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Table of Contents
Vol. 69, No. 3, 2002
Issue release date: May–June 2002
Respiration 2002;69:235–241
(DOI:10.1159/000063626)

Automated Analysis of Data Is Inferior to Visual Analysis of Ambulatory Sleep Apnea Monitoring

Fietze I. · Glos M. · Röttig J. · Witt C.
Department of Cardiology, Angiology and Pulmology, Humboldt University Medical School Charité (Campus Mitte), Berlin, Germany
email Corresponding Author

Abstract

Background: Many ambulatory sleep apnea monitoring devices are equipped with software which allows an automated analysis of data as well as a visual analysis. Objective: The Merlin system which records heart rate, snoring sound, efforts, oronasal flow, body position and oxygen saturation was investigated to identify proper parameter settings for the automated analysis and to compare the automated with the visual analysis in patients with mild obstructive sleep apnea syndrome (OSAS). Sensitivity and specificity of the visual and automated analysis of ambulatory monitoring in comparison with visual polysomnographic (PSG) analysis were determined. Methods and Results: First, we tried to find the optimal parameters for the automated analysis, using 7 different settings in 17 OSAS patients. Furthermore, we applied the optimized setting to 66 OSAS patients who were admitted (age 50.9 ± 9.9 years, BMI 32.9 ± 5 kg/m2), and compared the results with the visual analysis of raw data. The patients slept for one night in the sleep laboratory with Merlin and PSG simultaneously to compare the visual and automated analysis of Merlin data with results from the visual analysis of PSG. Automated analysis leads to an underestimation of the respiratory disturbance index (RDI; p < 0.001) compared with both the visual analysis and results of PSG. Using a cutoff level of 5 apneas and hypopneas/h for the diagnosis of OSAS, the sensitivity of Merlin with the automated analysis is 40.6% and the specificity is 100%. With a cutoff level of 15/h, sensitivity and specificity rose to 91.3 and 100%, respectively, which is comparable to the visual analysis. Conclusion: Merlin is a reliable device for detection of sleep-related breathing disorders, but recordings should be analyzed visually, especially in patients with a low RDI.


 Outline


 goto top of outline Key Words

  • Sleep apnea
  • Ambulatory monitoring
  • Merlin system
  • Polysomnography

 goto top of outline Abstract

Background: Many ambulatory sleep apnea monitoring devices are equipped with software which allows an automated analysis of data as well as a visual analysis. Objective: The Merlin system which records heart rate, snoring sound, efforts, oronasal flow, body position and oxygen saturation was investigated to identify proper parameter settings for the automated analysis and to compare the automated with the visual analysis in patients with mild obstructive sleep apnea syndrome (OSAS). Sensitivity and specificity of the visual and automated analysis of ambulatory monitoring in comparison with visual polysomnographic (PSG) analysis were determined. Methods and Results: First, we tried to find the optimal parameters for the automated analysis, using 7 different settings in 17 OSAS patients. Furthermore, we applied the optimized setting to 66 OSAS patients who were admitted (age 50.9 ± 9.9 years, BMI 32.9 ± 5 kg/m2), and compared the results with the visual analysis of raw data. The patients slept for one night in the sleep laboratory with Merlin and PSG simultaneously to compare the visual and automated analysis of Merlin data with results from the visual analysis of PSG. Automated analysis leads to an underestimation of the respiratory disturbance index (RDI; p < 0.001) compared with both the visual analysis and results of PSG. Using a cutoff level of 5 apneas and hypopneas/h for the diagnosis of OSAS, the sensitivity of Merlin with the automated analysis is 40.6% and the specificity is 100%. With a cutoff level of 15/h, sensitivity and specificity rose to 91.3 and 100%, respectively, which is comparable to the visual analysis. Conclusion: Merlin is a reliable device for detection of sleep-related breathing disorders, but recordings should be analyzed visually, especially in patients with a low RDI.

Copyright © 2002 S. Karger AG, Basel


goto top of outline introduction

Due to the high prevalence of the sleep apnea syndrome (SAS), there is an increasing need for reliable outpatient screening systems to separate severe from slight cases and to identify patients in need of evaluation in a sleep laboratory. This stepwise procedure of diagnosing SAS [1] is widely used for ambulatory and in-hospital monitoring. The high demand for such devices is also demonstrated in the variety of commercially available systems, such as EdenTec 3711 (Nellcor, Eden Praire, Minn., USA), Mesam, Mesam IV and Poly-Mesam (MAP, Munich, Germany), Medilog MPA 2 (Oxford Med., Oxon, UK), Poly-G and Sleep I/T (CNS; Chantassen, Minn., USA), Somnolog 3 (Ventec Aps, Denmark), CID 102 (Cidelec, France), NightWatch System (Healthdyne, Brussels, Belgium) [2, 3, 4, 5, 6, 7, 8, 9, 10, 11]. Most of these systems contain software algorithms which allow automated analysis of registered data. This, of course, can be time saving and comfortable but in some systems the software parameters for automated analysis can be changed by the user, which raises the question of which parameter setting should be selected for which patient. Although there are some periodically updated standards for visual detection of breathing disorders [12], they are usually used differently in different labs, and are not automatically implemented in the analysis software [13]. Hence the aim of this study was to find a suitable parameter setting for the automated analysis of data of the ambulatory system Merlin, and to assess the accuracy of this setting compared with visual analysis. The degree of agreement of visual and automated analysis depending on the severity of obstructive SAS (OSAS) was tested focussing mainly on patients with mild to moderate OSAS. Sensitivity and specificity of automated and visual analysis of ambulatory monitoring compared with visual analysis of polysomnography (PSG) were calculated.

 

goto top of outline methods

goto top of outline equipment

The Merlin (Heinen & Loewenstein, Bad Ems, Germany) is an eleven-channel digital device, recording oronasal airflow (thermistor), snoring sound, thoracic and abdominal effort (with piezo sensors), heart rate (derived from a three-lead ECG), oxygen saturation, body position and nCPAP pressure. Three undesignated channels and an event marker can be used additionally. The device allows data recording for about 8 h. For automated analysis, different parameter settings can be used. For standard PSG we used the ALICE III system (Healthdyne Technologies, Atlanta, Ga., USA) [14]. The electrodes and recording techniques for cardiorespiratory monitoring used are comparable to those of the Merlin system. Patients slept using the Merlin and PSG technique simultaneously to avoid a possible night-to-night variability in the respiratory disturbance index (RDI) [15, 16].

goto top of outline study design

We prospectively investigated 66 patients referred from our outpatient department (age 50.9 ± 9.9 years, 65 male, 1 female, BMI 32.9 ± 5 kg/m2) because of snoring, daytime sleepiness or witnessed apneas. All patients were admitted to our sleep laboratory for one diagnostic night using the Merlin and the PSG system simultaneously. Each study started between 10 and 11 p.m. and was terminated at 7 a.m.

To determine the total sleep time (TST), patients recorded their bed time and subjective sleep time in a questionnaire. In addition to these data we used objective criteria of the Merlin recording such as snoring, heart rate changes, body movements and begin of quiet breathing to assess sleep times, subtracting obvious wake periods during the night. For comparison, the TST from PSG evaluation according to the standard criteria [17] was used.

For visual analysis apneas were defined if the following events occurred: a reduction in oronasal airflow to at least 15% of the normal breathing level and the duration of the event for at least 10 s. Hypopneas were defined as events with a reduction of oronasal airflow to at least 50% of the preceding breathing amplitude and a duration of at least 10 s. Additionally an oxygen saturation decrease of 3% was required for hypopneas [12]. Episodes with periodic breathing were also counted as hypopneas when oronasal airflow decreased to maximally 50% followed by a reduction of oxygen saturation of at least 2%. No duration criteria were used for periodic breathing. Respiratory events without O2 drops were not counted, nor were O2 drops alone. Patients with a central SAS were not included in the study. The apnea index (AI; apneas/h), the hypopnea index (HI; hypopneas/h) and the RDI were calculated.

goto top of outline study i: setting of parameters for automated analysis

In order to adapt automated analysis to different tasks different parameters and sensitivities can be set for each channel. The following parameters for the curves of flow, thoracic and abdominal efforts can be changed separately: apnea level (the reduction in amplitude necessary for counting as an apnea), hypopnea level (the reduction in amplitude necessary for counting as a hypopnea), error level (determines the degree of detection of artifacts), and window (the minimal time for an event to be counted). Additionally, oxygen saturation criteria may be changed. In our study we used the same saturation criteria as for the visual analysis for apneas and hypopneas. To find an appropriate setting for detecting apneas/hypopneas that would correspond to the visual analysis, we tested 7 different parameter settings (I–VII) of the respiration analysis (table 1) in a group of 17 patients, different from the prospective study group with 66 patients (study II). Retrospectively, we recruited the 17 patients with an RDI from 5 to 50/h according to a visual analysis from our outpatient department. Each recording of these patients was examined with all 7 parameter settings. The setting for an automated analysis which fitted best the visual analysis according to RDI detection and correlation analysis was determined for each patient (table 1). The optimal setting for most of the 17 patients was chosen for the next study (study II).

TAB01

Table 1. Parameter settings (I–VII) for automatic analysis of RDI from Merlin recording in 17 patients with SAS

goto top of outline study ii: comparison of rdi in visual and automated analysis of merlin data

The optimal analysis configuration from study I was applied to all recordings of the 66 patients prospectively studied in the sleep laboratory. Furthermore, automatic analysis was compared with visual analysis. To analyze differences depending on SAS severity, especially in patients with mild SAS, three groups were formed depending on visually detected RDI – group I: RDI <10/h (n = 32), group II: RDI between 10 and 20/h (n = 13) and group III: RDI >20/h (n = 21). No differences in age, BMI or concomitant diseases were evident between these three groups.

goto top of outline study iii: sensitivity and specificity of merlin data

In order to calculate sensitivity and specificity of automated and visual analysis of Merlin data compared with visual PSG analysis, we used three different cutoff levels for the RDI to determine the presence of OSAS: RDI >5/h, >10/h and >15/h. These cutoff levels were chosen because of the lack of an established RDI threshold for OSA diagnosis and due to their common usage in the literature and clinical practice [18]. Low cutoff levels were chosen in order to characterize the value of ambulatory monitoring with the Merlin device in patients with a mild SAS.

goto top of outline study iv: comparison of merlin data with psg

In all 66 patients the results of the automated and visual analysis of Merlin data were compared with the visual analysis of the PSG data, done by the same examiner according to the standard criteria. This was performed to confirm the accuracy of the visual analysis of ambulatory data and to check the intraobserver variability, since due to equal sensors in Merlin and PSG results should be comparable.

goto top of outline analysis

The difference between mean values of the calculated RDI of the visual and automated analysis in ambulatory and PSG recording was assessed using the Wilcoxon test for pairs. The rank correlation test according to Spearman was applied in study I, assessing the correlation between visual and automated RDI. Sensitivity, specificity and predictive values were calculated for the automated analysis of RDI from Merlin and for the visual analysis of RDI from Merlin compared to the visual analysis of RDI from PSG.

 

goto top of outline results

goto top of outline study i

None of the results of the 7 parameter settings corresponded to the visual analysis in all 17 investigated cases (table 1). The automated and visual analysis of RDI corresponded most frequently (8 cases) using the parameter setting No. VI. Setting No. II fitted best with regard to mean RDI, and settings No. I and VI fitted best with regard to correlation analysis. Thus setting No. VI was detected to be the most effective setting and was used for study II.

goto top of outline study ii

The comparison of the visual with the automated analysis using the parameter setting No. VI showed a significant difference of mean RDI: 24.2 ± 26.6/h (visual) versus 17.5 ± 22.4/h (automated; p < 0.001) (fig. 1), which is based both on lower AI (9.6 ± 16.8 vs. 6.5 ± 12.3/h, p < 0.001) and HI (15.1 ± 12.9 vs. 11.1 ± 12.7/h, p < 0.001) (table 2). Furthermore, it was evident that the correlation between the visual and automated analysis decreased with decreasing RDI. The correlation quotient was 0.86 (p < 0.001) for group III (RDI >20/h), 0.6 (p < 0.05) for group II (RDI 10–20/h) and 0.62 (p < 0.001) for group I (RDI <10/h).

TAB02

Table 2. Comparison of RDI, AI and HI in visually analyzed PSG and visual and automated Merlin analysis from 66 patients with SAS

FIG01

Fig. 1. Mean values and standard deviations of RDI in Merlin (V = visual analysis, A = automated analysis) and PSG in the three patient groups. Group I (n = 32): RDI <10/h, group II (n = 13): RDI = 10–20/h, group III (n = 21): RDI >20/h. * p < 0.01 for comparison with RDI in automated Merlin analysis.

goto top of outline study iii

With the visual PSG analysis as the gold standard the following results of visual Merlin analysis were obtained (table 3). Using a cutoff level of 5/h, the results of 3 patients were considered false-positive, and 2 false-negative. When setting the cutoff level to 10/h, 6 cases were counted as false-positive, and 4 cases were considered false-negative. Using a cutoff level of 15/h, 3 false-positive and 1 false-negative results were found. For automated analysis at a cutoff level of 5/h no false-positive but 19 false-negative results were found. At a cutoff level of 10/h, 1 false-positive and 8 false-negative results were detected, and at a cutoff level of 15/h no false-positive and 4 false-negative results were found.

TAB03

Table 3. Sensitivity and specificity in visual and automated analysis compared with PSG for different cutoff levels of the RDI

goto top of outline study iv

The TST as measured by PSG (316 ± 51 min) was slightly lower than the TST used for Merlin (341 ± 49 min). Nevertheless, we could detect a correlation (0.94, p < 0.001) between visual detection of RDI in Merlin (24.2 ± 26.6/h) and in PSG (23.6 ± 27.6/h) as well as between AI (9.6 ±16.8 vs. 13.9 ± 25.7/h; 0.75, p < 0.001) and HI (15.1 ± 12.9 vs. 9.7 ± 8.8/h; 0.51, p < 0.001). Comparing the results of the automated analysis (Merlin) with PSG, the mean RDI was underestimated (17.5 ± 22.4 vs. 23.6 ± 27.6/h; correlation coefficient 0.9, p < 0.001) as well as the mean AI (6.5 ± 12.3 vs. 13.9 ± 25.7/h) and HI (11.1 ± 12.7 vs. 9.7 ± 8.8/h; p < 0.001).

 

goto top of outline discussion

Ambulatory monitoring systems have been developed for screening of SAS. However, they are sometimes limited with regard to sensitivity and specificity due to simplified measuring methods or limited equipment of sensors [19, 20]. This applies especially to the use of automated analysis. Nevertheless, automated analysis offers a convenient and time-saving way, but as in PSG analysis, the gold standard, it should be controlled and supervised. Therefore, we tested the built-in automated analysis of the ambulatory monitoring device (Merlin) and compared the results with visual analysis, taking the degree of OSAS into account. We found a significant underestimation of the RDI and of AI and HI, respectively, in the automated analysis compared with the visual analysis. Carrasco et al. [21] and Kociej et al. [22] reported similar results. Carrassco et al. compared the automated scoring of nighttime recording of respiratory variables (NTRRV; like level III ASDA device) with visual analysis of the NTRRV and the full PSG in 36 OSA patients. Concerning the comparison of visual analysis of the portable device and the PSG, no differences could be detected. This is in agreement with our study, although we used the Merlin and the PSG simultaneously in order to avoid the known night-to-night variability in RDI [14, 15]. The disadvantage of such a procedure is a somewhat more uncomfortable situation for the patient due to the doubling of the sensors. However, previous investigators used the same methodology with no apparent adverse results [3, 6, 8]. A limitation of this study is the simultaneous use of ambulatory and PSG technique only in sleep laboratory conditions. Although the laboratory conditions are standard conditions and, therefore, comparable for each patient and the simultaneous measurement avoid night-to-night variability in RDI, further validation in the home setting is necessary.

Furthermore, we found that the agreement of automated and visual analysis increased with increasing RDI. This was evident in the correlation analysis of automated and visual analysis and in data concerning sensitivity and specificity. Such a high correlation between automated and visual analysis (0.86) was seen in patients with an RDI above 20/h and a lower correlation (0.60) was seen in patients with an RDI below 20/h. A high sensitivity and specificity for automated analysis was found in patients with an RDI cutoff point of 15/h, decreasing with a cutoff point of 10 or 5/h.

One reason for these findings could be the difference in TST used for calculating RDI. However, we used the same TST in visual and automated analysis, and the TST derived from the questionnaire and used for Merlin analysis was not significantly different from the TST derived from PSG. Another reason could be the inclusion of phases with periodic breathing into the visual analysis, which were not counted by the automated analysis. Although the number of periodic breathing episodes was negligible, its percentage of the overall RDI rose with decreasing RDI. This percentage might have been even greater if we had counted periodic breathing episodes without 2% drops in oxygen saturation, or oxygen saturation drops without changes in the effort and flow signals. Although such episodes were rare in our recordings, they may appear more frequently, e.g. in patients with concomitant cardiopulmonary diseases such as chronic obstructive lung disease or chronic heart failure, where hypoventilation or Cheyne-Stokes respiration is common. In these cases as well as in mild OSAS or upper airway resistance syndrome, automated analysis of ambulatory systems, i.e. Merlin device, may reach its limits, mainly because there are software limitations in detecting apneas, hypopneas, periodic breathing, hypoventilation episodes and Cheyne-Stokes respiration separately. Furthermore, there is still a lack of commonly agreed definitions of hypopneas and periodic breathing episodes [18, 23, 24], partly based on different detection methods (flow or effort). So different sleep labs might obtain different results here, especially in ambulatory measurements with their lack of arousal detection, which is, beside the oxygen saturation, an important criterion for disease assessment. Concerning the influence of arousal, Vasquez et al. [25] could show that there is only little change in diagnostic sensitivity and specificity, regardless of whether the apnea hypopnea index incorporated arousal criteria or not.

Another reason for the difference in automated and visual analysis could be the parameter setting. We aimed to find an optimal setting for the automated analysis in a study group (study I) different from the patient population used for study II. The setting we found was optimal for the mean RDI of 35.4 ± 28.7/h of the 17 patients (study I). However, the mean RDI (24.2 ± 26.6/h) of the 66 patients (study II) showed a different distribution. Therefore, study group I might have been insufficient with regard to the number of study objects, or a different setting might have been more appropriate for patients with a low RDI.

Another aim of the study was to determine the diagnostic value of Merlin by calculating sensitivity and specificity. We compared both the visual and the automated analysis with the PSG. The prospective assessment of the patients presented only mild RDI so that the range of disease severity was not wide, which limits the analysis of sensitivity and specificity of Merlin. Nevertheless, we found that they depend on the RDI cutoff level. The best sensitivity for visual analysis was obtained using a cutoff level of 5/h, the best specificity for 15/h. For automated analysis, the best sensitivity was found only with a cutoff level of 15/h, whereas the specificity was equally good regardless of the cutoff level. The problem of automated analysis is in the huge amount of false-negative findings even when using a cutoff level of 15/h. This makes automated analysis inferior to visual analysis, especially in patients with an RDI below 15/h. In comparison with the oximetry technique alone or other level II and III ASDA devices [5, 6, 11, 12, 14, 23, 26, 27] the Merlin shows similar results in sensitivity and specificity, and shares the same problems, such as the underestimation of the RDI. The values reported in these studies are approximately between 91 and 100% for sensitivity and 86 and 100% for specificity. It is problematic to interpret sensitivity and specificity values with fixed thresholds for a screening device, since clinical findings also influence the decision of whether the subject suffers from OSAS or not. However, thresholds have been used in other publications to examine screening devices [3, 5, 9, 21, 25, 26].

In conclusion, a mild SAS with an RDI below 20/h according to automated analysis should be analyzed visually, whereas a severe OSAS with clinical symptoms and an RDI above 20/h in automated analysis can be sufficiently well detected by automated analysis. The reliability of automated analysis using the Merlin system increases with increasing RDI. Furthermore, there should be a check for the optimal parameter setting for this ambulatory device. Although ambulatory monitoring is useful, easy to use and in most cases reliable, an exclusion of OSAS based on automated analysis alone should not be done. The diagnosis of mild OSAS should always be based on visual analysis of recordings. It is the most accurate and useful method in patients who undergo ambulatory monitoring for suspected mild SAS. Even the best software cannot replace case-oriented visual analysis by an experienced physician.


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 goto top of outline Author Contacts

Dr. I. Fietze
Department of Cardiology, Angiology and Pulmology
Medical School (Charité), Campus Mitte, Humboldt University
Luisenstrasse 13a, D–10117 Berlin (Germany)
Tel. +49 30 4505 13136, Fax +49 30 4505 13906, E-Mail ingo.fietze@charite.de


 goto top of outline Article Information

Received: Received: April 12, 2001
Accepted after revision: February 4, 2002
Number of Print Pages : 7
Number of Figures : 1, Number of Tables : 3, Number of References : 26


 goto top of outline Publication Details

Respiration (International Review of Thoracic Diseases)
Founded 1944 as ‘Schweizerische Zeitschrift für Tuberkulose und Pneumonologie’ by E. Bachmann, M. Gilbert, F. Häberlin, W. Löffler, P. Steiner and E. Uehlinger, continued 1962–1967 as ‘Medicina Thoracalis’ as of 1968 as ‘Respiration’, H. Herzog (1962–1997)
Official Journal of the European Association for Bronchology and Interventional Pulmonology

Vol. 69, No. 3, Year 2002 (Cover Date: May-June 2002)

Journal Editor: C.T. Bolliger, Cape Town
ISSN: 0025–7931 (print), 1423–0356 (Online)

For additional information: http://www.karger.com/journals/res


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Abstract

Background: Many ambulatory sleep apnea monitoring devices are equipped with software which allows an automated analysis of data as well as a visual analysis. Objective: The Merlin system which records heart rate, snoring sound, efforts, oronasal flow, body position and oxygen saturation was investigated to identify proper parameter settings for the automated analysis and to compare the automated with the visual analysis in patients with mild obstructive sleep apnea syndrome (OSAS). Sensitivity and specificity of the visual and automated analysis of ambulatory monitoring in comparison with visual polysomnographic (PSG) analysis were determined. Methods and Results: First, we tried to find the optimal parameters for the automated analysis, using 7 different settings in 17 OSAS patients. Furthermore, we applied the optimized setting to 66 OSAS patients who were admitted (age 50.9 ± 9.9 years, BMI 32.9 ± 5 kg/m2), and compared the results with the visual analysis of raw data. The patients slept for one night in the sleep laboratory with Merlin and PSG simultaneously to compare the visual and automated analysis of Merlin data with results from the visual analysis of PSG. Automated analysis leads to an underestimation of the respiratory disturbance index (RDI; p < 0.001) compared with both the visual analysis and results of PSG. Using a cutoff level of 5 apneas and hypopneas/h for the diagnosis of OSAS, the sensitivity of Merlin with the automated analysis is 40.6% and the specificity is 100%. With a cutoff level of 15/h, sensitivity and specificity rose to 91.3 and 100%, respectively, which is comparable to the visual analysis. Conclusion: Merlin is a reliable device for detection of sleep-related breathing disorders, but recordings should be analyzed visually, especially in patients with a low RDI.



 goto top of outline Author Contacts

Dr. I. Fietze
Department of Cardiology, Angiology and Pulmology
Medical School (Charité), Campus Mitte, Humboldt University
Luisenstrasse 13a, D–10117 Berlin (Germany)
Tel. +49 30 4505 13136, Fax +49 30 4505 13906, E-Mail ingo.fietze@charite.de


 goto top of outline Article Information

Received: Received: April 12, 2001
Accepted after revision: February 4, 2002
Number of Print Pages : 7
Number of Figures : 1, Number of Tables : 3, Number of References : 26


 goto top of outline Publication Details

Respiration (International Review of Thoracic Diseases)
Founded 1944 as ‘Schweizerische Zeitschrift für Tuberkulose und Pneumonologie’ by E. Bachmann, M. Gilbert, F. Häberlin, W. Löffler, P. Steiner and E. Uehlinger, continued 1962–1967 as ‘Medicina Thoracalis’ as of 1968 as ‘Respiration’, H. Herzog (1962–1997)
Official Journal of the European Association for Bronchology and Interventional Pulmonology

Vol. 69, No. 3, Year 2002 (Cover Date: May-June 2002)

Journal Editor: C.T. Bolliger, Cape Town
ISSN: 0025–7931 (print), 1423–0356 (Online)

For additional information: http://www.karger.com/journals/res


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