An Assessment of Sleep Quality Using Validation in Patients Suspected with Sleep Disordered Breathing

Authors:
Baker D, Schramm PJ, Neville AN, Thomas R., Madison S

Reference:
SLEEP 2009;32:A82

Objectives:
To assess automated sleep quality analysis software using CPC from one ECG channel polysomnography from 69 patients suspected of sleep disordered breathing (SDB).

Conclusions:
The RemLogic CPC analyzer accurately reproduces sleep quality data obtained from patient results collected at Beth Israel Deaconess Hospital and is comparable to the work of Thomas et al. 2007

Practical Significance:
The RemLogic CPC tool is validated against the CPC algorithm created by Dr. Robert Thomas of Beth Israel University, a teaching school of Harvard University, as seen in the 2007 study differentiating obstructive from central and complex sleep apnea using an automated electrocardiogram-based method.

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An Early Indicator of Complex Sleep Apnea

Authors:
Schramm PJ.

Reference:
Advance for Respiratory Care and Sleep Medicine June 21, 2010

Objectives:
Demonstration of the impact on a Complex Sleep Apnea patient’s sleep quality with CPAP versus ASV using CPC to detect stable and unstable sleep.

Conclusions:
CPC variables indicated that the patient’s sleep quality had improved objectively. Subjectively, the patient reported his sleep more restful when using the combination of ASV at 9cm H2O and added dead space compared to CPAP.

Practical Significance:
This study highlights that the presence of e-LFCNB can help identify complex sleep apnea both before and after initiation of PAP therapy. A second CPC study following the application of ASV with dead space showed improved quality of sleep in the form of increased HFC, which corresponded well with the patients subjective findings.

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An electrocardiogram-based analysis evaluating sleep quality in patients with obstructive sleep apnea.

Authors:
Harrington J, Schramm PJ, Davies CR, Lee-Chiong TL Jr.

Reference:
Sleep Breath. 2013 Sep;17(3):1071-8.

Objectives:
The study compares polysomnography (PSG) and cardiopulmonary coupling (CPC) sleep quality variables in patients with (1) obstructive sleep apnea (OSA) and (2) successful and unsuccessful continuous positive airway pressure (CPAP) response.

Conclusions:
Tests differentiated no and moderate to severe OSA groups by REM %, HFC, VLFC, and LFC/HFC ratio variables. The successful CPAP therapy group had more HFC, less LFC, and e-LFCBB compared to the unsuccessful CPAP therapy group. HFC ≥ 50 % showed high sensitivity (77.8 %) and specificity (88.9 %) in identifying successful CPAP therapy.

Practical Significance:
The results support the use of the SleepImage system to investigate and objectively measure sleep quality in patients complaining of a sleep disorder.

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Cardiopulmonary Coupling Measures Correlate to Standard Sleep Variables in a Random Clinical Sample of Patients Suspected with Sleep Disordered Breathing (SDB)

Authors:
Schramm PJ, Neville AG, Madison S, Thomas RJ, Baker DN

Reference:
SLEEP Abstract Supplements 2009;32:A189 Number 0575

Objectives:
To determine the correlation of Cardiopulmonary variables to standard sleep variables in a random clinical sample.

Conclusions:
The RemLogic CPC analysis variables correlate with standard sleep metrics in a clinical population suspected with OSA, and seem to detect complementary aspects of sleep physiology.

Practical Significance:
Some of these variables were reported in subjects selected from the Sleep Heart Health study in addition to CPC measures. CPC variables compliment various aspects of sleep physiology obtained using standard sleep metrics

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Differentiating Obstructive from Central & Complex Sleep Apnea Using an Automated Electrocardiogram-based Method

Authors:
Thomas RJ, Mietus JE, Peng CK, Gilmartin G, Daly RW, Goldberger AL, Gottlie DJ.

Reference:
Sleep. 2007 Dec;30(12):1756-69.

Objectives:
Complex sleep apnea is defined as sleep disordered breathing secondary to simultaneous upper airway obstruction and respiratory control dysfunction. The objective of this study was to assess the utility of an electrocardiogram (ECG) based CPC technique to distinguish obstructive from central or complex sleep apnea

Conclusions:
ECG based spectral analysis allows automated, operator-independent characterization of probable interactions between impaired respiration and upper airway anatomical obstruction. The clinical utility of spectrographic classification, especially in predicting failure of positive airway pressure therapy, remains to be more thoroughly tested

Practical Significance:
Using the Heart Health Study population of 3989 subjects, this study shows that CPC not only differentiated obstructive vs. central vs. complex sleep apnea, but it positively correlated with periodic breathing episodes in PSG and was the strongest predictor of success or failure with PAP titration.

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Distinct polysomnographic and ECG-spectrographic phenotypes embedded within obstructive sleep apnea

Authors:
Robert Joseph Thomas, Chol Shin, Matt Travis Bianchi, Clete Kushida and Chang-Ho Yun

Reference:
Sleep Science and Practice 20171:11, 10.1186/s41606-017-0012-9

Objectives:
The primary metric extracted from the polysomnogram in patients with sleep apnea is the apnea-hypopnea
index (or respiratory disturbance index) and its derivatives. Other phenomena of possible importance such as periods of stable breathing, features suggestive of high respiratory control loop gain, and sleep fragmentation phenotypes are not commonly generated in clinical practice or research. A broader phenotype designation can provide insights into biological processes, and possibly clinical therapy outcome effects.
 

Conclusions:
Distinct phenotypes are readily seen at all severities of sleep apnea, and can be identified from conventional polysomnography. The ECG-spectrogram analysis provides further phenotypic differentiation.

Practical Significance:
The dataset used for this study was the archived baseline diagnostic polysomnograms from the Apnea Positive Pressure Long-term Efficacy Study (APPLES). The electrocardiogram (ECG)-derived cardiopulmonary coupling sleep spectrogram was computed from the polysomnogram. Sleep fragmentation phenotypes used thresholds of sleep efficiency (SE) ≤ 70%, non-rapid eye movement (NREM) sleep N1 ≥ 30%, wake after sleep onset (WASO) ≥ 60 min, and high frequency coupling (HFC) on the ECG-spectrogram ≤ 30%. Sleep consolidation phenotypes used thresholds of SE ≥ 90%, WASO ≤ 30 min, HFC ≥ 50% and N1 ≤ 10%. Multiple and logistic regression analysis explored cross-sectional associations with covariates and across phenotype categories. NREM vs. REM dominant apnea categories were identified when the NREM divided by REM respiratory disturbance index (RDI) was > 1.

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Electrocardiogram-Based Sleep Spectrogram Measures of Sleep Stability and Glucose Disposal in Sleep Disordered Breathing

Authors:
Pogach, MD; Naresh M. Punjabi, MD, PhD; Neil Thomas; Robert J. Thomas, MD

Reference:
SLEEP 201235(1):139-148

Objectives:
This analysis explored associations between glucose metabolism and an EEG-independent measure of sleep quality, the sleep spectrogram, which maps coupled oscillations of heart-rate variability and electrocardiogram (ECG)-derived respiration.

Conclusions:
The ECG-spectrogram analysis of sleep quality may provide information beyond that obtained by conventional polysomnography (PSG) in relationship to glucose metabolism

Practical Significance:
Experimental sleep fragmentation can impair insulin sensitivity. ECG-derived sleep-spectrogram measures of sleep quality are associated with alterations in glucose-insulin homeostasis. This could improve our understanding of sleep and sleep-breathing effects on glucose metabolism.

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Heritability of Abnormalities in in Sleep Apnea: Use of an Electrocardiogram-based Technique

Authors:
Ibrahim LH, Jacono FJ, Patel SR, Thomas RJ, Larkin EK, Mietus JE, Peng CK, Goldberger AL, Redline S

Reference:
SLEEP 2010;33(5):643-646

Objectives:
To evaluate the familial aggregation of distinctive spectrographic biomarkers of unstable sleep, related to elevated-low frequency (e-LFC), and to assess their utility in genetic studies.

Conclusions:
Approximately 30% of the variability of e-LFC, measured from a continuous ECG during sleep is explained by familial factors other than BMI. ECG-based spectrographic measures of heart rate variability & breathing rate may provide novel markers for characterizing subgroups of individuals with different propensities and genetic etiologies for sleep apnea or for other conditions associated with sleep fragmentation.

Practical Significance:
This study suggests that CPC provides an objective measure aimed to enhance our understanding of the genetics of OSA by identifying intermediate traits with high heritability.

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Prevalent Hypertension and Stroke in the Sleep Heart Health Study: Association with an ECG-derived Spectrographic Marker of Cardiopulmonary Coupling

Authors:
Thomas RJ, Weiss MD, Mietus JE, Peng CK, Goldberger AL, Gottlieb DJ.

Reference:
SLEEP 2009;32(7):897-904

Objectives:
The ECG-based sleep spectrogram generates a map of CPC based on heart rate variability and respiration derived from QRS amplitude variations. A distinct spectrographic type, designated as elevated Low Frequency Coupling Narrow Band (e-LFCNB), has been associated with central apneas and periodic breathing and predicts failure of CPAP therapy. This study assesses, at a population level, the associations of this spectrographic biomarker with prevalent cardiovascular disease using the Sleep Heart Health Study (SHHS)-I dataset.

Conclusions:
An ECG derived spectrographic marker related to low frequency is associated with greater sleep apnea severity. Whether this biomarker is solely a sign of more severe disease or whether it reflects primary alterations in sleep apnea pathophysiology, which may either cause or result from sleep apnea, is unknown. This ECG-based spectral marker is associated with a higher prevalence of hypertension and stroke.

Practical Significance:
The presence of e-LFCNB represents for the first time a biomarker for sleep disordered breathing independent of age, sex and body mass has been described.

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Sleep quality change after upper airway surgery in obstructive sleep apnea: Electrocardiogram-based cardiopulmonary coupling analysis

Authors:
Choi JH1, Thomas RJ, Suh SY, Park IH, Kim TH, Lee SH, Lee HM, Yun CH, Lee SH.

Reference:
Laryngoscope. 2015 Feb 3. doi: 10.1002/lary.25101.

Objectives:
Sleep quality change after upper airway surgery in obstructive sleep apnea: Electrocardiogram-based cardiopulmonary coupling analysis

Conclusions:
Successful upper airway surgery can improve objective sleep quality in adult patients with OSA. CPC metrics of sleep quality are potentially useful to monitor therapeutic responses during long-term postoperative follow-up, as the ECG-based analysis is available as a standalone option outside laboratory polysomnography.

Practical Significance:
Sleep quality measured by CPC analysis improved significantly (HFC, P = .001; LFC, P = .002; e-LFC, P = .003), along with parallel reduction in ESS, respiratory parameters (AHI, AI, minimum SaO2), and sleep fragmentation (ArI) in the group with surgical success after upper airway surgery.

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The association between leukocyte telomere lengths and sleep instability based on cardiopulmonary coupling analysis

Authors:
Kwon AM1, Baik I, Thomas RJ, Shin C.

Reference:
Sleep Breath. 2015 Jan 28.

Objectives:
The purpose of the study is to examine the objective association between sleep stability and leukocyte telomere lengths (LTL) using cardiopulmonary coupling (CPC) analysis, which is an electrocardiogram (ECG)-based technique to quantify physiologic sleep stability.

Conclusions:
The present study suggested that shorter LTL might contribute to reduced sleep stability by interacting with OSA severity due to the stress of chronic sleep fragmentation or invariant sympathetic activity by respiratory chemoreflex activation.

Practical Significance:
LTL showed a significant association with elevated narrow-band low frequency coupling (e-LFCNB, a CPC marker of periodic breathing or sleep fragmentation due to pathological respiratory chemoreflex activation) by interacting with obstructive sleep apnea (OSA) severity (p value of <0.0001). Especially, sleep stability significantly reduced with shortened LTL in OSA patients (Apnea-Hypopnea Index (AHI) ≥15) based on increased e-LFCNB which had a negative correlation with high-frequency coupling band (HFC), a marker of stable sleep.

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The Sleep Quality Recovery of a Snorer's Bed Partner

Authors:
Schramm PJ, Neville AN, Baker D

Reference:
Respiratory Therapy Vol. 5 No. 3 June-July 2010 pg. 39

Objectives:
To demonstrate, through the use of CPC technology, the negative impact of snoring and Obstructive Sleep Apnea (OSA) and the response to PAP initiation the bed partner’s sleep quality.

Conclusions:
Both the snorer and his bed partner’s sleep quality improved significantly with the application of PAP therapy.

Practical Significance:
Proof to a reticent CPAP user of the benefit of CPAP compliance to their bed partner as well as themselves

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