David Duverney

Screening of Obstructive Sleep Apnea Syndrome by Heart Rate Variability Analysis

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.

Relationship Among the Severity of Sleep Apnea Syndrome, Cardiac Arrhythmias, and Autonomic Imbalance

ROCHE, F., et al.: Relationship Among the Severity of Sleep Apnea Syndrome, Cardiac Arrhythmias, and Autonomic Imbalance. The relationship between obstructive sleep apnea syndrome (OSAS), cardiac arrhythmias, and conduction disturbances in adults remains controversial. Early studies showed a higher prevalence than more recent and designed epidemiological studies. To clarify the actual prevalence of cardiac arrhythmias and conduction disturbances in patients referred for assessment of OSAS, a prospective cohort study was conducted: 147 consecutive patients (103 men; mean age of 54.5 ± 10.7 years) underwent time‐synchronized polysomnography and ECG Holter monitoring. OSAS was diagnosed in 66 (44.9%) of them based on an apnea hypopnea index (AHI) ≥10. Prevalence of heart failure, of prior myocardial infarction, of hypertension, and of ventricular arrhythmias were similar in patients with or without OSAS. Nocturnal paroxysmal asystole was significantly more prevalent in OSAS patients (10.6 vs 1.2%; P < 0.02) and the number of episodes of bradycardia and pauses increased with the severity of the syndrome. Almost all bradycardic events occurred in patients with severe OSAS (AHI > 30), prolonged periods of arterial oxyhemoglobin desaturation, and low diurnal awake PaO2. Moreover, using heart rate variability analysis, nocturnal sinusal dysfunction contrasted with a blunted diurnal parasympathetic modulation of the sinus node. Frequent nocturnal nonsustained supraventricular tachycardias were predominantly found in patients with severe sleep related breathing disorders; however, an increased risk of ventricular arrhythmias was not found. Under continuous positive airway pressure treatment, the 1‐year follow‐up of OSAS patients with nocturnal pauses did not reveal any arrhythmic event justifying a specific intervention. (PACE 2003; 26:669–677)

Predicting sleep apnoea syndrome from heart period: a time-frequency wavelet analysis

Heart rate fluctuations are a typical finding during obstructive sleep apnoea, characterised by bradycardia during the apnoeic phase and tachycardia at the restoration of ventilation. In this study, a time-frequency domain analysis of the nocturnal heart rate variability (HRV) was evaluated as the single diagnostic marker for obstructive sleep apnoea syndrome (OSAS). The predictive accuracy of time-frequency HRV variables (wavelet (Wv) decomposition parameters from level 2 (Wv2) to level 256 (Wv256)) obtained from nocturnal electrocardiogram Holter monitoring were analysed in 147 consecutive patients aged 53.8±11.2 yrs referred for possible OSAS. OSAS was diagnosed in 66 patients (44.9%) according to an apnoea/hypopnoea index ≥10. Using receiver-operating characteristic curves analysis, the most powerful predictor variable was Wv32 (W 0.758, p<0.0001), followed by Wv16 (W 0.729, p<0.0001) and Wv64 (W 0.700, p<0.0001). Classification and Regression Trees methodology generated a decision tree for OSAS prediction including all levels of Wv coefficients, from Wv2 to Wv256 with a sensitivity reaching 92.4% and a specificity of 90.1% (percentage of agreement 91.2%) with this nonparametric analysis. Time-frequency parameters calculated using wavelet transform and extracted from the nocturnal heart period analysis appeared as powerful tools for obstructive sleep apnoea syndrome diagnosis.

Frequent and prolonged asymptomatic episodes of paroxysmal atrial fibrillation revealed by automatic long-term event recorders in patients with a negative 24-hour holter

ROCHE, F., et al.: Frequent and Prolonged Asymptomatic Episodes of Paroxysmal Atrial Fibrillation Revealed by Automatic Long‐Term Event Recorders in Patients with a Negative 24‐Hour Holter. The presence, frequency, and duration of episodes of paroxysmal atrial fibrillation (PAF) is difficult to establish. This is caused by the limited duration of standard Holter recordings and to the unsatisfactory yield of patient‐triggered event recorders, because of asymptomatic events and of an inconsistent use of the patient dependent triggering function. A prospective cohort of 65 consecutive patients with recurrent palpitations and a negative 24‐hour ECG Holter was investigated by means of a cardiac event recorder bearing continuous automatic arrhythmia analysis and storage. Over a mean duration of 77 ± 36 hours, episodes of PAF were diagnosed in 20 (31%) patients, who had a total of 37 episodes; mean duration of PAF episodes was 7 hours 50 minutes ± 8/hours 45 minutes (minimum 45 minutes, maximum 28 hours). Eleven (55%) of these 20 patients were asymptomatic and would have remained undiagnosed without the automatic mode of the event recorder. Asymptomatic PAF episodes were longer than symptomatic ones (10 hours 30 minutes ± 6 hours 30 minutes vs 4 hours 50 minutes ± 4 hours, P < 0.05). In addition, episodes of sustained paroxysmal supraventricular tachycardia (PSVT) were diagnosed in 39 (57%) patients, of whom 34 (87%) were symptomatic. In this prospective cohort, a second standard 24‐hour monitoring would have missed 44% of the patients with PAF or PSVT and a classical patient‐triggered event recorder 13%. In patients still complaining of palpitations after one negative 24‐hour Holter, numerous, prolonged, and often asymptomatic episodes of PAF can be revealed by long‐term automatic event recorders. These devices should help clarify the clinical consequences of such episodes.

Interval training in elderly men increases both heart rate variability and baroreflex activity.

AimsAutonomic nervous system activity decreases continuously with age and appears to be a powerful predictor of disease and death. Attempts are thus made to reactivate autonomic drive with the intent of improving health.MethodsWe assessed maximal oxygen consumption (VO2max), auto- nomic nervous system activity by heart rate variability (HRV) analysis and spontaneous cardiac baroreflex activity (SBR) in eleven elderly men (73.5±4.2 years) before and after a 14-week program of intensive cycloergometer interval training. The standard HRV indices were calculated using time domain (mean RR, PNN50, RMSSD, SDNN, SDANN and SDNNIDX), and Fourier transform (total power, ULF,VLF, LF, LFnu, HF, HFnu and LF/HF) analyses of 24-hour, daytime and nighttime Holter recordings. The SBR was calculated from 15-minute recordings of spontaneous blood pressure and RR interval variations using the sequence (slope, slSBR) and cross-spectral (αSBRHF and αSBRLF) methods.ResultsAfter the training period,VO2max increased by 18.6 % (26.8±4.4 to 31.8±5.2 ml · kg–1 · min–1, p<0.01). The nocturnal parasympathetic indices of HRV increased (PNN50: 3.05±2.21 to 5.00±2.87%, RMSSD: 29.1±7.6 to 38.8±10.9 ms, HF: 117±54 to 194±116 ms2/Hz, all p<0.05) as did the SBR indices (slSBR: 7.0±1.8 to 9.8±2.1 ms·mmHg–1, p<0.01; αSBRHF: 6.9±2.2 to 10.5±3.7 ms ·mmHg–1, p<0.05; αSBRLF: 5.3±2.3 to 6.9±3.1 ms ·mmHg–1, p=0.22).ConclusionIntensive endurance training in elderly men enhanced parasympathetic parameters of HRV and, interestingly, of SBR. Physiological mechanisms and long-term clinical effects on health status should be further investigated.

Wavelet transform of heart rate variability to assess autonomic nervous system activity does not predict arousal from general anesthesia

PurposeThe relationship between autonomic nervous system (ANS) activity and general anesthesia has been explored. Studies have demonstrated partial recovery of heart rate variability (HRV), representative of ANS activity in the postoperative period, but the arousal period has not been precisely studied. The goals of this study were to analyze modifications of ANS activity during general anesthesia and, more particularly, around the arousal period, to look for predictors of arousal.MethodsWe analyzed HRV changes using wavelet transform, a time-frequency analysis that, in contrast to Fourier transform, is able to assess abrupt changes of ANS activity. Seventeen patients (mean ♂ SD age: 40.9 ♂ 16.4 yr) under general anesthesia for hip or knee surgery, were included in the study. The analysis began one hour before anesthesia, focussed on eye opening, and ended three hours after arousal.ResultsThere was a dramatic decrease in HRV after induction, that extended throughout anesthesia and represented a decrease in global autonomic regulation with, however, a relative predominance of vagal tone. At the moment of eye opening, there was an abrupt change in HRV, representing a sudden shift of ANS balance towards the predominance of sympathetic activity, while none of these indices changed seconds before arousal.ConclusionsWavelet analysis of HRV appears to be powerful tool to precisely assess instantaneous changes of HRV during anesthesia. Using this method, there were no identifiable precursory HRV indices of arousal.RésuméObjectifOn connaît la relation entre l’activité du système nerveux autonome (SNA) et l’anesthésie générale. Des études ont démontré la récupération postopératoire partielle de la variabilité de la fréquence cardiaque (VFC), représentant l’activité du SNA, mais le retour à la conscience n’a pas été précisément étudié. Les objectifs de la présente étude sont d’analyser les modifications de l’activité du SNA pendant l’anesthésie générale et, plus particulièrement, la période entourant le retour à la conscience, afin de découvrir des prédicteurs de réveil.MéthodeNous avons analysé les changements de VFC en utilisant la transformée par ondelettes, une analyse temps-fréquence qui, contrairement à la transformée de Fourier, permet d’évaluer les changements brusques de l’activité du SNA. Dixsept patients (âge moyen ♂ écart type : 40,9 ♂ 16,4 ans), sous anesthésie générale pour une intervention à la hanche ou au genou, ont participé à l’étude. L’analyse, centrée sur l’ouverture des yeux, a débuté une heure avant l’anesthésie et s’est terminée trois heures après le retour à la conscience.RésultatsAprès l’induction de l’anesthésie, il s’est produit une baisse marquée de la VFC qui s’est prolongée tout au long de l’anesthésie et qui représentait une diminution de la régulation autonome globale accompagnée, toutefois, d’une relative prédominance du tonus vagal. À l’ouverture des yeux, il y a eu un changement brusque de la VFC, indice d’un décalage soudain dans l’équilibre du SNA vers une prédominance de l’activité sympathique, alors qu’aucun de ces indices n’avait changé quelques secondes avant le réveil.ConclusionL’analyse par ondelettes de la VFC s’est révélée un outil puissant pour évaluer de façon précise les modifications de la VFC pendant l’anesthésie. Cette méthode n’a pas montré d’indices précurseurs identifiables de VFC de réveil.

Cardiac Interbeat Interval Increment for the Identification of Obstructive Sleep Apnea

ROCHE, F., et al.: Cardiac Interbeat Interval Increment for the Identification of Obstructive Sleep Apnea. 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 VLFIpsd (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.

High Accuracy of Automatic Detection of Atrial Fibrillation Using Wavelet Transform of Heart Rate Intervals

DUVERNEY, D., et al.: High Accuracy of Automatic Detection of Atrial Fibrillation Using Wavelet Transform of Heart Rate Intervals. Permanent and paroxysmal AF is a risk factor for the occurrence and the recurrence of stroke, which can occur as its first manifestation. However, its automatic identification is still unsatisfactory. In this study, a new mathematical approach was evaluated to automate AF identification. A derivation set of 30 24‐hour Holter recordings, 15 with chronic AF (CAF) and 15 with sinus rhythm (SR), allowed the authors to establish specific RR variability characteristics using wavelet and fractal analysis. Then, a validation set of 50 subjects was studied using these criteria, 19 with CAF, 16 with SR, and 15 with paroxysmal AF (PAF); and each QRS was classified as true or false sinus or AF beat. In the SR group, specificity reached 99.9%; in the CAF group, sensitivity reached 99.2%; in the PAF group, sensitivity reached 96.1%, and specificity 92.6%. However, classification on a patient basis provided a sensitivity of 100%. This new approach showed a high sensitivity and a high specificity for automatic AF detection, and could be used in screening for AF in large populations at risk.

Effect of acute hypoxia on QT rate dependence and corrected QT interval in healthy subjects

LVESD. In addition, during an average follow-up period of 10.8 years, we observed no significant abnormal change in LV dimensions in this cohort. This would seem to disprove the speculation that fibrillin defect in the myocardium may predispose patients with Marfan syndrome to LV dilatation and reduced LV function.4 As with all negative studies, a major weakness is the number of subjects studied and the possibility that if a larger number of patients were studied, a significant difference would be detected. During the clinical course of Marfan syndrome many patients develop valvular lesions,5,6 and this, of course, limits the number of patients available for a study like ours. With our sample size of 36 patients, there was sufficient power to exclude the presence of moderate differences. For instance, there was 90% power to detect average differences from normal if the differences were 0.56 SD units in magnitude or larger. As an example, LVEDD measurements, rescaled to be relative to the normal predictions, had an SD of about 1.7%. With our sample of 36 subjects, we can be 90% confident that the average LVEDD measurements from patients with the Marfan syndrome did not differ from normal by 1%. Although the average of the distribution of LV dimensions did not present any statistically significant difference from the normal average, 7 patients had increased LVEDD. Of these patients, 3 also had an increased LVESD. Overall, 2 patients had increased LVEDD and LVESD on the first and last echocardiograms. Ejection fraction was 50% for all patients and did not change during the follow-up period.

Quantification of cumulated physical fatigue at the workplace

Abstract. Quantification of physical fatigue remains a challenge. We hypothesized that its effects on central autonomic nervous system activity could be explored for such a quantification. To test this relationship, we prospectively measured central autonomic nervous activity through nocturnal heart rate variability (HRV) in six French garbage collectors, aged 32.1±4.3 years, twice a week during 3 consecutive weeks of work, and during the following week of rest. Eight healthy sedentary males formed a control group. HRV indices were calculated by applying standard temporal domain and wavelet transform analyses to standard ECG recordings. During the 3 consecutive weeks of work, there was a significantly progressive decrease in HRV indices, particularly pNN50 (–34.2%, P<0.05), as well as the high (–33.3%, P<0.05) and low (–22.2%, P<0.01) frequency components of wavelet transform, while there was an increase, although non-significant, of the ratio of low to high frequencies (9.1%). During the resting period, there was a significant recovery of HRV indices, notably of its high (50.0%, P<0.05) and low (28.6%, P<0.05) frequency components. No such changes occurred in the control group. A central signature of cumulated physical fatigue can thus be detected and quantified through nocturnal autonomic nervous system activity. Its characteristics are those of a progressive parasympathetic withdrawal.