Hinrichsenlindgaard0319

BACKGROUND Currently, there are no recommendations regarding the minimum duration of in-hospital monitoring after transfemoral (TF) transcatheter aortic valve replacement (TAVR) and practices are extremely heterogeneous. We, therefore, aimed to evaluate length of stay (LOS) and predictive factors for late discharge after TF TAVR using data from the FRANCE TAVI registry. METHODS TAVR was performed in 12,804 patients in 48 French centers between 2013 and 2015. LOS was evaluated in 5857 TF patients discharged home. LOS was calculated from TAVR procedure (day 0) to discharge. The study population was divided into three groups based on LOS values. Patients discharged within 3 days constituted the "very early" discharge group, patients with a LOS between 3 and 6 days constituted the "early" discharge group, and patients with a length of stay > 6 days constituted the "late" discharge group. RESULTS The median LOS was 7 (5-9) days and was extremely variable among centers. The proportion of patients discharged very early, early, and late was 4.4% (n = 256), 33.7% (n = 1997), and 61.9% (n = 3624) respectively. Variables associated with late discharge were female sex, co-morbidities, major complications, self-expandable valve, general anesthesia, and a significant center effect. In contrast, history of previous pacemaker was a protective factor. The composite of death and re-admission in the very early and early versus late discharge groups was similar at 30 days (3.3% vs. 3.5%, p = 0.66). CONCLUSIONS LOS is extremely variable after TF TAVR in France. Co-morbidities and complications were predictive factors of late discharge after TAVI. Interestingly, the use of self-expandable prosthesis and general anesthesia may also contribute to late discharge. Our results confirm that early discharge is safe.Non-targeted analysis (NTA) methods are being increasingly used to aid in the identification of unknown compounds in the environment, a problem that has challenged environmental chemists for decades. Despite its increased use, quality assurance practices for NTA have not been well established. Furthermore, capabilities and limitations of certain NTA methods have not been thoroughly evaluated. Standard reference material dust (SRM 2585) was used here to evaluate the ability of NTA to identify previously reported compounds, as well as a suite of 365 chemicals that were spiked at various stages of the analytical procedure. Analysis of the unaltered SRM 2585 extracts revealed that several previously reported compounds can be identified by NTA, and that correct identification was dependent on concentration. A manual inspection of unknown features in SRM 2585 revealed the presence of two chlorinated and fluorinated compounds in high abundance, likely precursors to perfluorooctane sulfonate (PFOS) and perfluorohexanfor identifying and monitoring compounds that may be of toxicological concern. Graphical abstract.The surgeon general of the USA defines osteoporosis as "a skeletal disorder characterized by compromised bone strength, predisposing to an increased risk of fracture." Measuring bone strength, Biomechanical Computed Tomography analysis (BCT), namely, finite element analysis of a patient's clinical-resolution computed tomography (CT) scan, is now available in the USA as a Medicare screening benefit for osteoporosis diagnostic testing. Helping to address under-diagnosis of osteoporosis, BCT can be applied "opportunistically" to most existing CT scans that include the spine or hip regions and were previously obtained for an unrelated medical indication. For the BCT test, no modifications are required to standard clinical CT imaging protocols. The analysis provides measurements of bone strength as well as a dual-energy X-ray absorptiometry (DXA)-equivalent bone mineral density (BMD) T-score at the hip and a volumetric BMD of trabecular bone at the spine. Based on both the bone strength and BMD measurements, a phyiously undergone CT testing (including hip or spine regions) for an unrelated medical condition.PURPOSE Natural language processing (NLP) can be used for automatic flagging of radiology reports. We assessed deep learning models for classifying non-English head CT reports. METHODS We retrospectively collected head CT reports (2011-2018). Reports were signed in Hebrew. Emergency department (ED) reports of adult patients from January to February for each year (2013-2018) were manually labeled. All other reports were used to pre-train an embedding layer. We explored two use cases (1) general labeling use case, in which reports were labeled as normal vs. pathological; (2) specific labeling use case, in which reports were labeled as with and without intra-cranial hemorrhage. We tested long short-term memory (LSTM) and LSTM-attention (LSTM-ATN) networks for classifying reports. We also evaluated the improvement of adding Word2Vec word embedding. Deep learning models were compared with a bag-of-words (BOW) model. RESULTS We retrieved 176,988 head CT reports for pre-training. We manually labeled 7784 reports as normal (46.3%) or pathological (53.7%), and 7.1% with intra-cranial hemorrhage. For the general labeling, LSTM-ATN-Word2Vec showed the best results (AUC = 0.967 ± 0.006, accuracy 90.8% ± 0.01). For the specific labeling, all methods showed similar accuracies between 95.0 and 95.9%. Both LSTM-ATN-Word2Vec and BOW had the highest AUC (0.970). CONCLUSION For a general use case, word embedding using a large cohort of non-English head CT reports and ATN improves NLP performance. For a more specific task, BOW and deep learning showed similar results. STAT5IN1 Models should be explored and tailored to the NLP task.PURPOSE The trauma centre of the Wuerzburg University Hospital has integrated a pioneering dual-room twin-CT scanner in a multiple trauma pathway. For concurrent treatment of two trauma patients, two carbon CT examination and intervention tables are positioned head to head with one sliding CT-Gantry in the middle. The focus of this study is the process of trauma care with the time to CT (tCT) and the time to operation (tOR) as quality indicator. METHODS All patients with suspected multiple trauma, who required emergency surgery and who were initially diagnosed by the CT trauma protocol between 05/2018 and 12/2018 were included. Data relating to time spans (tCT and tOR), severity of injury and outcome was obtained. RESULTS 110 of the 589 screened trauma patients had surgery immediately after finishing primary assessment in the ER. The ISS was 17 (9-34) (median and interquartile range, IQR). tCT was 15 (11-19) minutes (median and IQR) and tOR was 96.5 (75-119) minutes (median and IQR). In the first 30 days, seven patients died (6.4%) including two within the first 24 h (2%). There were two ICU days (1-6) (median and IQR) and one (0-1) (median and IQR) ventilator day. CONCLUSION The twin-CT technology is a fascinating tool to organize high-quality trauma care for two multiple trauma patients simultaneously.Sexual and gender minority (SGM) individuals have higher tobacco use prevalence and consequently higher burden of tobacco-caused diseases including cancer and cardiovascular disease compared with their heterosexual or cisgender counterparts. Yet, there is a critical gap in research focused on measuring SGM tobacco-related health disparities and addressing unmet needs of SGM individuals in the context of nicotine and tobacco research. In this commentary, we summarize recommendations discussed during a preconference workshop focused on challenges and opportunities in conducting SGM tobacco control research at the 2019 Society for Research on Nicotine and Tobacco Annual Meeting. Specifically, we recommend defining and measuring SGM identity in all nicotine and tobacco research routinely, using novel methods to engage a demographically diverse sample of the SGM population, and eliciting SGM community voices in tobacco control research. Addressing these critical research gaps will enable the scientific community to generate the data to fully understand and support SGM individuals in tobacco use prevention and cessation. © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.BACKGROUND Increasing educational level of the population could be a strategy to prevent depression. We investigated whether education may offer a greater benefit for mental health to women and to individuals living in socioeconomically disadvantaged areas. METHODS We performed a cross-sectional study using data on 6964 Czech participants of the Health, Alcohol and Psychosocial factors in Eastern Europe study (on average 58 years old; 53% women). Binary logistic regression was used to examine the association of education with depressive symptoms, adjusting for several groups of covariates. Interactions were tested between education and sex as well as between education and socioeconomic advantage of the area of residence. RESULTS Higher education was strongly associated with lower odds of depressive symptoms, independently of sociodemographic characteristics, health behavior and somatic diseases. This association was attenuated after adjusting for other markers of individual socioeconomic position (work activity, material deprivation and household items). There were no interactions between education and either sex or socioeconomic advantage of the area of residence. CONCLUSIONS We did not find an independent association between education and depressive symptoms after controlling for other socioeconomic markers in a sample with a formative history of communistic ideologies. Women or individuals from socioeconomically disadvantaged areas do not seem to gain a larger mental health benefit from education. © The Author(s) 2020. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.BACKGROUND Previous research from the USA has shown that low health literacy is associated with higher hospitalization rates and higher rates of emergency service use. However, studies in a European context using more comprehensive health literacy definitions are lacking. The aim was to study the impact of low health literacy on healthcare utilization in a Danish context. METHODS In this prospective cohort study, baseline survey data from 2013 were derived from a large Danish health and morbidity survey and merged with individual-level longitudinal register data for a 4-year follow-up period. The study included people in the general population (n = 29 473) and subgroups of people with four different chronic conditions cardiovascular disease (CVD) (n = 2389), chronic obstructive pulmonary disease (COPD) (n = 1214), diabetes (n = 1685) and mental disorders (n = 1577). RESULTS In the general population, low health literacy predicted slightly more visits to the general practitioner and admissions to hospital and longer hospitalization periods at 4 years of follow-up, whereas low health literacy did not predict planned outpatient visits or emergency room visits. In people with CVD, low health literacy predicted more days with emergency room visits. In people with mental disorders, difficulties in actively engaging with healthcare providers were associated with a higher number of hospital admission days. No significant association between health literacy and healthcare utilization was found for diabetes or COPD. CONCLUSIONS Even though Denmark has a universal healthcare system the level of health literacy affects healthcare use in the general population and in people with CVD and mental disorders. © The Author(s) 2020. Published by Oxford University Press on behalf of the European Public Health Association.