fast and robust strategy for accurate EAT segmentation, and volume (EATv) and attenuation (EATd) quantification tasks. The framework will be useful to clinicians and other practitioners for carrying out reproducible EAT quantification at patient level or for large cohorts and high-throughput projects.

With the enormous progress in the field of cardiovascular imaging in recent years, computed tomography (CT) has become readily available to phenotype atherosclerotic coronary artery disease. New analytical methods using artificial intelligence (AI) enable the analysis of complex phenotypic information of atherosclerotic plaques. In particular, deep learning-based approaches using convolutional neural networks (CNNs) facilitate tasks such as lesion detection, segmentation, and classification. New radiotranscriptomic techniques even capture underlying bio-histochemical processes through higher-order structural analysis of voxels on CT images. In the near future, the international large-scale Oxford Risk Factors And Non-invasive Imaging (ORFAN) study will provide a powerful platform for testing and validating prognostic AI-based models. The goal is the transition of these new approaches from research settings into a clinical workflow. In this review, we present an overview of existing AI-based techniques with focus on imaging biomarkers to determine the degree of coronary inflammation, coronary plaques, and the associated risk. Further, current limitations using AI-based approaches as well as the priorities to address these challenges will be discussed. This will pave the way for an AI-enabled risk assessment tool to detect vulnerable atherosclerotic plaques and to guide treatment strategies for patients.

Traumatic perforation of the tympanic membrane often occurs in Japanese patients who scratch their ears to relieve itching. Traumatic tympanic membrane perforation may close spontaneously, but the perforation may remain. One of the causes of prolonged tympanic membrane perforation closure is dysfunction of the Eustachian tube. In this study, I experienced a case of chronic epipharyngitis causing ear fullness and itching, and a traumatic perforation of the tympanic membrane caused by scratching with an earpick. The patient also had sleep apnea syndrome (SAS). Treatment of chronic epipharyngitis with epipharyngeal abrasive therapy (EAT) shortened the time to perforation closure and improved SAS, suggesting that EAT affected the improvement of Eustachian tube function and airway resistance in the epipharynx.

A case of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) with chronic epipharyngitis was treated with epipharyngeal abrasive therapy (EAT). The symptoms of ME/CFS improved along with the improvement of chronic epipharyngitis. The patient was followed up with endocrine and autonomic function tests. Endocrine function tests included salivary cortisol and salivary α-amylase activity. Salivary α-amylase activity was stimulated by EAT. EAT improved the diurnal variability of salivary cortisol secretion. Autonomic function tests included heart rate variability analysis by orthostatic stress test. EAT normalized parasympathetic and sympathetic reflexes over time and regulated autonomic balance. Based on the improvement of symptoms and test results, EAT was considered effective for ME/CFS. A literature review was conducted on the mechanism of the therapeutic effect of EAT on ME/CFS.

One of the characteristic features of ovarian cancer is its early dissemination. Metastasis and the invasiveness of ovarian cancer are strongly dependent on the phenotypical and molecular determinants of cancer cells. Invasive cancer cells, circulating tumor cells, and cancer stem cells, which are responsible for the metastatic process, may all undergo different modes of transition, giving rise to mesenchymal, amoeboid, and redifferentiated epithelial cells. Such variability is the result of the changing needs of cancer cells, which strive to survive and colonize new organs. This would not be possible if not for the variety of migration modes adopted by the transformed cells. The most common type of metastasis in ovarian cancer is dissemination through the transcoelomic route, but transitions in ovarian cancer cells contribute greatly to hematogenous and lymphatic dissemination. This review aims to outline the transition modes of ovarian cancer cells and discuss the migratory capabilities of those cells in light of the known ovarian cancer metastasis routes.

BACKGROUND: this study aimed to assess the complex relationship between EAT thickness, as measured with echocardiography, and the severity of coronary artery disease (CAD). We investigated whether individuals with higher EAT thickness underwent coronary revascularization. Subsequently, we conducted a three-year follow-up to explore any potential modifications in EAT depots post-angioplasty.
METHODS: we conducted a prospective and retrospective cross-sectional observational study involving 150 patients consecutively referred for acute coronary syndrome, including ST-elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction (NSTEMI), and unstable angina. Upon admission (T0), all patients underwent coronary angiography to assess the number of pathologic coronary vessels. Percutaneous transluminal coronary angioplasty (PTCA) was performed based on angiogram results if indicated. The sample was categorized into two groups: non-revascularized (no-PTCA) and revascularized (PTCA). Transthoracic echocardiograms to measure epicardial fat thickness were conducted at admission (T0) and after a 3-year follow-up (T1).
CONCLUSIONS: findings revealed a positive correlation between EAT thickness and the severity of coronary artery disease (CAD), with patients undergoing PTCA showing decreased EAT thickness after three years. Echocardiography demonstrated reliability in assessing EAT, offering potential for risk stratification. The study introduces a cut-off value of 0.65 cm as a diagnostic tool for cardiovascular risk. Incorporating EAT measurements into clinical practice may lead to more precise risk stratification and tailored treatment strategies, ultimately reducing the burden of cardiovascular disease.

A Southeastern, 741-bed acute care, Magnet designated teaching hospital and level III B NICU identified assessment and treatment concerns for Neonatal Opioid Withdrawal Syndrome (NOWS). In March 2020, a quality improvement project led to a multidisciplinary team formation to determine the effectiveness of the Eat, Sleep, Console (ESC) model of care in reducing the length of treatment (LOT) and length of stay (LOS) for neonates experiencing NOWS rather than use of the Finnegan Neonatal Abstinence Syndrome Scoring tool. The results concluded a decrease in the average LOT from 19.2 to 2.5 days and the average LOS from 23.9 to 9.3 days for those admitted directly into the ESC model of care on postpartum vs previous direct admission to the NICU. A group samples t-test showed there was a statistically significant decrease in LOS for ESC patients (p < .001) and LOT for ESC patients (p <001).

Compared with the Finnegan Neonatal Abstinence Scoring System (FNASS), the Eat, Sleep, Console (ESC) approach reduces pharmacotherapy and length of stay (LOS) for neonatal opioid withdrawal syndrome (NOWS) infants. The independent outcome contribution of ESC is unknown as the approach combines ESC assessment with additional management changes. Our objective was to evaluate ESC assessment\'s independent impact on outcomes compared with FNASS. We conducted a retrospective cohort study of in utero opioid-exposed infants ≥35 weeks gestation managed with FNASS versus ESC. Outcomes included pharmacotherapy initiation, LOS, length of pharmacotherapy, and emergency department visit/readmissions. Among 151 FNASS and 100 ESC managed infants, pharmacotherapy initiation (P = .47), LOS for all infants (P = .49), and LOS for pharmacologically treated infants (P = .68) were similar. Length of pharmacotherapy did not differ (P = .84). Emergency department evaluation/NOWS readmission was equally rare (P = .65). Using equivalent models of care, comparison of ESC and FNASS assessment tools showed no difference in NOWS outcomes.

BACKGROUND: Obesity is a major risk factor of many chronic diseases. However, current obesity control policies and actions are not sufficient to halt the pandemic. It has been documented that more than half of all adults are not able to interpret their own weight status, not to mention to practice healthy lifestyles. Social media and interactive websites can reach people on a long-term basis, which may be used as intervention vehicles to build up cognition for weight control and to promote healthy behavior practices.
OBJECTIVE: WAKE.TAIWAN is an ongoing web-based multifaceted healthy lifestyle promotion program with social media and interactive websites as the intervention vehicle. This study aimed to examine whether adults reached by our program would have increased awareness to their own anthropometric measures, correctly judge their body weight status, and practice healthy behaviors over time.
METHODS: This study adopted a quasi-experimental design with web-based questionnaire surveys. The experimental group consisted of WAKE.TAIWAN Facebook group members aged 20-65 years who have used the interactive website health education resources (n=177). The group was further stratified into 2 subgroups based on their duration of participation (E1 group: duration <1 year; E2 group: duration ≥1 year). The control group consisted of other Facebook users (n=545) in the same age range who had not been exposed to the health education materials of this project. A total of 722 people (male: n=267, 37%; and female: n=455, 63%) participated in our survey in 2019. Data were analyzed to evaluate program effectiveness using a generalized linear model.
RESULTS: The proportion of people correctly interpreting their own weight status in the experimental group was greater than that of the control group (control group: 320/545, 58.7%; group E1: 53/88, 60%; and group E2: 64/89, 72%). The E2 experimental group was significantly better than the control group in paying attention to weight-related measures and in correctly interpreting their own weight status (odds ratio 1.73, 95% CI 1.04-2.89; P=.04). With respect to the behavioral stages of practicing healthy eating and active living, both experimental groups, E1 and E2, performed significantly better than the control group (group E1: P=.003 and P=.02; and group E2: P=.004 and P<.001, respectively).
CONCLUSIONS: This study demonstrates that the longer the participants were exposed to our social media-based programs, the higher the proportion of them that would have the correct judgement on their weight status and fall in the higher stages of healthy lifestyle behaviors. A longitudinal follow-up survey is in place to verify these findings.