Deep Learning Analyses of Brain MRI to Identify Sustained Attention Deficit in Treated Obstructive Sleep Apnea: A Pilot Study.

Purpose: Persistent sustained attention deficit (SAD) after continuous positive airway pressure (CPAP) treatment is a source of quality of life and occupational impairment in obstructive sleep apnea (OSA). However, persistent SAD is difficult to predict in patients initiated on CPAP treatment. We performed secondary analyses of brain magnetic resonance (MR) images in treated OSA participants, using deep learning, to predict SAD. Methods: 26 middle-aged men with CPAP use of more than 6 hours daily and MR imaging were included. SAD was defined by psychomotor vigilance task lapses of more than 2. 17 participants had SAD and 9 were without SAD. A Convolutional Neural Network (CNN) model was used for classifying the MR images into +SAD and -SAD categories. Results: The CNN model achieved an accuracy of 97.02±0.80% in classifying MR images into +SAD and -SAD categories. Assuming a threshold of 90% probability for the MR image being correctly classified, the model provided a participant-level accuracy of 99.11±0.55% and a stable image level accuracy of 97.45±0.63%. Conclusion: Deep learning methods, such as the proposed CNN model, can accurately predict persistent SAD based on MR images. Further replication of these findings will allow early initiation of adjunctive pharmacologic treatment in high-risk patients, along with CPAP, to improve quality of life and occupational fitness. Future augmentation of this approach with explainable artificial intelligence methods may elucidate the neuroanatomical areas underlying persistent SAD to provide mechanistic insights and novel therapeutic targets.

The Utility of Recording Submental Electrical Activity in Polysomnography.

Background Polysomnography is widely utilized as a diagnostic tool in sleep medicine. It is used to diagnose a variety of sleep disorders, including obstructive and central sleep apnea, periodic limb movements, parasomnia, and other sleep disorders. The objective of this study is to discuss the utility of recording submental electrical activity as a tool that provides the additional information needed in producing accurate results of a polysomnogram and emphasize the importance of including this recording in home sleep apnea tests. Methods A total of 1472 consecutive polysomnograms were used to assess the usefulness of submental activity in contributing to the accurate reporting of polysomnographic findings. These records were gathered over a one-year period at a major academic sleep center. Results Some of the observed electrical activities in the submental area are rare, although they may be important in confirming the findings of the polysomnogram or provide additional information. Adding an electroencephalographic channel and submental electromyographic recording is likely to increase the accuracy of home sleep apnea tests. Conclusions Recording of submental electrical activity is an integral part of polysomnography and provides more information than just recording the muscle tone of the submental area and is important in increasing the accuracy of home sleep apnea tests.

"Click"-capture, ring-opening metathesis polymerization (ROMP), release: facile triazolation utilizing ROMP-derived oligomeric phosphates.

Soluble, high-load ring-opening metathesis polymerization (ROMP)-derived oligomeric triazole phosphates (OTP) are reported for application as efficient triazolating reagents of nucleophilic species. Utilizing a "Click"-capture, ROMP, release protocol, the efficient and purification-free, direct triazolation of N-, O-, and S-nucleophilic species was successfully achieved. A variety of OTP derivatives were rapidly synthesized as free-flowing solids on a multigram scale from commercially available materials.

Zolpidem and amnestic sleep related eating disorder.

Nocturnal eating disorders are more common than previously thought. Sleep related eating disorder has been described in association with zolpidem. A review of the literature revealed the presence of 6 previously reported cases. In this presentation, the case of a 46-year-old female who developed sleep related eating disorder when she was treated with zolpidem for insomnia is reported. The patient recovered totally when zolpidem was stopped. Drug-induced sleep related eating disorders should be considered when evaluating patients with nocturnal eating.