Electrocardiography Data Analysis in Sleep Disorders
| Status: | Completed |
|---|---|
| Conditions: | Insomnia Sleep Studies |
| Therapuetic Areas: | Psychiatry / Psychology |
| Healthy: | No |
| Age Range: | 18 - 95 |
| Updated: | 1/6/2019 |
| Start Date: | September 2013 |
| End Date: | December 2017 |
The objective of this study is to determine if a non-invasive technique, using an innovative
analysis of electrocardiogram (ECG) data, would allow for detection of respiratory events
during sleep and discrimination between central and obstructive apnea. Obstructive Sleep
Apnea (OSA) is the most common respiratory disturbance seen during sleep, with an estimated
prevalence of 10 % in the population and is strongly associated with the development of
cardiovascular disease. In patients with underlying cardiac disease, particularly in heart
failure (HF), central respiratory events such as Cheyne-Stokes Respiration (CSR) are often
seen during sleep. The presence of CSR is also associated with increased cardiovascular
morbidity and mortality. Currently, the identification and classification of sleep related
respiratory disturbances is performed during over-night sleep studies (polysomnography),
which are labor-intensive, time-consuming, expensive and difficult for patients. Thus, the
development of alternative techniques to assist in the identification of those events in the
outpatient setting is of marked importance for widespread screening of sleep apnea.
analysis of electrocardiogram (ECG) data, would allow for detection of respiratory events
during sleep and discrimination between central and obstructive apnea. Obstructive Sleep
Apnea (OSA) is the most common respiratory disturbance seen during sleep, with an estimated
prevalence of 10 % in the population and is strongly associated with the development of
cardiovascular disease. In patients with underlying cardiac disease, particularly in heart
failure (HF), central respiratory events such as Cheyne-Stokes Respiration (CSR) are often
seen during sleep. The presence of CSR is also associated with increased cardiovascular
morbidity and mortality. Currently, the identification and classification of sleep related
respiratory disturbances is performed during over-night sleep studies (polysomnography),
which are labor-intensive, time-consuming, expensive and difficult for patients. Thus, the
development of alternative techniques to assist in the identification of those events in the
outpatient setting is of marked importance for widespread screening of sleep apnea.
This study aims to use novel analyses of electrocardiogram data to detect the presence and
type of respiratory event observed in patients during sleep. Our specific aims include:
determining the accuracy of using a non-invasive electrocardiogram (ECG) to detect sleep
apnea and to distinguish between obstructive sleep apnea (OSA) and Cheyne-Stokes Respiration
(CSR). For this investigator-initiated study, data from approximately 400 consecutive
patients presenting to the Weill Cornell Center for Sleep Medicine for polysomnography will
be collected. A sample size of 45 subjects in each group will be needed to quantify mean
amplitude change in the ECG derived respiratory signal. Study procedures are outlined below.
Standard and novel, research measurements from the ECG will be correlated with findings from
polysomnography and used to assess the presence and severity of a variety of ECG-based
measures of cardiovascular disease, such as left ventricular hypertrophy and prior Q-wave
myocardial infarction. Subjects will also have to complete a Questionnaire prior to their ECG
at their visit.
Detailed procedures:
1. Subjects will be asked to complete a brief questionnaire (see attached). This
questionnaire will ask questions relating to subjects' sleep patterns, etc. Potential
risks include possible discomfort while completing the questionnaire.
2. Continuous 12-lead ECG recordings, using torso-located electrodes, will be obtained with
Mortara Instrument H12+ recorders. An MTA Agreement has been established for the use of
this equipment for the duration of this study. Electrocardiograms will be obtained in
standard clinical fashion using GE Medical Systems equipment. Patients will be asked to
lie in the supine position and 10 recording electrodes will be applied. With the patient
lying quietly, a 10 second digital ECG will be recorded and then downloaded via analog
modem to the MUSE ECG analysis and storage system at New York Presbyterian Hospital
where it will be stored on a dedicated site of our password protected MUSE server. ECG
information:12-lead ECGs will be downloaded from the MUSE system to a secure network
drive and then copied to the hard drive of a password protected computer where they will
be batch-analyzed using an ECG research analysis program, Magellan, provided by GE
Medical Systems. Magellan will generate a series of measurements from each ECG and will
then export these measurements to an Excel file which will be converted to SPSS files
for data analysis. Deidentified ECG data may be downloaded to the Electrocardiography
data center and transferred using a secure file transfer system, such as Cornell's file
transfer website, to an outside company (Mortara, Inc.) for further analysis as needed.
3. Standard polysomnography will be performed for 12 hours at approximately the patients
regular sleep time. Sleep data will be recorded in a digitized system and analyzed using
Grass Twin software ® (Middleton, WI) for the determination and classification of
respiratory events and other sleep related parameters. The Apnea-Hypopnea Index (AHI)
will be calculated by computing the average number of obstructive apneas plus
obstructive hypopneas per hour of sleep. Obstructive sleep apnea (OSA) is here defined
by an AHI ≥5. Intermittent hypoxemia (IH) will be determined by the number of
periods ≥6 sec with SaO2 drops ≥4%. Cheyne-Stokes Respiration will be
determined by the typical crescendo-decrescendo pattern on the respiratory flow signal,
chest and thoracic impedance, using standard criteria. Total duration of CSR will be
calculated for the determination of the % of sleep time on CSR. Data regarding
percentage of sleep time at SaO2 ≤90% (%TST<90) and lowest saturation level
(LowSaO2) will also be recorded.
Upon completion of data attainment some de-identified data will be remote analyzed.
type of respiratory event observed in patients during sleep. Our specific aims include:
determining the accuracy of using a non-invasive electrocardiogram (ECG) to detect sleep
apnea and to distinguish between obstructive sleep apnea (OSA) and Cheyne-Stokes Respiration
(CSR). For this investigator-initiated study, data from approximately 400 consecutive
patients presenting to the Weill Cornell Center for Sleep Medicine for polysomnography will
be collected. A sample size of 45 subjects in each group will be needed to quantify mean
amplitude change in the ECG derived respiratory signal. Study procedures are outlined below.
Standard and novel, research measurements from the ECG will be correlated with findings from
polysomnography and used to assess the presence and severity of a variety of ECG-based
measures of cardiovascular disease, such as left ventricular hypertrophy and prior Q-wave
myocardial infarction. Subjects will also have to complete a Questionnaire prior to their ECG
at their visit.
Detailed procedures:
1. Subjects will be asked to complete a brief questionnaire (see attached). This
questionnaire will ask questions relating to subjects' sleep patterns, etc. Potential
risks include possible discomfort while completing the questionnaire.
2. Continuous 12-lead ECG recordings, using torso-located electrodes, will be obtained with
Mortara Instrument H12+ recorders. An MTA Agreement has been established for the use of
this equipment for the duration of this study. Electrocardiograms will be obtained in
standard clinical fashion using GE Medical Systems equipment. Patients will be asked to
lie in the supine position and 10 recording electrodes will be applied. With the patient
lying quietly, a 10 second digital ECG will be recorded and then downloaded via analog
modem to the MUSE ECG analysis and storage system at New York Presbyterian Hospital
where it will be stored on a dedicated site of our password protected MUSE server. ECG
information:12-lead ECGs will be downloaded from the MUSE system to a secure network
drive and then copied to the hard drive of a password protected computer where they will
be batch-analyzed using an ECG research analysis program, Magellan, provided by GE
Medical Systems. Magellan will generate a series of measurements from each ECG and will
then export these measurements to an Excel file which will be converted to SPSS files
for data analysis. Deidentified ECG data may be downloaded to the Electrocardiography
data center and transferred using a secure file transfer system, such as Cornell's file
transfer website, to an outside company (Mortara, Inc.) for further analysis as needed.
3. Standard polysomnography will be performed for 12 hours at approximately the patients
regular sleep time. Sleep data will be recorded in a digitized system and analyzed using
Grass Twin software ® (Middleton, WI) for the determination and classification of
respiratory events and other sleep related parameters. The Apnea-Hypopnea Index (AHI)
will be calculated by computing the average number of obstructive apneas plus
obstructive hypopneas per hour of sleep. Obstructive sleep apnea (OSA) is here defined
by an AHI ≥5. Intermittent hypoxemia (IH) will be determined by the number of
periods ≥6 sec with SaO2 drops ≥4%. Cheyne-Stokes Respiration will be
determined by the typical crescendo-decrescendo pattern on the respiratory flow signal,
chest and thoracic impedance, using standard criteria. Total duration of CSR will be
calculated for the determination of the % of sleep time on CSR. Data regarding
percentage of sleep time at SaO2 ≤90% (%TST<90) and lowest saturation level
(LowSaO2) will also be recorded.
Upon completion of data attainment some de-identified data will be remote analyzed.
Inclusion Criteria:
- Patients presenting to the WCMC Sleep Center for polysomnography
Exclusion Criteria:
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