Continuous positive airway pressure (CPAP) is highly effective in treating sleep-disordered breathing (SDB). However, unlike surgical interventions, this treatment modality relies heavily on patient acceptance and adherence. The current definition of adherence is largely arbitrary and is mainly used by third-party payers to determine CPAP reimbursement but CPAP adherence remains sub-optimal. Strategies to augment adherence, especially early in the course of a CPAP trial, are needed in the management of SDB. An understanding of the basis for observed differences in CPAP and oral appliance (OA) use is necessary in developing these strategies, but to date no single factor has been consistently identified. Consequently, a multidimensional approach using educational, behavioural, technological and potentially pharmacological strategies to target (i) disease characteristics, (ii) patient characteristics including psychosocial factors, (iii) treatment protocols and (iv) technological devices and side effects that may influence adherence, is likely required to augment the complex behaviour of CPAP and OA use. In the near future, we envision a personalized medicine approach to determine the risk of non-adherence and set individualized adherence goals aimed at treating specific symptoms (e.g. excessive daytime sleepiness) and reducing the risk of patient-specific SDB consequences (e.g. atherosclerosis). Resources for interventions to improve adherence such as educational programmes and telemedicine encounters could then be more efficiently allocated.
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http://dx.doi.org/10.1111/resp.13589 | DOI Listing |
Adv Sci (Weinh)
January 2025
The Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Xingangzhong Road 466, Guangzhou, 518037, P. R. China.
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View Article and Find Full Text PDFEnviron Sci Technol
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School of Ecology and Environmental Science, Yunnan University, Kunming 650504, China.
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January 2025
Department of Otorhinolaryngology, University Medical Center of the Johannes Gutenberg-University Mainz, Langenbeckstraße 1, 55131, Mainz, Germany.
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December 2024
Department of Speech Therapy, School of Health Sciences, University of Ioannina, 455 00 Ioannina, Greece.
This study presents a comprehensive investigation into the correlation between Rare Diseases and Syndromes (RDS) and the dysphagic disorders manifested during childhood and adulthood in affected patients. Dysphagia is characterized by difficulty or an inability to swallow food of any consistency, as well as saliva or medications, from the oral cavity to the stomach. RDS often present with complex and heterogeneous clinical manifestations, making it challenging to develop standardized diagnostic and therapeutic approaches.
View Article and Find Full Text PDFNeuroradiol J
January 2025
Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY, USA.
This study evaluates the efficacy of deep learning models in identifying infarct tissue on computed tomography perfusion (CTP) scans from patients with acute ischemic stroke due to large vessel occlusion, specifically addressing the potential influence of varying noise reduction techniques implemented by different vendors. We analyzed CTP scans from 60 patients who underwent mechanical thrombectomy achieving a modified thrombolysis in cerebral infarction (mTICI) score of 2c or 3, ensuring minimal changes in the infarct core between the initial CTP and follow-up MR imaging. Noise reduction techniques, including principal component analysis (PCA), wavelet, non-local means (NLM), and a no denoising approach, were employed to create hemodynamic parameter maps.
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