Maloneycurtis1274

BACKGROUND Recent research in machine-learning techniques has led to significant progress in various research fields. In particular, knowledge discovery using this method has become a hot topic in traditional Chinese medicine. As the key clinical manifestations of patients, symptoms play a significant role in clinical diagnosis and treatment, which evidently have their underlying traditional Chinese medicine mechanisms. OBJECTIVE We aimed to explore the core symptoms and potential regularity of symptoms for diagnosing insomnia to reveal the key symptoms, hidden relationships underlying the symptoms, and their corresponding syndromes. METHODS An insomnia dataset with 807 samples was extracted from real-world electronic medical records. After cleaning and selecting the theme data referring to the syndromes and symptoms, the symptom network analysis model was constructed using complex network theory. We used four evaluation metrics of node centrality to discover the core symptom nodes from multiple aspects. To explnalyses can objectively and effectively find the key symptoms and relationships among symptoms. Identification of the symptom distribution and symptom clusters of insomnia further provide valuable guidance for clinical diagnosis and treatment. ©Fang Hu, Liuhuan Li, Xiaoyu Huang, Xingyu Yan, Panpan Huang. Originally published in JMIR Medical Informatics (http//medinform.jmir.org), 16.04.2020.The coronavirus disease (COVID-19) pandemic has revealed many areas of public health preparedness that are lacking, especially in lower- and middle-income countries. Digital interventions provide many opportunities for strengthening health systems and could be vital resources in the current public health emergency. PF-02341066 We provide several use cases for infection control, home-based diagnosis and screening, empowerment through information, public health surveillance and epidemiology, and leveraging crowd-sourced data. A thoughtful, concerted effort-leveraging existing experience and robust enterprise-grade technologies-can have a substantive impact on the immediate and distal consequences of COVID-19. ©Sultan Mahmood, Khaled Hasan, Michelle Colder Carras, Alain Labrique. Originally published in JMIR Public Health and Surveillance (http//publichealth.jmir.org), 16.04.2020.BACKGROUND The use of multidomain developmental screening tools is a viable strategy for pediatric professionals to identify children at risk for developmental problems. However, a specialized multidimensional computer adaptive testing (MCAT) tool has not been developed to date. OBJECTIVE We developed an app using MCAT, combined with Multidimensional Screening in Child Development (MuSiC) for toddlers, to help patients and their family members or clinicians identify developmental problems at an earlier stage. link2 METHODS We retrieved 75 item parameters from the MuSiC literature item bank for 1- to 3-year-old children, and simulated 1000 person measures from a normal standard distribution to compare the efficiency and precision of MCAT and nonadaptive testing (NAT) in five domains (ie, cognitive skills, language skills, gross motor skills, fine motor skills, and socioadaptive skills). The number of items saved and the cutoff points for the tool were determined and compared. We then developed an app for a Web-based assessment. RESULTS MCAT yielded significantly more precise measurements and was significantly more efficient than NAT, with 46.67% (=(75-40)/75) saving in item length when measurement differences less than 5% were allowed. Person-measure correlation coefficients were highly consistent among the five domains. Significantly fewer items were answered on MCAT than on NAT without compromising the precision of MCAT. CONCLUSIONS Developing an app as a tool for parents that can be implemented with their own computers, tablets, or mobile phones for the online screening and prediction of developmental delays in toddlers is useful and not difficult. ©Chen-Fang Hsu, Tsair-Wei Chien, Julie Chi Chow, Yu-Tsen Yeh, Willy Chou. Originally published in JMIR Pediatrics and Parenting (http//pediatrics.jmir.org), 16.04.2020.BACKGROUND At most institutions, internal medicine residents struggle with balancing clinical duties and learning opportunities, particularly during busy cardiology ward rotations. To improve learning experiences for residents, we helped develop a cardiology handbook app to supplement cardiology education. OBJECTIVE The aim of this study was to report the development, implementation, and preliminary impact of the Krannert Cardiology Handbook app on graduate medical education. METHODS In June 2017, 122 residents at Indiana University were invited to download the digital handbook in the Krannert app. The Krannert app featured a total of 13 chapters written by cardiology fellows and faculty at Indiana University. Residents were surveyed on their self-reported improvement in cardiology knowledge and level of satisfaction after using the Krannert app. Residents were also surveyed regarding their preference for a digital handbook app versus a paper handbook. RESULTS Of the 122 residents, 38 trainees (31.1%) participated in survey evaluations. Among all respondents, 31 app users (82%) reported that the app helped improve their cardiology knowledge base. The app had an overall favorable response. CONCLUSIONS The Krannert app shows promise in augmenting clinical education in cardiology with mobile learning. Future work includes adding new topics, updating the content, and comparing the app to other learning modalities. ©Asad Torabi, Abhishek Khemka, Pantila V Bateman. Originally published in JMIR Medical Education (http//mededu.jmir.org), 16.04.2020.BACKGROUND Ectopic pregnancy (EP) is a serious complication of assisted reproductive technology (ART). However, there is no acknowledged mathematical model for predicting EP in the ART population. OBJECTIVE The goal of the research was to establish a model to tailor treatment for women with a higher risk of EP. METHODS From December 2015 to July 2016, we retrospectively included 1703 women whose serum human chorionic gonadotropin (hCG) levels were positive on day 21 (hCG21) after fresh embryo transfer. Multivariable multinomial logistic regression was used to predict EP, intrauterine pregnancy (IUP), and biochemical pregnancy (BCP). RESULTS The variables included in the final predicting model were (hCG21, ratio of hCG21/hCG14, and main cause of infertility). During evaluation of the model, the areas under the receiver operating curve for IUP, EP, and BCP were 0.978, 0.962, and 0.999, respectively, in the training set, and 0.963, 0.942, and 0.996, respectively, in the validation set. The misclassification rates were 0.038 and 0.045, respectively, in the training and validation sets. Our model classified the whole in vitro fertilization/intracytoplasmic sperm injection-embryo transfer population into four groups first, the low-risk EP group, with incidence of EP of 0.52% (0.23%-1.03%); second, a predicted BCP group, with incidence of EP of 5.79% (1.21%-15.95%); third, a predicted undetermined group, with incidence of EP of 28.32% (21.10%-35.53%), and fourth, a predicted high-risk EP group, with incidence of EP of 64.11% (47.22%-78.81%). CONCLUSIONS We have established a model to sort the women undergoing ART into four groups according to their incidence of EP in order to reduce the medical resources spent on women with low-risk EP and provide targeted tailor-made treatment for women with a higher risk of EP. ©Huiyu Xu, Guoshuang Feng, Yuan Wei, Ying Feng, Rui Yang, Liying Wang, Hongxia Zhang, Rong Li, Jie Qiao. Originally published in JMIR Medical Informatics (http//medinform.jmir.org), 16.04.2020.BACKGROUND Positive results can be obtained through game-based learning, but children with physical disabilities have fewer opportunities to participate in enjoyable physical activity. Because intelligent serious games can provide personalized learning opportunities, motivate the learner, teach 21st-century skills, and provide an environment for authentic and relevant assessment, they may be used to help children and adolescents with different kinds of learning disabilities to develop social and cognitive competences. link3 OBJECTIVE The aim of the study was to produce and evaluate a suite of intelligent serious games based on accessible learning objectives for improving key skills, personal development, and work sustainability among children with learning difficulties. METHODS We conducted this research between 2016 and 2018, with pupils aged 11 to 12 years with learning disabilities who were integrated into the mainstream educational system. We used a 4-step methodology to develop learner creativity and social cot survey confirmed improvements in all aspects. ©Andrej Flogie, Boris Aberšek, Metka Kordigel Aberšek, Cecilia Sik Lanyi, Igor Pesek. Originally published in JMIR Serious Games (http//games.jmir.org), 16.04.2020.BACKGROUND Single high-sensitivity troponin T (hs-TnT) measurement is predictive of cardiac events in adults with congenital heart disease (ACHD). We aimed to study the prognostic value of serial hs-TnT measurements in stable patients with ACHD. METHODS In total, 602 consecutive patients with ACHD were enrolled in this prospective study (2011-2013). Blood sampling was performed at enrollment and thereafter yearly during scheduled visits, up to 4 years. Hs-TnT, N-terminal pro B-type natriuretic peptide (NT-proBNP), and estimated glomerular filtration rate (eGFR) were measured. The composite primary endpoint was defined as all-cause mortality, heart failure, arrhythmia, hospitalization, cardiac (re)interventions, or thromboembolic events. The relationship between changes in serial hs-TnT and the primary endpoint was studied by joint models with adjustment for repeated NT-proBNP and eGFR. RESULTS In 601 patients (median age, 33 [interquartile range, 25-41] years, 42% women, 90% NYHA I), at least 1 hs-TnT measurement was performed; a mean of 4.3 hs-TnT measurements per patient were collected. After a median follow-up of 5.8 [interquartile range, 5.3-6.3] years, 229 (38.1%) patients reached the primary endpoint. On average, hs-TnT levels increased over time, and more in patients who reached the primary endpoint (P less then 0.001). A 2-fold higher hs-TnT was associated with the primary endpoint (unadjusted hazard ratio, 1.62; 95% confidence interval, 1.44-1.82; P less then 0.001). The association remained after adjustment for repeated eGFR but not when adjusted for repeated NT-proBNP; repeated NT-proBNP remained associated with the primary endpoint. CONCLUSION In stable patients with ACHD, hs-TnT levels increased before the occurrence of an event and repeated hs-TnT was associated with the risk of adverse cardiac events. However, repeated hs-TnT was not superior to repeated NT-proBNP. Applying big-data analytic techniques to brain images from 18,707 individuals is shedding light on the influence of aging on the brain. © 2020, Nyberg and Wåhlin.In Wnt/β-catenin signaling, the transcriptional coactivator β-catenin is regulated by its phosphorylation in a complex that includes the scaffold protein Axin and associated kinases. Wnt binding to its coreceptors activates the cytosolic effector Dishevelled (Dvl), leading to the recruitment of Axin and the inhibition of β-catenin phosphorylation. This process requires interaction of homologous DIX domains present in Dvl and Axin, but is mechanistically undefined. We show that Dvl DIX forms antiparallel, double-stranded oligomers in vitro, and that Dvl in cells forms oligomers typically less then 10 molecules at endogenous expression levels. Axin DIX (DAX) forms small single-stranded oligomers, but its self-association is stronger than that of DIX. DAX caps the ends of DIX oligomers, such that a DIX oligomer has at most four DAX binding sites. The relative affinities and stoichiometry of the DIX-DAX interaction provide a mechanism for efficient inhibition of β-catenin phosphorylation upon Axin recruitment to the Wnt receptor complex.