Simple four-variable screening tool for identification of patients with sleep-disordered breathing

To aid in the identification of patients with moderate-to-severe sleep-disordered breathing (SDB), we developed and validated a simple screening tool applicable to both clinical and community settings.

Logistic regression analysis was used to develop an integer-based risk scoring system. The participants in this derivation study included 132 patients visiting one of 2 hospitals in Japan, and 175 residents of a rural town. The participants in the present validation study included 308 employees of a company in Japan who were undergoing a health check.

The screening tool consisted of only 4 variables: sex, blood pressure level, body mass index, and self-reported snoring. This tool (screening score) gave an area under the receiver operating characteristic curve (ROC) of 0.90, sensitivity of 0.93, and specificity of 0.66, using a cutoff point of 11. Predicted and observed prevalence proportions in the validation dataset were in close agreement across the entire spectrum of risk scores. In the validation dataset, the area under the ROC for moderate-to-severe SDB and severe SDB were 0.78 and 0.85, respectively. The diagnostic performance of this tool did not significantly differ from that of previous, more complex tools.

These findings suggest that our screening scoring system is a valid tool for the identification and assessment of moderate-to-severe SDB. With knowledge of only 4 easily ascertainable variables, which are routinely checked during daily clinical practice or mass health screening, moderate-to-severe SDB can be easily detected in clinical and public health settings.