Abstract:
BACKGROUND AND PURPOSE:Present methods to extract respiratory myogram interference (RMI) from the Holter-ECG and assess effect of supraventricular arrhythmias (SVAs) onto ECG-based detection of sleep-related breathing disorders (SRBDs) and AHI estimation. METHODS:RMI was quantified as residual energy after ECG cancellation or high-pass filtering for different windowing constellations. In 140 cases without (SET_A) and 10 cases with persistent SVAs (SET_B), respiratory polysomnogram annotations served as reference for SRDB detection from Holter-ECGs. We applied our previously published method to identify SRDBs in 1-min epochs and estimate the AHI based on joint modulations in RMI and QRS-area. RESULTS:Sensitivity and specificity of 0.855/0.860 in SET_A dropped to 0.831/0.75 in SET_B. A significantly higher number of wake events in SET_B likely contribute to the asymmetric decrease and is consistent with a tendency to overestimate the AHI. CONCLUSIONS:Despite reduced accuracy, RMI and QRS-area appear relatively robust against SVA and promise Holter-based detection at least of medium to severe SRBDs also in patients with SVAs.
journal_name
J Electrocardioljournal_title
Journal of electrocardiologyauthors
Maier C,Dickhaus Hdoi
10.1016/j.jelectrocard.2014.07.017subject
Has Abstractpub_date
2014-11-01 00:00:00pages
826-30issue
6eissn
0022-0736issn
1532-8430pii
S0022-0736(14)00291-Xjournal_volume
47pub_type
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