Paulsenalvarado2085

© 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http//creativecommons.org/licenses/by/4.0/).BACKGROUND/PURPOSE Although illicit substance use-induced toxicity or complication is a frequent cause of visit to the emergency department (ED), there are limited data on cases confirmed by liquid chromatography tandem-mass spectrometry (LC-MS/MS) analysis. This study aimed to describe clinical presentations of patients who visited the ED because of acute illicit substance-related complications. METHODS We performed a retrospective study between May 2017 and August 2018 on patients presenting to the ED with positive urine illicit substance analysis by LC-MS/MS. RESULTS Of 203 patients with at least one illicit substance detected in their urine, 162 (79.8%) showed traditional illicit substances, and 56 (32.0%) showed new psychoactive substances (NPS). Methamphetamine was the most common illicit substance (67.9%). The most common NPS was ketamine (21.7%), followed by synthetic cathinones (14.8%). selleck inhibitor We divided patients into traditional, NPS and combined (both traditional illicit substance and NPS) groups. Polysubstance use was more common in the NPS group than in the traditional group (P  less then  0.001). Most patients were men (78.3%), and the average age was lower in the NPS group compared to the traditional group (P  less then  0.001). Although the chemical structures of cathinones are similar to that of amphetamine, 92.0% of the cathinone use cases without combination with methamphetamine use showed negative immunoassay results. CONCLUSION Our study provided the acute illicit substance complications at ED by LC-MS/MS analysis in Taiwan. Our study showed that more than one-third cases studied were NPS users. Young adults and polysubstance users were more common among NPS users. BACKGROUND Critically compromised by upper airway anatomical impaired properties, obstructive sleep apnea (OSA) can be categorized into different phenotypic traits, mainly including oropharyngeal muscle dysfunction. The upper airway muscle strength training was targeted on oropharyngeal muscle dysfunction by re-educating the oropharyngeal muscles to maintain the upper airway patency. OSA was characterized with multilevel collapsibility of the upper airway; however, the programs are still inconsistent and the effects are unknown. Therefore, the purpose of this study was to investigate the effects of a comprehensive physical therapy on OSA. METHODS Fifteen subjects with newly diagnosed moderate or severe OSA (AHI ≥ 15) were randomized into intervention and control groups. The intervention group underwent a 12-week-intervention of hospital based physical therapy, while the control group was kept on waiting for 12 weeks. Polysomnography (PSG) data, oropharyngeal and respiratory muscle performance were measured before and after intervention. RESULTS In intervention group (n = 8), AHI was significantly improved (from 46.96 ± 19.45 to 32.78 ± 10.78 events/h, p = 0.017); in control group (n = 7), AHI was significantly increased (from 35.77 ± 17.49 to 42.96 ± 17.32 events/h, p = 0.043). While the control group remained no change between pre- and post- intervention, the intervention group demonstrated that other PSG outcomes significantly improved, including arousal index (46.04 ± 18.9 versus 32.98 ± 8.35/h), mean SpO2 (92.88 ± 2.1 versus 94.13 ± 1.46%), and oxygen desaturation index (ODI) (31.13 ± 19.48 versus 20.57 ± 7.83/h). CONCLUSION This comprehensive physical therapy can be prescribed for the significant clinical improvement on sleep apnea for the patients with moderate and severe OSA. V.RATIONALE AND OBJECTIVES To assess the prevalence and associated factors of burnout among U.S. academic radiologists. MATERIALS AND METHODS An online survey was sent to the radiologists who were full members of the Association of University Radiologists in December 2018. Burnout was measured using the abbreviated Maslach Burnout Inventory Human Services Survey. Survey respondents were also requested to complete questions on demographics, potential professional stressors, sense of calling, and career satisfaction. Associations between survey participants' characteristics and burnout were tested using logistic regression model. RESULTS The survey response rate was 27% (228/831). Twenty-nine percent met all three criteria for high burnout, including high emotional exhaustion, high depersonalization, and low personal accomplishment. Seventy-nine percent had one or more symptoms of burnout. Numerous factors including work overload, inability to balance personal and professional life, lack of autonomy, lack of appreciation from patients and other medical staff were significantly associated (p less then 0.05) with high burnout. Older age (OR, 0.95; 95%CI 0.92-0.98; p less then 0.05), higher number of years of experience practicing as radiologists (OR, 0.95; 95%CI 0.92-0.98; p less then 0.05), and holding academic rank of professor (OR, 0.25; 95%CI 0.11-0.56; p less then 0.05) were factors associated with lower odds of experiencing burnout. Radiologists with high burnout were more likely to be dissatisfied with their career (OR, 2.28; 95%CI 1.70-3.07; p less then 0.0001) and less likely to identify medicine as a calling. CONCLUSION Multiple factors contribute to high burnout in academic radiologists. Familiarity with these factors may help academic radiology departments to develop strategies to promote health and wellness of their faculty. RATIONALE AND OBJECTIVES Tumor grading of nonfunctional pancreatic neuroendocrine tumors (NF-pNETs) determines the choice of clinical treatment and management. The pathological grade of pancreatic neuroendocrine tumors is usually assessed on postoperative specimens. The goal of our study is to establish a tumor grade (G) prediction model for preoperative G1/2 NF-pNETs using radiomics for multislice spiral CT image analysis. MATERIALS AND METHODS This retrospective study included a primary cohort of 59 patients and an independent validation cohort of 40 consecutive patients; their multislice spiral CT images were collected from October 2012 to October 2016 and October 2016 to June 2018, respectively. All 99 patients were diagnosed with clinicopathologically confirmed NF-pNETs. Most significant radiomic features were selected using the minimum redundancy and maximum relevance algorithm. Support vector machine classifier with a radial basis function-based predictive model was subsequently developed for clinical use.