Accuracy of ECG-based screening for sleep-disordered breathing: A survey of all male workers in a transport company

Junichiro Hayano, Teruomi Tsukahara, Eiichi Watanabe, Fumihiko Sasaki, Kiyohiro Kawai, Hiroki Sakakibara, Itsuo Kodama, Tetsuo Nomiyama, Keisaku Fujimoto

Research output: Contribution to journalReview article

8 Citations (Scopus)

Abstract

Purpose: Sleep-disordered breathing (SDB) is associated with increased risk for cardiovascular morbidity and mortality and for sleepiness-related accidents, but >75 % of the patients remain undiagnosed. We sought to determine the diagnostic accuracy of ECG-based detection of SDB when used for population-based screening. Methods: All male workers, mostly truck drivers, of a transport company (n = 165; age, 43 ± 12 years) underwent standard attended overnight polysomnography. Cyclic variation of heart rate (CVHR), a characteristic pattern of heart rate associated with SDB, was detected from single-lead ECG signals during the polysomnography by a newly developed automated algorithm of autocorrelated wave detection with adaptive threshold (ACAT). Results: Among 165 subjects, the apnea-hypopnea index (AHI) was ≥5 in 62 (38 %), ≥15 in 26 (16 %), and ≥30 in 16 (10 %). The number of CVHR per hour (CVHR index) closely correlated with AHI [r = 0.868 (95 % CI, 0.825-0.901)]. The areas under the receiver operating characteristic curves for detecting subjects with AHI ≥5, ≥15, and ≥30 were 0.796 (95 % CI, 0.727-0.855), 0.974 (0.937-0.993), and 0.997 (0.971-0.999), respectively. With a predetermined criterion of CVHR index ≥15, subjects with AHI ≥15 were identified with 88 % sensitivity and 97 % specificity (likelihood ratios for positive and negative test, 30.7 and 0.12). The classification performance was retained in subgroups of subjects with obesity, hypertension, diabetes mellitus, dyslipidemia, and decreased autonomic function. Conclusions: The CVHR obtained by the ACAT algorithm may provide a useful marker for screening for moderate-to-severe SDB among apparently healthy male workers.

Original languageEnglish
Pages (from-to)243-251
Number of pages9
JournalSleep and Breathing
Volume17
Issue number1
DOIs
Publication statusPublished - 01-03-2013

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Sleep Apnea Syndromes
Electrocardiography
Heart Rate
Apnea
Polysomnography
Motor Vehicles
Dyslipidemias
ROC Curve
Accidents
Surveys and Questionnaires
Diabetes Mellitus
Obesity
Hypertension
Morbidity
Sensitivity and Specificity
Mortality
Population

All Science Journal Classification (ASJC) codes

  • Otorhinolaryngology
  • Clinical Neurology

Cite this

Hayano, Junichiro ; Tsukahara, Teruomi ; Watanabe, Eiichi ; Sasaki, Fumihiko ; Kawai, Kiyohiro ; Sakakibara, Hiroki ; Kodama, Itsuo ; Nomiyama, Tetsuo ; Fujimoto, Keisaku. / Accuracy of ECG-based screening for sleep-disordered breathing : A survey of all male workers in a transport company. In: Sleep and Breathing. 2013 ; Vol. 17, No. 1. pp. 243-251.
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title = "Accuracy of ECG-based screening for sleep-disordered breathing: A survey of all male workers in a transport company",
abstract = "Purpose: Sleep-disordered breathing (SDB) is associated with increased risk for cardiovascular morbidity and mortality and for sleepiness-related accidents, but >75 {\%} of the patients remain undiagnosed. We sought to determine the diagnostic accuracy of ECG-based detection of SDB when used for population-based screening. Methods: All male workers, mostly truck drivers, of a transport company (n = 165; age, 43 ± 12 years) underwent standard attended overnight polysomnography. Cyclic variation of heart rate (CVHR), a characteristic pattern of heart rate associated with SDB, was detected from single-lead ECG signals during the polysomnography by a newly developed automated algorithm of autocorrelated wave detection with adaptive threshold (ACAT). Results: Among 165 subjects, the apnea-hypopnea index (AHI) was ≥5 in 62 (38 {\%}), ≥15 in 26 (16 {\%}), and ≥30 in 16 (10 {\%}). The number of CVHR per hour (CVHR index) closely correlated with AHI [r = 0.868 (95 {\%} CI, 0.825-0.901)]. The areas under the receiver operating characteristic curves for detecting subjects with AHI ≥5, ≥15, and ≥30 were 0.796 (95 {\%} CI, 0.727-0.855), 0.974 (0.937-0.993), and 0.997 (0.971-0.999), respectively. With a predetermined criterion of CVHR index ≥15, subjects with AHI ≥15 were identified with 88 {\%} sensitivity and 97 {\%} specificity (likelihood ratios for positive and negative test, 30.7 and 0.12). The classification performance was retained in subgroups of subjects with obesity, hypertension, diabetes mellitus, dyslipidemia, and decreased autonomic function. Conclusions: The CVHR obtained by the ACAT algorithm may provide a useful marker for screening for moderate-to-severe SDB among apparently healthy male workers.",
author = "Junichiro Hayano and Teruomi Tsukahara and Eiichi Watanabe and Fumihiko Sasaki and Kiyohiro Kawai and Hiroki Sakakibara and Itsuo Kodama and Tetsuo Nomiyama and Keisaku Fujimoto",
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Hayano, J, Tsukahara, T, Watanabe, E, Sasaki, F, Kawai, K, Sakakibara, H, Kodama, I, Nomiyama, T & Fujimoto, K 2013, 'Accuracy of ECG-based screening for sleep-disordered breathing: A survey of all male workers in a transport company', Sleep and Breathing, vol. 17, no. 1, pp. 243-251. https://doi.org/10.1007/s11325-012-0681-7

Accuracy of ECG-based screening for sleep-disordered breathing : A survey of all male workers in a transport company. / Hayano, Junichiro; Tsukahara, Teruomi; Watanabe, Eiichi; Sasaki, Fumihiko; Kawai, Kiyohiro; Sakakibara, Hiroki; Kodama, Itsuo; Nomiyama, Tetsuo; Fujimoto, Keisaku.

In: Sleep and Breathing, Vol. 17, No. 1, 01.03.2013, p. 243-251.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Accuracy of ECG-based screening for sleep-disordered breathing

T2 - A survey of all male workers in a transport company

AU - Hayano, Junichiro

AU - Tsukahara, Teruomi

AU - Watanabe, Eiichi

AU - Sasaki, Fumihiko

AU - Kawai, Kiyohiro

AU - Sakakibara, Hiroki

AU - Kodama, Itsuo

AU - Nomiyama, Tetsuo

AU - Fujimoto, Keisaku

PY - 2013/3/1

Y1 - 2013/3/1

N2 - Purpose: Sleep-disordered breathing (SDB) is associated with increased risk for cardiovascular morbidity and mortality and for sleepiness-related accidents, but >75 % of the patients remain undiagnosed. We sought to determine the diagnostic accuracy of ECG-based detection of SDB when used for population-based screening. Methods: All male workers, mostly truck drivers, of a transport company (n = 165; age, 43 ± 12 years) underwent standard attended overnight polysomnography. Cyclic variation of heart rate (CVHR), a characteristic pattern of heart rate associated with SDB, was detected from single-lead ECG signals during the polysomnography by a newly developed automated algorithm of autocorrelated wave detection with adaptive threshold (ACAT). Results: Among 165 subjects, the apnea-hypopnea index (AHI) was ≥5 in 62 (38 %), ≥15 in 26 (16 %), and ≥30 in 16 (10 %). The number of CVHR per hour (CVHR index) closely correlated with AHI [r = 0.868 (95 % CI, 0.825-0.901)]. The areas under the receiver operating characteristic curves for detecting subjects with AHI ≥5, ≥15, and ≥30 were 0.796 (95 % CI, 0.727-0.855), 0.974 (0.937-0.993), and 0.997 (0.971-0.999), respectively. With a predetermined criterion of CVHR index ≥15, subjects with AHI ≥15 were identified with 88 % sensitivity and 97 % specificity (likelihood ratios for positive and negative test, 30.7 and 0.12). The classification performance was retained in subgroups of subjects with obesity, hypertension, diabetes mellitus, dyslipidemia, and decreased autonomic function. Conclusions: The CVHR obtained by the ACAT algorithm may provide a useful marker for screening for moderate-to-severe SDB among apparently healthy male workers.

AB - Purpose: Sleep-disordered breathing (SDB) is associated with increased risk for cardiovascular morbidity and mortality and for sleepiness-related accidents, but >75 % of the patients remain undiagnosed. We sought to determine the diagnostic accuracy of ECG-based detection of SDB when used for population-based screening. Methods: All male workers, mostly truck drivers, of a transport company (n = 165; age, 43 ± 12 years) underwent standard attended overnight polysomnography. Cyclic variation of heart rate (CVHR), a characteristic pattern of heart rate associated with SDB, was detected from single-lead ECG signals during the polysomnography by a newly developed automated algorithm of autocorrelated wave detection with adaptive threshold (ACAT). Results: Among 165 subjects, the apnea-hypopnea index (AHI) was ≥5 in 62 (38 %), ≥15 in 26 (16 %), and ≥30 in 16 (10 %). The number of CVHR per hour (CVHR index) closely correlated with AHI [r = 0.868 (95 % CI, 0.825-0.901)]. The areas under the receiver operating characteristic curves for detecting subjects with AHI ≥5, ≥15, and ≥30 were 0.796 (95 % CI, 0.727-0.855), 0.974 (0.937-0.993), and 0.997 (0.971-0.999), respectively. With a predetermined criterion of CVHR index ≥15, subjects with AHI ≥15 were identified with 88 % sensitivity and 97 % specificity (likelihood ratios for positive and negative test, 30.7 and 0.12). The classification performance was retained in subgroups of subjects with obesity, hypertension, diabetes mellitus, dyslipidemia, and decreased autonomic function. Conclusions: The CVHR obtained by the ACAT algorithm may provide a useful marker for screening for moderate-to-severe SDB among apparently healthy male workers.

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JO - Sleep and Breathing

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