Respiratory investigation · 2025
Predicting sleep disordered breathing in middle-aged Japanese office workers: A simple and effective screening tool.
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Yamasawa Wakako, Tanabe Akiko, Asano Koichiro, Sato Yasunori, Matsushita Hiromichi, Fukunaga Koichi
Аннотация
BACKGROUND: Sleep Disordered Breathing (SDB) is a common yet underdiagnosed condition, as many afflicted individuals are unaware of the condition. It is a major contributor to metabolic syndrome, sudden death, and deteriorating overall health, making early detection crucial, especially in populations such as Japanese office workers in whom symptoms may not be evident. This study aimed to fill the critical gap in SDB detection by investigating its prevalence among Japanese office workers unaware of any SDB symptoms and by and developing a straightforward, effective screening tool that can be integrated into routine health examinations.
METHODS: A total of 518 male office workers underwent a sleep monitoring test along with a comprehensive questionnaire assessing lifestyle, comorbidities, and sleep quality. Participants were divided into derivation and validation cohorts to develop and test, respectively, an SDB prediction score.
RESULTS: In this study, 149 (28.7 %) patients had a respiratory disturbance index ≥15 and moderate or severe SDB. The developed prediction model demonstrated a high sensitivity of 91.5 % and a specificity of 49.4 %, making it a powerful tool for early detection of SDB requiring treatment.
CONCLUSIONS: This study presents a convenient screening tool that could revolutionize SDB detection among Japanese office workers, leading to earlier interventions and potentially reducing the burden of related health complications. This tool holds significant promise for incorporation into standard health examinations, offering a proactive approach to managing SDB.
METHODS: A total of 518 male office workers underwent a sleep monitoring test along with a comprehensive questionnaire assessing lifestyle, comorbidities, and sleep quality. Participants were divided into derivation and validation cohorts to develop and test, respectively, an SDB prediction score.
RESULTS: In this study, 149 (28.7 %) patients had a respiratory disturbance index ≥15 and moderate or severe SDB. The developed prediction model demonstrated a high sensitivity of 91.5 % and a specificity of 49.4 %, making it a powerful tool for early detection of SDB requiring treatment.
CONCLUSIONS: This study presents a convenient screening tool that could revolutionize SDB detection among Japanese office workers, leading to earlier interventions and potentially reducing the burden of related health complications. This tool holds significant promise for incorporation into standard health examinations, offering a proactive approach to managing SDB.