Post Hoc Analysis of the Impact of Lemborexant on Patient-Reported Sleep and Insomnia Severity in Adults with Insomnia and Depression Histories
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DOI: 10.1017/s1092852922000499
Abstract: Abstract Introduction The dual orexin receptor antagonist lemborexant (LEM) is approved in multiple countries including the United States, Japan, Canada, and Australia for insomnia treatment in adults. In phase 3 study E2006-G000-303 (Study 303; SUNRISE-2;… read more here.
Keywords: lem; pbo; depression; analysis ... See more keywords
0354 Effect of Lemborexant on Sleep Architecture in Subjects with Comorbid Insomnia and Mild Obstructive Sleep Apnea from a Ph 3 Trial
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DOI: 10.1093/sleep/zsad077.0354
Abstract: Many patients with insomnia have co-morbid obstructive sleep apnea (COMISA). Patients with obstructive sleep apnea (OSA) may also have decreased REM-sleep. Lemborexant (LEM) is a dual-orexin-receptor-antagonist approved to treat adults with insomnia. LEM has been… read more here.
Keywords: zol pbo; lem; apnea; zol ... See more keywords
Acute Cognitive Effects of the Dual Orexin Receptor Antagonist Lemborexant Compared With Suvorexant and Zolpidem in Recreational Sedative Users
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DOI: 10.1097/jcp.0000000000001562
Abstract: Abstract Purpose/Background As part of a human abuse potential (HAP) study of lemborexant (LEM), the effects of therapeutic (LEM 10 mg), and supratherapeutic doses of LEM 20 mg and LEM 30 mg on cognition and… read more here.
Keywords: suv; lem; reaction; reaction time ... See more keywords
Blockchain-Based Local Energy Market Enabling P2P Trading: An Australian Collated Case Study on Energy Users, Retailers and Utilities
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DOI: 10.1109/access.2022.3224936
Abstract: This paper presents a collated case study on local energy market (LEM) in Australia, in which energy users take part frequently in peer-to-peer (P2P) energy trading among themselves considering the agile presence of energy retailers… read more here.
Keywords: trading; lem; energy; collated case ... See more keywords
Generalized Learning Vector Quantization With Log-Euclidean Metric Learning on Symmetric Positive-Definite Manifold.
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DOI: 10.1109/tcyb.2022.3178412
Abstract: In many classification scenarios, the data to be analyzed can be naturally represented as points living on the curved Riemannian manifold of symmetric positive-definite (SPD) matrices. Due to its non-Euclidean geometry, usual Euclidean learning algorithms… read more here.
Keywords: lem; metric learning; distance; geometry ... See more keywords