OBJECTIVE: To compare periodic leg movement (PLM) counts obtained with polysomnography (PSG) to those obtained from actigraphy with two devices (Actiwatch and PAM-RL). METHODS: Twenty-four patients underwent full night actigraphy with Actiwatch from both legs and simultaneous PSG. Out of these patients, 10 had additional actigraphy with PAM-RL. Bilateral and unilateral PLM indices (PLMI) for both actigraphs were calculated for time in bed and compared to polysomnographic PLMI. Additionally, a comparison between the two different actigraphs was performed. RESULTS: PLMI obtained with Actiwatch were significantly lower than those obtained with PSG (21.2+/-25.6/h versus 34.4+/-30.7/h; p<0.001), whereas the PLMI from PAM-RL were significantly higher than in PSG (63.6+/-39.3/h versus 37.0+/-33.5/h; p=0.009). In direct comparison, Actiwatch gave significantly lower PLMI than the PAM-RL (p=0.005). The correlations between Actiwatch and PSG (rho=0.835, p<0.001), PAM-RL and PSG (rho=0.939, p<0.001), and Actiwatch and PAM-RL (rho=0.915, p<0.001) were significant. Unilateral actigraphy compared to standard PSG gave less consistent findings. When comparing different settings of the PAM-RL, manual threshold setting resulted in PLMI that were no longer different from PSG (p=0.074), in contrast to the default threshold setting. CONCLUSIONS: The Actiwatch underestimated and the PAM-RL overestimated PLMI compared to PSG. Whereas PLMI obtained with two actigraphs and PSG were highly correlated, they differed in mean values. Therefore, PSG, actigraphy and also the different actigraphs cannot be interchanged in longitudinal studies, and actigraphy should not be used for diagnostic decision making based on PLM indices. The best approximation to PSG PLMI was achieved by using manual threshold setting with the PAM-RL.
OBJECTIVE: To compare periodic leg movement (PLM) counts obtained with polysomnography (PSG) to those obtained from actigraphy with two devices (Actiwatch and PAM-RL). METHODS: Twenty-four patients underwent full night actigraphy with Actiwatch from both legs and simultaneous PSG. Out of these patients, 10 had additional actigraphy with PAM-RL. Bilateral and unilateral PLM indices (PLMI) for both actigraphs were calculated for time in bed and compared to polysomnographic PLMI. Additionally, a comparison between the two different actigraphs was performed. RESULTS: PLMI obtained with Actiwatch were significantly lower than those obtained with PSG (21.2+/-25.6/h versus 34.4+/-30.7/h; p<0.001), whereas the PLMI from PAM-RL were significantly higher than in PSG (63.6+/-39.3/h versus 37.0+/-33.5/h; p=0.009). In direct comparison, Actiwatch gave significantly lower PLMI than the PAM-RL (p=0.005). The correlations between Actiwatch and PSG (rho=0.835, p<0.001), PAM-RL and PSG (rho=0.939, p<0.001), and Actiwatch and PAM-RL (rho=0.915, p<0.001) were significant. Unilateral actigraphy compared to standard PSG gave less consistent findings. When comparing different settings of the PAM-RL, manual threshold setting resulted in PLMI that were no longer different from PSG (p=0.074), in contrast to the default threshold setting. CONCLUSIONS: The Actiwatch underestimated and the PAM-RL overestimated PLMI compared to PSG. Whereas PLMI obtained with two actigraphs and PSG were highly correlated, they differed in mean values. Therefore, PSG, actigraphy and also the different actigraphs cannot be interchanged in longitudinal studies, and actigraphy should not be used for diagnostic decision making based on PLM indices. The best approximation to PSG PLMI was achieved by using manual threshold setting with the PAM-RL.
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