Comparison of three actigraphic algorithms used to evaluate sleep in patients with obstructive sleep apnea

Actigraphy is a non-invasive and valid method to detect sleep/wake status. However, the technique lacks reliability in patients with sleep-disordered breathing and its results may depend on the algorithm employed.

We compared three currently used algorithms (the Cole-Kripke, Sadeh, and University of California San Diego [UCSD]) and determined which is the most reliable in patients with obstructive sleep apnea (OSA) assessing total sleep time. After identification of the most reliable algorithm, we compared total sleep time with the severity of obstructive sleep apnea.

The mean total sleep time was not significantly different from that yielded by polysomnography when the UCSD algorithm was employed (p = 0.798) and UCSD algorithm was associated with the smallest bias. The correlation levels (with polysomnographic data) were mild-to-modest when the results yielded by all algorithms were evaluated, but were highest when the UCSD algorithm was employed (UCSD, r = 0.498, p < 0.001; Cole-Kripke, r = 0.389, p < 0.01; Sadeh, r = 0.272, p = 0.057). Actigraphic measures of mean total sleep time underestimated sleep in patients with severe obstructive sleep apnea (apnea-hypopnea index [AHI] ≥30), and the correlation was low (r = 0.317, p = 0.116), but overestimated sleep, with high correlations, in patients with mild (5 ≤ AHI < 15) and moderate OSA (15 ≤ AHI < 30; r = 0.859, p < 0.001; r = 0.842, p < 0.001, respectively).

Among the three actigraphic algorithms tested in this study, sleep duration estimated by the UCSD algorithm was the most correlated with polysomnography data in an OSA population. However, none of them was reliable enough for estimating sleep time in patients with sleep-disordered breathing, especially in patients with severe OSA.