Background Inadequate refilling from extravascular compartments during hemodialysis can lead to intradialytic symptoms, such as hypotension, nausea, vomiting, and cramping/myalgia. Relative blood volume (RBV) plays an important role in adapting the ultrafiltration rate which in turn has a positive effect on intradialytic symptoms. It has been clinically challenging to identify changes RBV in real time to proactively intervene and reduce potential negative consequences of volume depletion. Leveraging advanced technologies to process large volumes of dialysis and machine data in real time and developing prediction models using machine learning (ML) is critical in identifying these signals. Method We conducted a proof-of-concept analysis to retrospectively assess near real-time dialysis treatment data from in-center patients in six clinics using Optical Sensing Device (OSD), during December 2018 to August 2019. The goal of this analysis was to use real-time OSD data to predict if a patient’s relative blood volume (RBV) decreases at a rate of at least − 6.5 % per hour within the next 15 min during a dialysis treatment, based on 10-second windows of data in the previous 15 min. A dashboard application was constructed to demonstrate how reporting structures may be developed to alert clinicians in real time of at-risk cases. Data was derived from three sources: (1) OSDs, (2) hemodialysis machines, and (3) patient electronic health records. Results Treatment data from 616 in-center dialysis patients in the six clinics was curated into a big data store and fed into a Machine Learning (ML) model developed and deployed within the cloud. The threshold for classifying observations as positive or negative was set at 0.08. Precision for the model at this threshold was 0.33 and recall was 0.94. The area under the receiver operating curve (AUROC) for the ML model was 0.89 using test data. Conclusions The findings from our proof-of concept analysis demonstrate the design of a cloud-based framework that can be used for making real-time predictions of events during dialysis treatments. Making real-time predictions has the potential to assist clinicians at the point of care during hemodialysis.

This study investigated severe-to-profound hearing-impaired school-age children's comprehension of figurative language. Twelve severe-to-profound hearing-impaired children, ages 9 to 19 years, served as subjects. Twenty sentences, subdivided into four groups (similes, metaphors, idioms, proverbs) comprised the stimulus items. Subjects were instructed to read the sentences and explain them. Three judges rated the subjects' responses on a scale from one (literal interpretation) to three (nonliteral interpretation). Data generated from the hearing-impaired group were compared with the performance of a control group. A significant between-group diference was noted. Furthermore, a regression analysis indicated that the hearing-impaired subjects' performance appeared more dependent upon reading level and was variable across chronological age. FIGURATIVE LANGUAGE is language which deviates from the literal or standard construction, from the established and expected significance to achieve special meaning or effect (Robertson, 1973). According to Wiig and Semel (1976), the ability to identify changes in word meanings and translate the word meanings into abstract and generalized language is basic to the comprehension of figurative language. During early adolescence, it becomes increasingly important to appropriately interpret and use figurative references in both social and academic situations (Wiig & Semel, 1976).Investigators have studied the comprehension of figurative language by severeto-profound hearing impaired children and assert that such individuals demonstrate difficulty understanding such references (Myklebust, 1953; Blackwell, Engen, Fischgrund, & Zaracadoolas, 1978). It has also been reported that severe-toprofound hearing impaired adolescents, either interpret something as literal or it is absurd and therefore, the material is interpreted as insignificant.Acquisition offigurative language in normally-developing children. Billow (1975) indicated that metaphor comprehension is related to maturing cognitive operations suggesting that a &dquo;figurative sense&dquo; is evident as early as five and seven years of at SIMON FRASER LIBRARY on June 3, 2015 cdq.sagepub.com Downloaded from

No abstract

The globalisation of healthcare is changing the demands placed on health professionals. It requires different skills and thought processes across national borders. Thinking in an innovative manner may provide healthcare workers with some of the necessary tools to facilitate international change by increasing students' mental flexibility and ability to apply solutions in multiple contexts. We created the International Innovation Program for health profession education students to learn about and implement the innovation process. The programme provides students the opportunity to learn in interprofessional, international teams and apply didactic knowledge to community problems using the innovation process. The purpose of this article is to describe student perceptions across 4 years of programme implementation. Through analysis of closed-ended survey data, we found that students who participated in the programme reported improvements in collaboration and teamwork, project management, interprofessional teamwork, professional growth and development, thinking in an innovative manner, research and development skills, information seeking, and willingness to work on international projects. Analysis of the open-ended questions revealed five themes: language, teamwork and collaboration, cultural awareness, innovation process, and personal growth and self-improvement. The long-term, follow-up data indicate that these attributes can be transferred into a clinical context which have implications for improved collaboration and patient care.