Abstract
Objectives: In type III home polygraphy (HPG), Apnea Hypopnea Index (AHI) is calculated over the total recording time rather than the total sleep time (TST) as in polysomnography (PSG) and it is, therefore, underestimated. The aim of this study is to assess the impact of an automatic sleep/wake estimation algorithm on the AHI calculation.
Methods: The study included 176 patients admitted to the sleep laboratory for a PSG recording. The sleep/wake estimation algorithm used a single lead EEG (FP2-A1) associated to HPG signals (tracheal sounds, nasal airflow, actimetry, light, respiratory inductive plethysmography and suprasternal pressure). AHI using the enhanced HPG (AHIHPG+) scoring was compared with manual AASM scoring of both HPG (AHIHPG) and PSG (AHIPSG). Based on the AHI, patients were diagnosed with mild, moderate or severe sleep apnea.
Results: Cohen’s Kappa coefficient, sensitivity, specificity and the positive predictive value for the detection of wakefulness were 0.72, 78%, 94% and 78% respectively. TST estimation resulted in a better AHI assessment (Figure 1). In comparison to AHIPSG, a total of 54 patients were misclassified, using AHIHPG, as mild or moderate instead of moderate or severe. One third (18/54) of these patients would have been diagnosed properly based on AHIHPG+.
Conclusions: Enhanced HPG using single lead EEG is an efficient and cost-effective method for TST estimation and AHI calculation.
Footnotes
Cite this article as: European Respiratory Journal 2018 52: Suppl. 62, PA2247.
This is an ERS International Congress abstract. No full-text version is available. Further material to accompany this abstract may be available at www.ers-education.org (ERS member access only).
- Copyright ©the authors 2018
