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https://www.selleckchem.com/products/salubrinal.html The Spearman correlation coefficient was used to determine the correlation between sEAdi and tEAdi. Agreement was calculated by using Bland-Altman statistics. RESULTS Fifteen subjects were included. The tEAdi detected 3,675 breathing efforts, of which 3,162 (86.0%) were also detected by sEAdi. A statistically significant temporal correlation (r = 0.95, P less then .001) was found between sEAdi and tEAdi in stable recordings. The mean difference in the time intervals between both techniques was 10.1 ms, with limits of agreement from -410 to 430 ms. CONCLUSIONS Analysis of our results showed that sEAdi was not reliable for breathing effort detection in subjects who were invasively ventilated compared with tEAdi. In stable recordings, however, sEAdi and tEAdi had excellent temporal correlation and good agreement. With optimization of signal stability, sEAdi may become a useful monitoring tool. Copyright © 2020 by Daedalus Enterprises.BACKGROUND Medication adherence in asthma and COPD is notoriously low. To intervene effectively, family physicians need to assess adherence accurately, which is a challenging endeavor. In collaboration family physicians and individuals with asthma or COPD, we aimed to explore the barriers and facilitators of assessing medication adherence in clinical practice (exploratory phase), and to develop a novel web-based tool (e-MEDRESP) that will allow physicians to monitor adherence using pharmacy claims data (development phase). METHODS We used qualitative research methods and a framework inspired by user-centered design principles. Five focus groups were held 2 with subjects (n = 15) and 3 with physicians (n = 20), and 10 individual interviews were conducted with physicians. In the exploratory phase, data were analyzed using thematic networks. In the development phase, we identified components to be included in an e-MEDRESP prototype through an iterative approach. The web-based e-MEDRESP tool

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