Notes

Electrostatic Potential Area Consequences in Amine Macrocyclizations inside Yoctoliter Spaces: Supramolecular Electron Withdrawing/Donating Organizations.
ears. Of the 9871 participants, 3157 (31.97%) were survivors of leukemia, 2075 (21.02%) lymphoma, and 1356 (13.7%) central nervous system (CNS) tumors. Most participants (9225/9871, 93.46%) had no history of a subsequent tumor; 77.45% (7645/9871) received chemotherapy with or without other treatments. More than half (5460/9871, 55.31%) were aged 25 to 34 years at the time of the HRQoL study. Participating survivors differed from nonparticipants; participants were more often women, survivors of leukemia or lymphoma, and less frequently, survivors of CNS tumors than nonparticipants.

PanCareLIFE successfully assessed HRQoL and its predictors in 9871 European survivors of childhood cancer. This large population will permit detailed investigations of HRQoL after childhood cancer, particularly the impact of hearing and female fertility impairment on HRQoL.

RR1-10.2196/21851.
RR1-10.2196/21851.
Diabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes-specific virtual communities.

The objective of this study was to examine social support exchanges from a type 2 diabetes self-management education and support intervention that was delivered via a virtual environment.

Data comprised virtual environment-mediated synchronous interactions among participants and between participants anhat are effective and sustainable, where social interactions can be leveraged to achieve diverse health goals.
In schizophrenia spectrum populations, adherence to treatment is poor, community-based supports are limited, and efforts to foster illness self-management have had limited success. These challenges contribute to frequent, lengthy, and costly hospital readmissions and poor functional outcomes. Digital health strategies, in turn, hold considerable promise in the effort to address these problems.

This feasibility trial will examine a digital health platform called App4Independence (A4i), which was designed to enhance illness self-management and treatment engagement for individuals with schizophrenia.

Feasibility metrics in this single-blind, randomized trial include study recruitment and retention, rate of technology use, safety, and utility in clinical interactions. Other outcome metrics include symptomatology, treatment adherence, patient-provider alliance, and quality of life. In this trial, 160 study participants with schizophrenia spectrum diagnoses will be randomized to either treatment or control conditions, with pretest-posttest outcomes measured over a 6-month period.

This study was funded by the Canadian Institutes of Health Research in January 2020 and received Institutional Review Board approval on August 13, 2020. This study plans to begin recruiting in January 2021 and will be completed within 3 years. Selleckchem Abivertinib Data collection is projected to begin in January 2021.

This research will provide critical information for the development of this new technology in the larger effort to address a key problem in the schizophrenia field-how to leverage technology to enhance illness self-management and care engagement in resource-limited service contexts.

PRR1-10.2196/24736.
PRR1-10.2196/24736.
Serious games are being used to train specific technical skills in medicine, and most research has been done for surgical skills. It is not known if these games improve technical skills in real life as most games have not been completely validated.

This scoping review aimed to evaluate the current use of serious games for improving technical skills in medicine and to determine their current validation state using a validation framework specifically designed for serious games.

We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A multidatabase search strategy was adopted, after which a total of 17 publications were included in this review.

These 17 publications described five different serious games for improving technical skills. We discuss these games in detail and report about their current validation status. Only one game was almost fully validated. We also discuss the different frameworks that can be used for validation of serious games.

Serious games are not extensively used for improving technical skills in medicine, although they may represent an attractive alternative way of learning. The validation of these games is mostly incomplete. Additionally, several frameworks for validation exist, but it is unknown which one is the best. This review may assist game developers or educators in validating serious games.
Serious games are not extensively used for improving technical skills in medicine, although they may represent an attractive alternative way of learning. The validation of these games is mostly incomplete. Additionally, several frameworks for validation exist, but it is unknown which one is the best. This review may assist game developers or educators in validating serious games.
Secondary hypertension is a kind of hypertension with a definite etiology and may be cured. Patients with suspected secondary hypertension can benefit from timely detection and treatment and, conversely, will have a higher risk of morbidity and mortality than those with primary hypertension.

The aim of this study was to develop and validate machine learning (ML) prediction models of common etiologies in patients with suspected secondary hypertension.

The analyzed data set was retrospectively extracted from electronic medical records of patients discharged from Fuwai Hospital between January 1, 2016, and June 30, 2019. A total of 7532 unique patients were included and divided into 2 data sets by time 6302 patients in 2016-2018 as the training data set for model building and 1230 patients in 2019 as the validation data set for further evaluation. Extreme Gradient Boosting (XGBoost) was adopted to develop 5 models to predict 4 etiologies of secondary hypertension and occurrence of any of them (named as composite outcome), including renovascular hypertension (RVH), primary aldosteronism (PA), thyroid dysfunction, and aortic stenosis.
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