Cardiac Variability and Heart-Rate Increment as a Marker of Sleep Fragmentation in Patients With a Sleep Disorder: a Preliminary Study
Emilia Sforza, MD, PhD(1); Vincent Pichot, PhD(2); Katerina Cervena MD(1); Jean Claude Barthélémy, MD, PhD(2); Frederic Roche, MD(2)
(1): Sleep laboratory, Department of Psychiatry, University Hospital, Geneva, Switzerland
(2): Service d’Exploration Fonctionnelle Cardiorespiratoire, University Hospital, Saint-Etienne, France.
Study Objectives
The ratio between the heart-rate increment to total power spectral density (%VLFI) has been introduced as a sensitive measure of sleep-related breathing disorders (SRBD). Since a complex interaction is present between sleep disorders and occurrence of arousals, we hypothesized that %VLFI and other indexes of heart-rate variability (HRV) measures refl ect the degree of sleep fragmentation.
Methods
The high- and low-frequency peaks from spectral analysis (FFT) of R-R intervals, the HRV changes using wavelet transform (WT), the geometric and time domain HRV, and the %VLFI were measured in 336 sleep studies performed in patients with insomnia, SRBD and restless legs syndrome/ periodic limb movement disorder (RLS/PLMD). The ability of HRV measures to assess sleep fragmentation was examined by correlation analysis and from the area under the receiver operating characteristic (ROC) curve.
Results
The ratio of low frequency to high frequency (LF/HF ratio) at the FFT and WT and the %VLFI were higher in patients with SRBD and RLS/PLMD, compared with patients with insomnia. These measures were related to the arousal (MA) index as well as to the apnea-hypopnea index, oxygen desaturations, and periodic leg movement index (p < .001). The presence of a sleep fragmentation defi ned as an MA index > 20 was well detected by the %VLFI (ROC area: 0.66 ± 0.03) and the LF/HF ratio at WT (ROC area: 0.66 ± 0.03).
Conclusion
The %VLFI and LF/HF ratio provide indirect measures of sleep fragmentation, suggesting that HRV measures during sleep assess more the associated sleep fragmentation than the presence of a specific sleep disorder.
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The use of heart rate variability in detecting sleep disordered breathing in patients with heart failure
A Vazir 1*, M Dayer 1, RH Minnion 2, MR Cowie 1, PA Poole-Wilson 1, MJ Morrell 2 and AK Simonds 2. 1 Cardiac Medicine and 2 Clinical & Academic Unit of Sleep & Breathing, Royal Brompton Hospital, National Heart & lung Institute, Imperial college, London, UK.
Background
Sleep disordered breathing (SDB) is common in patients with congestive heart failure (CHF). In patients with OSA, the very low frequency (VLF) power spectral density of the interbeat interval increment, when corrected for the total power spectral density (%VLFI), is strongly associated with presence of obstructive apneas.
Aim
To determine if the %VLFI could be used to detect the presence of SDB in CHF patients.
Methods
20 male patients with CHF [age 62.1(11.7) yrs, NYHA 1.5(0.6), EF 39.5(12.7) %, MVO2 17.6(3.6) ml/Kg/min] were recruited. Patients with atrial fibrillation, ventricular pacing, excessive ventricular ectopy were excluded. All underwent polysomnography. SDB was defined as an AHI20 events/hr. Heart rate (HR) data was collected overnight using a Holter monitor and processed using an analysis program automated to calculate %VLFI (Novacor).
Results
9/20 had SDB. A receiver operator characteristic curve was constructed assuming a cut-off an AHI of 20 events/hr. The area under the curve was 0.869, and the asymptotic significance was 0.011. Setting the %VLFI at 2.33% yielded a sensitivity of 100% and a specificity of 64.3%. The positive predictive value was 54.5% and the negative predictive value 100%. There were no false negatives.
Summary
Spectral analysis of HR may be used as a rule out test for SDB in mild to moderate CHF. For health services assessment of HR variability may reduce demand on overburden sleep laboratories, by eliminating those unlikely to have SDB.
Presented at the ERS 2004, Glasgow
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Screening
of obstructive sleep apnea syndrome by heart rate variability
analysis.
Roche F. et al.
BACKGROUND
Enhanced nocturnal heart rate variability (HRV) has been evoked in
sleep-related breathing disorders. However, its capacity to detect
obstructive sleep apnea syndrome (OSAS) has not been systematically
determined. Thus, we evaluated the discriminant power of HRV parameters
in a first group of patients (G1) and validated their discriminant
capacity in a second group (G2).
METHODS AND RESULTS
In G1, 39 of 91 patients (42.8%) were identified
as diseased by polysomnography, as were 24 of 52 patients
(46%) in G2. Time-domain HRV variables (SD of NN intervals
[SDNN], mean of the standard deviations of all NN intervals
for all consecutive 5-minute segments of the recording
[SDNN index], square root of the mean of the sum of the
squares of differences between adjacent normal RR intervals
[r-MSSD], and SD of the averages of NN intervals in all
5-minute segments of the recording [SDANN]) were calculated
for daytime and nighttime periods, as well as the differences
between daytime and nighttime values (Delta[D/N]). Correlations
between HRV variables and OSAS status were analyzed in
G1 by use of receiver-operating characteristic (ROC)
curves and logistic regression analysis. By ROC curve
analysis, 7 variables were significantly associated with
OSAS. After adjustment for other variables through multiple
logistic regression analysis, Delta[D/N]SDNN index and
Delta[D/N] r-MSSD remained significant independent predictors
of OSAS, with ORs of 8.22 (95% CI, 3.16 to 21.4) and
2.86 (95% CI, 1.21 to 6.75), respectively. The classification
and regression tree methodology demonstrated a sensitivity
reaching 89.7% (95% CI, 73.7 to 97.7) with Delta[D/N]
SDNN index and a specificity of 98.1% (95% CI, 86.4 to
100) with Delta[D/N] SDNN using appropriate thresholds.
These thresholds, applied to G2, yielded a sensitivity
of 83% using Delta[D/N] SDNN index and a specificity
of 96.5% using Delta[D/N] SDNN.
CONCLUSIONS
Time-domain HRV analysis may represent an accurate and inexpensive
screening tool in clinically suspected OSAS patients and may help
focus resources on those at the highest risk.
Circulation 1999; 111:1411-1415
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Cardiac
interbeat interval increment for the identification of obstructive
sleep apnea.
Roche F. et al.
The prevalence of obstructive sleep apnea syndrome (OSAS) is high in
developed countries but its diagnosis is costly. Based on physiological
evidence, the frequency component of heart rate variability (HRV) was
evaluated as a simple and inexpensive diagnostic tool in OSAS. The
predictive accuracy of frequency-domain HRV variables obtained from
24-hour ECG Holter monitoring (the power spectral density of the interbeat
interval increment of very low frequencies, "VLFIpsd," and
its percentage over the total power spectral density, "% VLFI"),
and of established time-domain HRV variables were analyzed by comparison
with respiratory disturbances indexes assessed by complete polysomnography
in 124 consecutive patients (98 men aged 53.8 +/- 11.2 years) with
clinically suspected OSAS. OSAS was present in 54 (43.5%) patients
according to standard criteria. Using receiver operating characteristic
curve analysis, two of the three most powerful predictors were frequency-domain
variables: % VLFI (W = 0.80, P < 0.0001), and VL-FIpsd (W = 0.79,
P < 0.0001). Using a multiple logistic regression analysis, %VLFI
was the most strongly associated with diseased status (adjusted OR:
8.4; 95% CI: 3.4-19.5). Using an appropriate threshold, %VLFI demonstrated
a diagnostic sensitivity of 87%. A 3-month continuous positive airway
pressure treatment significantly improved the same parameter. Frequency-domain
analysis of the interbeat interval increment appears as a powerful
tool for OSAS diagnosis and follow-up. The simplicity of its analysis
and of its use makes of it a well-suited variable for mass screening
of OSAS patients.
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PACE
2002; 25:1192-1199
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The
unexpected sleep apnea syndrome is highly prevalent and associated
with the alteration of the autonomic nervous system activity
in a general 65 years old population. The PROOF study
F.
Roche, V. Pichot, D. Duverney, F. Costes, S. Chomienne, M. Garet,
J.-C. Barthelemy.
CHU Saint-Etienne, Physiologie Clinique, Saint-Etienne, France.
Aim
Up to 5% of adults in Western countries are likely to have undiagnosed
obstructive sleep apnea syndrome (OSAS). OSAS had be found to be particularly
highly prevalent in people older than age 65 years. The identification
of OSAS as a risk factor for increased morbidity and mortality is needed
in such older population since they should become candidates for treatment.
The autonomic nervous system (ANS) activity, a recognized marker of cardiovascular
and all cause mortality in a general population, is precociously altered
in OSAS: the degree of autonomic imbalance appears correlated with sleep
fragmentation, inspiratory efforts and hypoxia.
Methods
We thus evaluated in a large cohort (n=1011) of 65+-0.4 years old men
(40%) and women (60%) free of cardiovascular of cerebrovascular
event or of diagnoses Sleep Related Breathing Disorders, the prevalence
of unexpected OSAS and its relationship with ambulatory blood pressure,
spontaneous cardiac baroflex sensitivity and basal cardiac autonomic
activity.
Results
According to the presence of nocturnal cyclical heart rate variability
quantified using validated algorithm calculating the Very Low Frequency
component of the Interbeat Interval Increment (VLFi, Roche et al.
PACE 2002), the probability of OSAS was retained in 40% and 14%
of this population with a VLFi threshold corresponding to, respectively
10 and 30 brady/tachycardia cycles per hour of sleep.
Using logistic regression analysis, the severity of OSAS was highly
correlated with spontaneous baroflex sensitivity (p<0.01), and
heart rate variability parameters (parasympathetic indicators,
p<0.0001). Neither BMI, nor ambulatory blood pressure were significantely
associated with OSAS.
Conclusion
Thus, the presence of OSAS and the alteration of ANS appears highly
in a general 65 years old population. The follow-up of this parameter
to determine the clinical implications of such findings in the
occurrence of cardiovascular events is now proposed.
Eur.
Heart Journal, 2003, vol24 (suppl) Abstract 2697
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Heart rate increment: an electrocardiological approach for the early detection of obstructive sleep apnoea-hypopnea syndrome.
Roche F, Sforza E, Duverney D, Borderies JR, Pichot V, Bigaignon O, Ascher G, Barthelemy JC.
The prevalence of obstructive sleep apnoea-hypopnea syndrome (OSAHS) is high in developed countries and it is estimated that the vast majority of patients remain undiagnosed. Based on physiological evidence, we evaluated the frequency component of heart rate increment (HRI) as a simple and inexpensive screening tool for OSAHS detection in a first group of patients (G1) and validated their discriminant capacity in a second group (G2). The predictive accuracy of hourly frequency-domain HRI variable obtained from nocturnal ECG Holter monitoring "%VLFI", was analysed by comparison with hour by hour respiratory disturbances index assessed by complete polysomnography in 28 consecutive clinically suspected OSAHS patients for G1 and in 35 patients for G2. OSAHS was present in 20 patients according to a mean hourly apnoea plus hypopnea index > 10 in G1 and prevalence reached 77.1% in G2. Sensitivity, specificity, positive and negative predictive accuracy were calculated and a receiver operating characteristic (ROC) curve was constructed for several polysomnographic threshold values. In G1, hourly %VLFI appears as an evident predictor of apnoea plus hypopnea index (W=0.848, p<0.0001). Using an appropriate threshold (value > 3.2%),%VLFI demonstrated a sensitivity of 78.1% and a specificity of 70.4%. These threshold, applied to G2, yielded a sensitivity of 73.9% and a specificity of 76.6%. Frequency-domain analysis of the heart rate increment appears as a powerful tool for OSAHS prediction. The simplicity of its analysis and of its use makes of it a particularly well-suited variable for routinely mass screening in high-risk populations undergoing ECG Holter monitoring.
Clinical Science (2004) 107, 105-110
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CLINICAL APPLICATIONS
Sleep Apnea 
