BACKGROUND AND PURPOSE: Micro-arousals (MA) are commonly considered as sleep components reflecting sleep fragmentation. However, their elucidation is time-consuming, with considerable inter-observer variability. The aim of our study was to investigate the usefulness of a sleep fragmentation index (SFI) to detect sleep disruption in a large sample of patients. PATIENTS AND METHODS: Five-hundred ninety-eight polysomnographic studies made in controls and patients were examined. The SFI was calculated as the total number of awakenings and sleep stage shifts divided by total sleep time. RESULTS: In the whole group a significant correlation was found between the SFI and the MA index (MAI) (P<0.001) with good agreement across a wide range of values. When patients were stratified according to final diagnosis a significant relation was noted for patients with insomnia (P<0.001), parasomnia (P<0.001), circadian schedule disorders (P<0.001) and sleep related breathing disorders (P< 0.001). Lower values were found in controls (P<0.01) and in patients with periodic limb movement disorder and/or restless legs syndrome (P<0.05). In 111 patients having two consecutive recording nights, a good reproducibility was present with no differences between nights (P=ns) and with significant correlation (P<0.001). CONCLUSIONS: The SFI seems to be an accurate, reproducible and easy method to detect sleep fragmentation in patients with sleep disorders. Further studies are needed to validate the usefulness of this tool in clinical practice.
BACKGROUND AND PURPOSE: Micro-arousals (MA) are commonly considered as sleep components reflecting sleep fragmentation. However, their elucidation is time-consuming, with considerable inter-observer variability. The aim of our study was to investigate the usefulness of a sleep fragmentation index (SFI) to detect sleep disruption in a large sample of patients. PATIENTS AND METHODS: Five-hundred ninety-eight polysomnographic studies made in controls and patients were examined. The SFI was calculated as the total number of awakenings and sleep stage shifts divided by total sleep time. RESULTS: In the whole group a significant correlation was found between the SFI and the MA index (MAI) (P<0.001) with good agreement across a wide range of values. When patients were stratified according to final diagnosis a significant relation was noted for patients with insomnia (P<0.001), parasomnia (P<0.001), circadian schedule disorders (P<0.001) and sleep related breathing disorders (P< 0.001). Lower values were found in controls (P<0.01) and in patients with periodic limb movement disorder and/or restless legs syndrome (P<0.05). In 111 patients having two consecutive recording nights, a good reproducibility was present with no differences between nights (P=ns) and with significant correlation (P<0.001). CONCLUSIONS: The SFI seems to be an accurate, reproducible and easy method to detect sleep fragmentation in patients with sleep disorders. Further studies are needed to validate the usefulness of this tool in clinical practice.
Authors: Benjamin Kye Jyn Tan; Yao Hao Teo; Nicole Kye Wen Tan; Dominic Wei Ting Yap; Raghav Sundar; Chi Hang Lee; Anna See; Song Tar Toh Journal: J Clin Sleep Med Date: 2022-05-01 Impact factor: 4.324