No abstract

Background: Obstructive sleep apnea (OSA) has a high prevalence, with an estimated 425 million adults with apnea hypopnea index (AHI) of ≥15 events/hour, and is significantly underdiagnosed. This presents a significant pain point for both the sufferers, and for healthcare systems, particularly in a post COVID-19 pandemic world. As such, it presents an opportunity for new technologies that can enable screening in both developing and developed countries. In this work, the performance of a non-contact OSA screener App that can run on both Apple and Android smartphones is presented. Methods: The subtle breathing patterns of a person in bed can be measured via a smartphone using the "Firefly" app technology platform [and underpinning software development kit (SDK)], which utilizes advanced digital signal processing (DSP) technology and artificial intelligence (AI) algorithms to identify detailed sleep stages, respiration rate, snoring, and OSA patterns. The smartphone is simply placed adjacent to the subject, such as on a bedside table, night stand or shelf, during the sleep session. The system was trained on a set of 128 overnights recorded at a sleep laboratory, where volunteers underwent simultaneous full polysomnography (PSG), and "Firefly" smartphone app analysis. A separate independent test set of 120 recordings was collected across a range of Apple iOS and Android smartphones, and withheld for performance evaluation by a different team. An operating point tuned for mid-sensitivity (i.e., balancing sensitivity and specificity) was chosen for the screener. Results:The performance on the test set is comparable to ambulatory OSA screeners, and other smartphone screening apps, with a sensitivity of 88.3% and specificity of 80.0% [with receiver operating characteristic (ROC) area under the curve (AUC) of 0.92], for a clinical threshold for the AHI of ≥15 events/ hour of detected sleep time. Conclusions: The "Firefly" app based sensing technology offers the potential to significantly lower the barrier of entry to OSA screening, as no hardware (other than the user's personal smartphone) is required.Additionally, multi-night analysis is possible in the home environment, without requiring the wearing of a portable PSG or other home sleep test (HST).

Patient's quality of life scores correlated directly with their injury severity and pre-existing conditions. They were not negatively affected by IEF treatment itself. High quality of life scores (non-physical) were achieved with IEF treatment.

Objective: To examine the conditions leading to sideswipe injury of the upper limb in motor vehicle accidents and to highlight the severity of these injuries. Design and setting: Prospective study of upper‐limb sideswipe injuries in patients admitted to Royal Perth Hospital, Western Australia, between August 2003 and January 2005. Participants: Eleven patients sustaining sideswipe injuries to the upper limb. Main outcome measures: Accident pattern, type of injury, surgical management, complications, and functional and employment implications. Results: Ten patients required open reduction and internal fixation for open fractures of the humerus, ulna and radius, and nine underwent additional surgical procedures including nerve, artery and tendon repair, and free flaps and split‐skin grafting. The injury severity scores ranged from 9 to 25. The severity of injuries led to extensive functional deficits in eight patients, affecting employment prospects in seven. Conclusion: Appropriate educational programs, legislation and improvements in traffic conditions, especially in rural areas, as well as changes in current car design, could contribute to preventing these devastating and complex injuries.

This study demonstrates a high performance of IF in the treatment of severe tibial fractures with compromised soft tissue where more standard forms of treatment are contraindicated.