An emerging technology for the identification and characterization of postural-dependent obstructive sleep apnea
| Autor: | Peter R. Eastwood, Craig Freakley, V. Kurup, Jennifer H. Walsh, A. Tate, D. Mann, Philip I. Terrill, Bindiya Shenoy |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Pulmonary and Respiratory Medicine
medicine.medical_specialty Technology Polysomnography Posture 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation medicine Supine Position Humans Emerging Technologies Retrospective Studies Sleep Apnea Obstructive medicine.diagnostic_test business.industry Body posture medicine.disease nervous system diseases respiratory tract diseases Obstructive sleep apnea Neurology Identification (biology) Neurology (clinical) business 030217 neurology & neurosurgery |
| Zdroj: | J Clin Sleep Med |
| Popis: | STUDY OBJECTIVES: Body posture has a significant impact on the presence and severity of obstructive sleep apnea (OSA). The majority of polysomnography (PSG) systems have the capacity to categorize body (torso) posture as supine, left-lateral, right-lateral or prone, each within a 90-degree range. However, such broad categorization may limit the identification of subtle relationships between posture and OSA severity. The aim of this study was to quantify sleeping posture as a continuous variable; and to develop an intuitive tool for visualizing the relationship between body posture and OSA severity. METHODS: A customized triaxial accelerometer-based posture sensor which quantifies torso posture as a continuous variable was developed. 38 participants attending the sleep laboratory for suspected OSA were recruited. Each participant underwent a diagnostic PSG with an additional customized posture sensor securely attached to the sternum. Individual data were presented using a novel circular histogram-based visualization which displays sleeping position and position-specific OSA severity. RESULTS: Acceptable measurements were obtained in 21 participants. The mean ± standard deviation percentage of total sleep time spent within ± 15 degrees of the center of supine, left-lateral, right-lateral and prone was 59.7 ± 26.0%. A further 40.3 ± 26.0% of sleep time was spent in intermediate positions outside these traditional categorizations. The novel visualization revealed a wide variety of positional OSA phenotypes. CONCLUSIONS: Quantification of torso posture as a continuous variable and analysis of these data using a novel visualization enables the identification of subtle relationships between body posture and OSA severity that are not apparent using standard clinical sensors and summary statistics. CITATION: Tate A, Walsh J, Kurup V, Shenoy B, Mann D, Freakley C, Eastwood P, Terrill P. An emerging technology for the identification and characterization of postural-dependent obstructive sleep apnea. J Clin Sleep Med. 2020;16(2):309–318. |
| Databáze: | OpenAIRE |
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