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Mild to Moderate Sleep Respiratory Events
Mild to Moderate Sleep Respiratory Events* One Negative Night May Not Be Enough Olivier Le Bon, MD; Guy Hoffmann, PhD; Juan Tecco, MD; Luc Staner, MD; Andre´ Noseda, MD, PhD; Isidore Pelc, MD, PhD; and Paul Linkowski, MD, PhD
Study objectives: Reports on the reproducibility of apnea-hypopnea indexes (AHIs) across sequential polysomnography (PSG) sessions are conflicting, leading to a lack of clear recommendations on the optimal use of this technique: is one night of monitoring sufficient or is a second night required in order to safely reject the diagnosis? Design: Retrospective comparison of two consecutive nights. Setting: Sleep unit of a tertiary-care facility. Patients: Two hundred forty-three subjects with suspected sleep apneas. Interventions: Two sequential PSG sessions in a sleep unit. Measurements and results: Using analysis of covariance for repeated measures, with age and body mass index as covariates and gender as a cofactor, a classic first-night effect was found for sleep variables. In addition, a night effect was demonstrated for sleep respiratory variables. Moreover, the high variability of AHIs showed that many patients had their condition diagnosed on only one of the two nights, and more often on the second night than on the first. The gain in detection by adding a second night when the results of testing on the first were negative was between 15% and 25%, according to the AHI obtained on night 1. Conclusions: Considering the disability associated with sleep apnea/hypopnea syndrome, as well as its global cost for society, the present study shows that it is worth performing two consecutive PSG sessions or at least a second one when the result of the first one is negative in all patients admitted for apnea detection. (CHEST 2000; 118:353–359) Key words: apnea-hypopnea index; first-night effect; polysomnography; sleep; sleep apnea syndrome Abbreviations: AHI ⫽ apnea-hypopnea index; ANCOVA ⫽ analysis of covariance; BMI ⫽ body mass index; FNE ⫽ first-night effect; N1 ⫽ first night; N2 ⫽ second night; nCPAP ⫽ nasal continuous positive airway pressure; NREMS ⫽ non-rapid eye movement sleep; PSG ⫽ polysomnography; REMS ⫽ rapid eye movement sleep; RL ⫽ rapid eye movement sleep latency; SAHS ⫽ sleep apnea-hypopnea syndrome; SOL ⫽ sleep-onset latency; SPT ⫽ sleep period time; SWS ⫽ slow-wave sleep; TST ⫽ total sleep time; WASO ⫽ wake time after sleep onset
on the night-to-night variability of the R eports apnea-hypopnea index (AHI), the main polysomnography (PSG) criterion used to determine the severity of the sleep apnea-hypopnea syndrome (SAHS), provide conflicting results.1–7 Thus, recommendations on the optimal use of PSG are not clear. *From the Centre Hospitalier Universitaire Brugmann (Drs. Le Bon, Hoffmann, Tecco, Noseda, and Pelc), Universite´ Libre de Bruxelles, Brussels, Belgium; Sleep Laboratory (Dr. Staner), FORENAP, Centre Hospitalier Rouffach, France; Hoˆpital Universitaire Erasme (Dr. Linkowski), Universite´ Libre de Bruxelles, Brussels, Belgium. This work was entirely funded by SOMALCPE (Brussels), a private association dedicated to the scientific study of sleep. Manuscript received August 10, 1999; revision accepted April 12, 2000. Correspondence to: Olivier Le Bon, MD, CHU Brugmann, Service de Psychiatrie, S48, Place Van Gehuchten 4, 1020 Bruxelles, Belgium; e-mail: [email protected]
A negative result for a first PSG session did not eliminate the diagnosis of SAHS in subjects presenting with various complaints,1 in samples from an elderly community,5,8,9 in subjects suspected of having SAHS,2,3 or in subjects complaining of impotence.7 However, a study of a healthy community sample4 and a study of subjects suspected of having SAHS6 concluded that one night of recording generally should suffice. The American Thoracic Society Consensus Conference on Cardio-Pulmonary Sleep Studies10 similarly concluded that “a single polysomnogram is sufficient to exclude clinically important sleep apnea.” In practice, it appears that most sleep laboratories record only one night and, in many, only the first few hours. SAHS is a major general health problem, yet it can be treated effectively when detected. Therefore, it is CHEST / 118 / 2 / AUGUST, 2000
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of interest to determine whether recording patients for only one night might lead to the underdiagnosis of a significant cohort of patients who subsequently do not benefit from the treatment they deserve. This retrospective study compared classic sleep variables and sleep respiratory events in a middleaged population presenting with a suspicion of sleep respiratory events. The study included a large number of patients with two sequential PSG recordings and examined sleep apnea parameters (AHI, microarousals, O2 saturation, maximal O2 drop, number of saturation drops, and low-heart-rate events). Gender, age, body mass index (BMI), and, when relevant, AHI were taken into consideration as cofactors or covariates.
rationale was the following: according to Belgian Social Security guidelines, sleep apnea patients may benefit from a free nCPAP treatment if they have an AHI of ⱖ 20 on one PSG recording. Thus, patients who show AHIs of ⱖ 20 on N1 can readily try nCPAP on N2. If the threshold is exceeded only on N2, patients are invited to return for another appointment for nCPAP titration. When the AHI level remains ⬍ 20, patients are referred for otorhinolaryngology surgery, maxillofacial surgery, or mandibular advancement devices, where appropriate, unless they are willing to assume the cost of purchasing or renting a nCPAP device. The patient distribution was as follows (Fig 1): among the 243 patients who were admitted, 101 had AHIs ⱖ 20 on N1. Of these 101 patients, 74 used nCPAP devices on N2 and 27 had a second normal PSG recording. All remaining patients (n ⫽ 142) had a second normal full PSG recording. Patients trying the nCPAP on N2 were not suitable for the comparison of sleep and respiratory parameters between the two nights and were not included in these calculations. PSG
Materials and Methods Patients Two hundred forty-three patients were admitted to the Brugmann Hospital Sleep Unit between 1992 and 1998 for the exclusion of SAHS. They presented with excessive daytime sleepiness, fatigue, snoring, or a description by their spouse of respiratory interruptions during sleep. They were referred by pneumology, ear-nose-throat, or sleep disorders outpatient clinics or were self-referred. There were no exclusion criteria, since the object was to describe the sample in a natural way. Patients were required to be free of psychotropic medications for the 2 weeks prior to PSG. All patients admitted to the sleep unit were recorded for two consecutive nights. If an AHI threshold of ⱖ 20 was exceeded on the first night (N1), a trial of nasal continuous positive airway pressure (nCPAP) was carried out on the second night (N2), according to device availability and patient consent. The remaining patients were recorded on N2 to observe whether they would exceed the AHI threshold or to consolidate their results if the threshold already had been exceeded on N1 but they did not wish to try a nCPAP trial at that time or no device was available. The
The sleep unit is located in a pleasant, old refurbished one-story building dedicated solely to sleep testing. The five individual rooms (size, 25 m2) are practically identical and include a window with a view of a park, a small bathroom with toilet, a comfortable bed, an armchair, a chair, a table, and a computer for psychological testing, when needed. The rooms are reasonably soundproof, with thick walls and double glass, and are located in the heart of a pavilion-style hospital campus where few cars are admitted. Patients can adjust the lighting using a light dimmer and dark curtains. According to a recent inquiry, 94% of all of our patients come from the Brussels area or its immediate surroundings (maximum distance, 20 km from home). Recordings were performed for two consecutive nights between Mondays and Wednesdays or between Wednesdays and Fridays. Patients were prepared for the recordings between 10:00 and 11:00 pm and were allowed to retire when they wished (goodnight time). They were awakened around 7:00 am, had they not arisen spontaneously (good morning time). PSG involved an electroencephalogram, recording from the FZp1-A1, C4-A1, and O2-A1 sites, with electrooculogram, and submental and anterior tibial electromyograms. Oral and nasal airflow using thermoresistors at the nose and the mouth, respiratory effort via thoracic and abdominal belts, and arterial oxygen saturation were re-
Figure 1. Study design for N2: (a) all patients are admitted for the detection of sleep respiratory disorders (a second PSG session immediately followed N1 in all cases); (b) patients who showed an AHI ⱖ 20 on N1; (c) patients used their N2 session to test the nCPAP device; (d) for patients who refused the nCPAP trial or for whom no nCPAP device was available, a second PSG recording was performed for further evaluation; (e) no difference in AHI was observed statistically between (c) and (d) on N1; (f) for patients with AHIs ⬍ 20 on N1, a second PSG recording again was performed for further evaluation; (g) the comparisons between the two PSG sessions were performed for all patients who did not use a nCPAP device on N2; and (h) calculations on the increase in diagnostic precision gained by adding a recording on N2 included data for the patients using the nCPAP on N2 who had already had their condition diagnosed on the basis of N1 recordings alone. 354
Clinical Investigations
corded on both nights. Body position was encoded in eight categories: supine, lateral (left and right), lateral-prone (left and right), lateral-supine (left and right), and sitting. Encoding for the sitting position was added for the supine group. Encoding for the lateral position included all other positions. Recordings were randomly analyzed by one of two well-trained technicians, on a 21-inch screen (Alice; Respironics; Plattsburgh, PA) displaying 30-s polysomnograph epochs, except for microarousal detection, which was always performed by the same person. As demonstrated in another study,11 interrater reliability () exceeded 0.90 for all scored sleep variables. Classic criteria were used for sleep-stage scoring.12 Visual scoring was performed in the following three steps: (1) determination of sleep stages; (2) detection and quantification of respiratory sleep events and periodic limb movements; and (3), added in 1996, the detection and quantification of microarousals. Sleep-onset latency (SOL) was defined as the time between lights out and the first period of stage 2. Wake time did not include sleep latency (wake time after sleep onset [WASO]). Sleep efficiency was defined as total sleep time (TST) divided by time in bed. Non-rapid eye movement sleep (NREMS) included sleep stages 1 to 4. Rapid eye movement sleep (REMS) latency (RL) was defined as the time between the first epoch of stage 2 and the first epoch of REMS. An episode of apnea was defined as a ⬎ 80% reduction in airflow for at least 10 s during sleep. A hypopneic episode was defined as a 50 to 80% reduction of airflow amplitude accompanied either by a reduction in oxygen saturation of ⱖ 3% or by an arousal. In a modification of the criteria established by Bonnet et al,13 microarousals were considered present only when associated with increases in electromyogram tonus. Respiratory microarousals were defined as arousals that immediately followed a respiratory event. Statistical Analysis SOL, RL, WASO, and apnea scores and indexes were logtransformed to reach normal distributions and were used in that form in all statistical analyses. Raw data were used for staging and classification. Between-group comparisons were computed using Student’s t test for unpaired series. Stepwise linear regression was used for dependent ratio measures, and logistic regression was used for binary outcomes. Analysis of covariance (ANCOVA) was used for repeated measures, with gender as a cofactor, and AHI, BMI, and age were used as covariates when appropriate. One type of computer software (SPSS, version 6.1; SPSS Inc; Chicago, IL) was used for regression analyses and ANCOVA, and another (StatView, version 5.0; SAS Institute; Cary, NC) was used for stratifications and Bland-Altman plots.
Results Two hundred forty-three patients entered the study (mean [⫾ SD] age, 48.4 ⫾ 11.9; men, 179 [74%]; mean BMI, 28.7 ⫾ 5.8). One hundred one patients had AHIs ⱖ 20 on N1, and 74 of them tried an nCPAP device on N2. Unpaired t tests performed between patients with AHIs ⬎ 20 who underwent a nCPAP trial (n ⫽ 74) and those who did not (n ⫽ 27) showed no significant difference in AHIs on N1. Only the subgroup of 169 patients who did not use a nCPAP device on N2 (mean age, 47.2 ⫾ 12.1; men, 113 [67%]; mean BMI, 27.4 ⫾ 5.5) was considered for sleep and respiratory night-to-night (N1 vs N2) comparisons.
Regression analyses on N1 data in this subgroup (n ⫽ 169), using age as a dependent variable, were significant for AHI (p ⫽ 0.003), sleep efficiency (p ⫽ 0.004), and SOL (p ⫽ 0.021). The same analyses using BMI as a dependent variable showed a significant relationship with AHI (p ⫽ 0.009). Using AHI as dependent variable, significant relationships were found for the number of awakenings (p ⫽ 0.001), gender (p ⫽ 0.001), age (p ⫽ 0.011), and BMI (p ⫽ 0.0471). Logistic regression using gender as a dependent variable showed a significant relationship with AHI (p ⫽ 0.028) and slow-wave sleep (SWS) (p ⫽ 0.012). Data for N2 were largely comparable. Due to the significant relationships described above, gender was introduced as a cofactor in all analyses. Age, BMI, and AHI were introduced as covariates in the ANCOVA of sleep variables. Age and BMI were introduced as covariates for sleep respiratory variables. Selected sleep variables are presented in Table 1. The comparison between N1 and N2 recordings indicates a clear classic first-night effect (FNE) with shorter sleep period time (SPT) and TST, less sleep efficiency, longer SOL, more WASO, higher awakening index, less REMS time, and a longer RL on N1 compared to N2. NREMS measures (NREMS and SWS) and stage-shifts indexes also were decreased on N1. Nonrespiratory microarousals showed a significant decrease between N1 and N2, whereas respiratory microarousal indexes were not significantly different. To allow comparison with previous reports, the same calculations were performed using only patients with AHIs ⱖ 5 on either N1 or N2 (n ⫽ 116); outcomes were comparable to analyses of the overall sample (data not shown). In order to ascertain its potential influence on night-to-night variation, body position was measured and was not found to be significantly different between the two nights. Table 2 presents data on sleep respiratory events. The first PSG recording showed significantly fewer severe indexes of obstructive apnea, total apnea, hypopnea, and combined apnea-hypopnea. The levels of mean O2 saturation and maximum O2 drop were stable across nights. There were fewer instances of desaturation of ⱖ 3% in absolute number on N1, but the index of desaturations of ⱖ 3% showed fewer desaturations on N2. The frequency of low heart rate was stable across nights. Again, to allow comparisons with other studies, the same calculations were performed only on patients with AHIs ⱖ 5 on either N1 or N2 (n ⫽ 116). Comparable results were obtained for hypopneas and total indexes, but apnea indexes were no longer significantly different between N1 and N2 (data not CHEST / 118 / 2 / AUGUST, 2000
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Table 1—Selected Sleep Measures (n ⴝ 169)* Measures
N1
N2
p Value†
TIB, min SPT, min TST, min Efficiency Sleep latency, min‡ Stage shifts, index/h WASO, min‡ Awakenings, index/h Nonrespiratory microarousals, index/h§ Respiratory microarousals, index/h§ NREMS, min SWS, min REMS, min RL, min‡ Body position, min Supine Lateral
434.8 (52.4) 385.9 (82.2) 308.6 (87.0) 71.9 (18.2) 41.0 (49.8) 37.7 (29.8) 73.2 (60.7) 7.9 (8.7) 36.7 (20.3) 7.8 (11.9) 270.8 (73.6) 37.9 (33.3) 42.5 (32.5) 95.5 (85.7)
443.9 (37.8) 407.3 (45.3) 340.1 (62.6) 77.9 (13.1) 31.6 (29.6) 33.5 (19.7) 64.8 (55.9) 6.2 (6.5) 28.9 (14.9) 10.8 (11.8) 291.6 (57.7) 42.2 (34.2) 49.9 (30.1) 88.0 (69.6)
NS 0.006 0.001 0.001 0.015 0.019 0.002 0.019 0.0351 NS 0.001 0.029 0.002 0.040
182.9 (136.1) 251.3 (148.8)
199.7 (145.2) 242.1 (152.6)
NS NS
*Values given as mean (SD). TIB ⫽ time in bed; NS ⫽ not significant. †ANCOVA for repeated measures, with gender as a cofactor, and age, BMI, and AHI (on N1) as covariates. ‡Log-transformed values. §Starting in 1996, n ⫽ 89.
shown). The correlation between N1 and N2 for AHI was highly significant (r ⫽ 0.770; p ⫽ 0.0001). Table 3 displays the distribution of AHI by 5-point intervals from 0 to 20 across the two nights. Respiratory microarousal indexes increased with each increasing AHI interval, paralleling the evolution of AHI. The total number of patients who shifted upward in AHI interval from N1 to N2 (n ⫽ 62) is almost double the number who shifted downward
(n ⫽ 32). This finding underscores the larger proportion of subjects having more severe respiratory events on N2. Bland-Altman plots14 were performed to assess the observed test-retest variability of AHIs between the two nights. A positive correlation between the mean of the two measurements and the difference between them would indicate that the differences observed between AHIs on N1 and N2 increased
Table 2—Sleep Cardiorespiratory Variables (n ⴝ 169)* N1
N2
Variables
Absolute No.
Index
Absolute No.
Index
p Value†
Central apneas Obstructive apneas Mixed apneas Total apneas REMS NREMS Hypopneas REMS NREMS Total apneas/hypopneas REMS NREMS Mean O2 saturation Max O2 saturation drop O2 desaturations ⬎ 3% Low heart rate
2.6 (7.6) 17.4 (37.4) 2.3 (6.5) 19.9 (40.2) 4.2 (11.5) 17.7 (37.8) 39.6 (38.2) 9.3 (11.2) 30.2 (32.6) 59.8 (65.4) 13.5 (17.9) 47.9 (59.6) 93.2 (4.4) 6.5 (7.0) 11.2 (39.1) 7.2 (50.7)
0.50 (1.4) 3.7 (8.7) 0.51 (1.6) 4.2 (9.3) 0.8 (2.1) 3.9 (9.2) 7.9 (8.6) 1.6 (1.9) 6.2 (7.9) 12.3 (14.7)‡ 2.5 (3.1) 3.9 (9.2)
4.1 (10.5) 24.1 (49.5) 4.0 (10.5) 28.3 (54.0) 6.0 (12.7) 26.4 (55.6) 57.5 (51.9) 13.5 (14.7) 43.6 (45.9) 85.5 (90.6) 19.5 (21.6) 69.7 (88.6) 93.3 (4.5) 9.8 (7.4) 15.7 (48.6) 8.1 (36.2)
0.75 (1.9) 4.7 (10.7) 0.72 (1.9) 5.4 (11.8) 1.0 (2.2) 5.1 (12.2) 10.2 (8.9) 2.3 (2.5) 7.8 (8.0) 15.5 (17.4)‡ 3.3 (3.7) 5.1 (12.2)
NS 0.033 NS 0.022 NS 0.029 0.005 0.005 0.023 0.001 0.004 0.005 NS NS 0.010 NS
5.4 (36.4) 1.2 (8.5)
3.5 (14.1) 1.3 (6.1)
*Values given as mean (SD). See Table 1 for abbreviations not in text. All apnea and hypopnea variables were log-transformed. ANCOVA for repeated values was performed using gender as a cofactor, with age and BMI as covariates. †ANCOVA performed on indexes, except for mean O2 saturation and maximal O2 saturation drop, where indexes did not make sense. ‡AHI. 356
Clinical Investigations
Table 3—Descriptive Stratification of AHI and Respiratory Microarousals Values, and Changes Between AHI Interval From Night to Night (n ⴝ 169)* N1
Interval Change, No.§
N2
AHI
No. (%)†
AHI (SD)
RMI (SD)‡
⬍5 05–10 10–15 15–20 ⱖ 20 Total Mean
57 (33.7) 48 (28.4) 20 (11.8) 17 (10.1) 27 (16.0) 169 (100)
1.8 (1.4) 7.3 (1.4) 11.8 (1.2) 17.5 (1.6) 40.3 (20.1)
1.4 (1.8) 5.9 (3.5) 9.4 (6.1) 15.4 (7.6) 33.3 (25.2)
12.3 (14.7)
7.8 (11.9)
No. (%)†
AHI (SD)
RMI (SD)‡
44 (26.0) 41 (24.3) 24 (14.2) 15 (8.9) 45 (26.6) 169 (100)
2.2 (1.6) 6.8 (1.2) 12.2 (1.4) 17.0 (1.0) 38.7 (22.8)
4.0 (4.9) 5.7 (4.7) 12.4 (7.3) 32.6 (16.7) 28.9 (16.1)
15.5 (17.4)
10.8 (11.8)
Up 28 21 8 5 62
Down
r Value㛳
11 7 7 7 32
0.940 0.965 0.962 0.885 0.490 0.291
*RMI ⫽ respiratory microarousal index (per TST). †Percentages represent the fraction of the total number of subjects by interval (N1 and N2). Raw data were used. ‡Starting in 1996, n ⫽ 89. §Up is from the corresponding interval to any higher interval; Down is from the corresponding interval to any lower interval. 㛳Bland-Altman plot. The average between AHI for N1 and AHI for N2 is plotted against the difference between the two measurements, according to the AHI interval in N1.
with the magnitude of the measurement. For the whole group, r ⫽ 0.291 (p ⫽ 0.0001; 95% confidence interval, 0.146 to 0.420; R2 ⫽ 0.085), indicating a weak positive relationship. Outcomes of the plots by AHI interval for N1 are given in Table 3. The plot then was analyzed with only patients having AHIs ⬍ 20 on N1, in order to measure this correlation only among the patients with lower AHIs on N1, and the correlation was stronger than in the whole group, as r ⫽ 0.560 (p ⫽ 0.0001; 95% confidence interval, 0.435 to 663; R2 ⫽ 0.313). Subsequent analyses then were performed to assess whether a prediction could be made about patients who had AHIs ⬍ 20 on N1 (n ⫽ 142) and then crossed the threshold of AHI ⱖ 20 on N2. First, patients with AHIs ⬍ 20 on N1 and ⱖ 20 on N2 (n ⫽ 25) were compared by unpaired t tests with those having AHIs ⬍ 20 on N2 (n ⫽ 117) for sleep and respiratory variables. No sleep variable was associated with changing from the low-AHI group to the high-AHI group on N2. Only a higher AHI on N1 (9.3 ⫾ 5.9 vs 6.5 ⫾ 5.2) was found to be associated (p ⫽ 0.0191) with a change to AHI ⱖ 20 on N2. Second, the patients with AHIs ⬍ 20 on N1 and AHIs ⱖ 20 on N2 were spread equally among all ranges of AHI for N1: six patients had AHIs ⬍ 5; eight had AHIs between 5 and 10; six had AHIs between 10 and 15); and five had AHIs between 15 and 20). In order to eliminate the potential influence of poor sleep quality on N1, only those patients who had SPTs of ⱖ 360 min were considered in a consecutive analysis. The results from the ANCOVA for AHI and total apneas/hypopneas and for the changes in AHI interval were almost identical to those for the whole group (data not shown). Again, patients with
AHIs ⬍ 20 on N1 and ⱖ 20 on N2 (n ⫽ 97) were compared with those patients with AHIs ⬍ 20 on N1 who maintained AHIs ⬍ 20 on N2. There was no significant difference between these two groups for any of the sleep variables. Only a higher AHI on N1 (10.0 ⫾ 6.1 vs 6.6 ⫾ 5.1) was associated with changing to an AHI ⱖ 20 on N2 (p ⫽ 0.0119). Table 4 presents, for each 5-point increase in AHI cutoff, the diagnostic sensitivity data for N1 alone, N2 alone (which corresponds to a PSG immediately following an habituation night), and the combination of N1 and N2. The diagnostic sensitivity increases by 12% for AHI ⱖ 5 and to 67% for AHI ⱖ 20 when using an habituation night over N1 alone. Using a second PSG recording when the results of the first were negative (from the point of view of AHI detection at a given threshold) on N1 alone, showed increases in test sensitivity varying from 25% (AHI, ⱖ 5) to 92% (AHI, ⱖ 20). To obtain the diagnostic sensitivity increases for the overall sample (n ⫽ 243), the 74 patients who had already had their condition diagnosed according to N1 results and had had an CPAP trial on N2 must be considered. For those patients, the following increases in diagnostic sensitivity were less dramatic, although still quite substantial: 7% (AHI, ⱖ 5); 14% (AHI, ⱖ 10); 14% (AHI, ⱖ 15); 18% (AHI, ⱖ 20) for N2 with a prior habituation night; 15% (AHI ⱖ 5); 23% (AHI, ⱖ 10); 23% (AHI, ⱖ 15); and 25% (AHI, ⱖ 20) for N2 when N1 is negative.
Discussion In this comparison of two sequential nights of PSG recordings in patients suspected of SAHS, a typical CHEST / 118 / 2 / AUGUST, 2000
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Table 4 —Diagnostic Sensitivity Comparisons (n ⴝ 169)* N1 Alone
N2 Alone
N1 or N2†
N2 With Habituation‡
AHI
No. (%)
No. (%)
No. (%)
No. (%)
Increase in Test Sensitivity vs N1 Alone, %
ⱖ 5 ⱖ 10 ⱖ 15 ⱖ 20
112 (66.2) 64 (37.8) 44 (26.0) 27 (15.9)
125 (73.9) 84 (49.7) 60 (35.5) 45 (26.6)
140 (82.8) 96 (56.8) 71 (42.0) 52 (30.7)
13 (7.6) 20 (11.8) 16 (9.4) 18 (10.6)
11.6 31.1 36.3 66.6
N2⫹ when N1⫺§ No. (%)
Increase in Test Sensitivity vs N1 Alone, %
28 (16.5) 32 (18.9) 27 (15.9) 25 (14.7)
25.0 50.0 61.1 92.5
*⫹ ⫽ positive; ⫺ ⫽ negative. †Conditions diagnosed on either one of two consecutive PSG sessions. ‡Increase in patients whose conditions were diagnosed using N2 data on an habituation night. §Increase in patients whose conditions were diagnosed by using a second PSG session when threshold AHI was not reached on N1.
FNE was found, including a reduction of NREMS and stage-shift values, which are less consistently observed in studies on FNEs. Though a partial FNE has been observed before in patients evaluated for possible SAHS, this is the first time that a full FNE clearly has been demonstrated, taking into account the potential influences of age, BMI, and AHI. Similarly, sleep respiratory events, measured by their indexes to eliminate the influence of TST, also were associated with an FNE, since most AHIs were reduced on the N1 PSG recording compared to that for N2. A slight difference in the mean AHIs for N1 and N2 has been demonstrated previously.5 BlandAltman tests plots confirmed that the AHIs obtained for the two nights differed significantly for all intervals of AHI. This difference between the two nights was also evident for microarousals; nonrespiratory microarousals were significantly more frequent on N1, whereas respiratory microarousal indexes showed nonsignificant differences. Interestingly, more severe AHIs were present when sleep quality was better, which is rather counterintuitive. This illustrates the complex relationships among sleep, respiratory function, and FNE. The differences observed between the two nights were found at all four 5-point AHI intervals. In all cases, PSG recordings on N2 were more efficient in detecting patients with sleep apneas than were those on N1, which is what would occur with an N1 recording immediately following a habituation night. The most efficient approach, however, would be to perform a second PSG recording when the results of the first one are negative. The search for predictors of which patients having an AHI ⬍ 20 on N1 would have an AHI ⱖ 20 on N2 was almost entirely fruitless. First, the only variable that was associated with the change was a small increment in AHI on N1. However, as the patients were equally spread over the four AHI intervals on N1, no efficient prediction could be made about what level of AHI they would attain on N2. Though 358
we hypothesized that differences in sleeping position between the two nights could have been associated with different AHI outcomes, no difference in sleep position patterns was observed between nights. Thus, it is unlikely that this factor played an important role in the FNE observed here. Third, waking the patients at a time bound to hospital routine could have artificially reduced the sleep time on N1, when the patients were getting accustomed to the new environment, vs that on N2. However, all the respiratory data were computed as indexes, which allowed for comparisons between different sleep times. Furthermore, analyses of a subgroup of the patients with SPTs ⬎ 360 min provided the same results as in the overall group. Fourth, studies have shown that improving the environment of the room or studying patients at home could reduce night-to-night variations.15,16 However, a large study performed by our group on healthy control subjects (unpublished data) does not support this hypothesis, since classic FNEs were found in a comparable number of subjects as those found in sleep laboratory settings. Considering the above, the reasons why N2 provided a better detection of sleep respiratory events seem unclear at present and need to be studied in the context of the complex phenomena of FNEs in general. The fact that a negative result on N1 does not necessarily exclude SAHS has been described by many authors, but the percentage of patients misdiagnosed in a N1 PSG recording has varied considerably, from 43%,8 to 32%,7 to 23%,5 to 17%,4 to 15%,17 to 9%.6 These results cannot be compared easily, however, since different populations and different diagnostic cutoff points were used. Moreover, the sensitivity of a test is a function of the composition of the group selected, which varied substantially in these studies. In addition, the frequency of the event that the test is measuring is not known with certainty, since apneas possibly could appear only on a later night that has not yet been recorded. Clinical Investigations
The results and conclusions presented here diverge significantly with the largest published study on a comparable group of subjects,6 in which no FNE was demonstrated on respiratory variables and the night-to-night variability did not influence diagnosis significantly. Patients in that study had a very high mean AHI (51.7) on N1, a score that is far superior to that in our group (12.3). In the study by Mendelson,6 patients were self-selected to contact the sleep center, perhaps creating a selection bias toward severely affected subjects. Second, the methodology differed; only patients presenting with AHIs ⱖ 5 on either N1 or N2 were analyzed by paired t tests in that study, while we used an ANCOVA with AHI, BMI, and age as covariates and gender as a cofactor. Analyses of our patients presenting with AHIs ⱖ 5 replicated the analyses of the entire sample, however. Finally, we benefited here from a larger group of patients. In terms of criteria, we used data from the worst night, that is, the night with the highest AHI index, for diagnosis. An alternative approach could be to use the mean of the two nights, or N2 alone, or a combination of variables, but, presently, there are no guidelines as to which approach would be best correlated with good clinical outcome. The rationale used here was that significant morbidity due to SAHS, such as accidents related to excessive daytime sleepiness, is more likely to occur immediately following a night with many respiratory events, and, hence, we preferred to capture the full severity of the syndrome by using the worst night for diagnosis. This study has the usual limitations of retrospective protocols, such as the relatively loose definition of the studied group. However, most findings were homogeneous among all AHI intervals, showing a robust inner stability. A second limitation is that only two nights were recorded when it is likely that, given the large variability observed, a few more cases of SAHS would have appeared with subsequent PSG recordings. Data on the consumption of alcohol or caffeine were not available. In conclusion, the present study demonstrates a classic FNE in a population of patients suspected of sleep respiratory disorders. It confirms the high night-to-night variability of AHIs and microarousal indexes. An important number of subjects presented false-negative results on N1, which turned out to be more frequent among severe cases. The major health and economic implications of SAHS,18 as well as the consequences of missing the diagnosis, underscore
the need for a second PSG recording when the results on N1 are negative. ACKNOWLEDGMENT: The authors thank Anita Bessemans and Marleen Bocken for their meticulous scoring of PSG sessions.
References 1 Wittig RM, Romaker A, Zorick FJ, et al. Night-to-night consistency of apneas during sleep. Am Rev Respir Dis 1984; 129:244 –246 2 Dean RJ, Chaudhary BA. Negative polysomnogram in patients with obstructive sleep apnea syndrome. Chest 1992; 101;105–108 3 Meyer TJ, Eveloff SE, Kline LR, et al. One negative polysomnogram does not exclude obstructive sleep apnea. Chest 1993; 3:756 –760 4 Lord S, Sawyer B, O’Connell D, et al. Night-to-night variability of disturbed breathing during sleep in an elderly community sample. Sleep 1991; 14:252–258 5 Bliwise DL, Benkert RE, Ingham RH. Factors associated with nightly variability in sleep-disordered breathing in the elderly. Chest 1991; 100;4:973–976 6 Mendelson WB. Use of the sleep laboratory in suspected sleep apnea syndrome: is one night enough? Cleve Clin J Med 1994; 61:299 –303 7 Chediack AD, Acevedo-Crespo JC, Seiden DJ, et al. Nightly variability in the indices of sleep-disordered breathing in men being evaluated for impotence with consecutive night polysomnograms. Sleep 1996; 19:589 –592 8 Mosko SS, Dickel MJ, Ashurst J. Night-to-night variability in sleep apnea and sleep-related periodic limb movements in the elderly. Sleep 1988; 11:340 –348 9 Aber WR, Block AJ, Hellard DW, et al. Consistency of respiratory measurements from night-to-night during the sleep of elderly men. Chest 1989; 96:747–751 10 American Thoracic Society Consensus Conference on Cardio-Pulmonary Sleep Studies. Indications and standards for cardiopulmonary sleep studies. Am Rev Respir Dis 1969; 139:559 –568 11 Le Bon O, Verbanck P, Hoffmann G, et al. Sleep in detoxified alcoholics: impairment of most standard sleep parameters and increased risk for sleep apnea, but not for myoclonias; a controlled study. J Stud Alcohol 1997; 58:30 –36 12 Rechtschaffen A, Kales A, eds. A manual of standardized terminology techniques and scoring system for sleep states of human subjects. Washington DC: US Govt Printing Office, 1968 13 Bonnet M, Carley D, Carskadon M, et al. EEG arousals: scoring rules and examples. Sleep 1992; 15:173–184 14 Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1:307–310 15 Coble P, McPartland RJ, Silva WJ, et al. Is there a first-night effect? (a revisit). Biol Psychiatry 1974; 9:215–219 16 Browman CP, Cartwright RD. The first-night effect on sleep and dreams. Biol Psychiatry 1980; 15:809 – 812 17 Kramer M, Silva C. Night-to-night variability of apneas [abstract]. Sleep Res 1986; 15:138 18 Leger D. The cost of sleepiness. Sleep 1995; 18:281–284
CHEST / 118 / 2 / AUGUST, 2000
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Study objectives: Reports on the reproducibility of apnea-hypopnea indexes (AHIs) across sequential polysomnography (PSG) sessions are conflicting, leading to a lack of clear recommendations on the optimal use of this technique: is one night of monitoring sufficient or is a second night required in order to safely reject the diagnosis? Design: Retrospective comparison of two consecutive nights. Setting: Sleep unit of a tertiary-care facility. Patients: Two hundred forty-three subjects with suspected sleep apneas. Interventions: Two sequential PSG sessions in a sleep unit. Measurements and results: Using analysis of covariance for repeated measures, with age and body mass index as covariates and gender as a cofactor, a classic first-night effect was found for sleep variables. In addition, a night effect was demonstrated for sleep respiratory variables. Moreover, the high variability of AHIs showed that many patients had their condition diagnosed on only one of the two nights, and more often on the second night than on the first. The gain in detection by adding a second night when the results of testing on the first were negative was between 15% and 25%, according to the AHI obtained on night 1. Conclusions: Considering the disability associated with sleep apnea/hypopnea syndrome, as well as its global cost for society, the present study shows that it is worth performing two consecutive PSG sessions or at least a second one when the result of the first one is negative in all patients admitted for apnea detection. (CHEST 2000; 118:353–359) Key words: apnea-hypopnea index; first-night effect; polysomnography; sleep; sleep apnea syndrome Abbreviations: AHI ⫽ apnea-hypopnea index; ANCOVA ⫽ analysis of covariance; BMI ⫽ body mass index; FNE ⫽ first-night effect; N1 ⫽ first night; N2 ⫽ second night; nCPAP ⫽ nasal continuous positive airway pressure; NREMS ⫽ non-rapid eye movement sleep; PSG ⫽ polysomnography; REMS ⫽ rapid eye movement sleep; RL ⫽ rapid eye movement sleep latency; SAHS ⫽ sleep apnea-hypopnea syndrome; SOL ⫽ sleep-onset latency; SPT ⫽ sleep period time; SWS ⫽ slow-wave sleep; TST ⫽ total sleep time; WASO ⫽ wake time after sleep onset
on the night-to-night variability of the R eports apnea-hypopnea index (AHI), the main polysomnography (PSG) criterion used to determine the severity of the sleep apnea-hypopnea syndrome (SAHS), provide conflicting results.1–7 Thus, recommendations on the optimal use of PSG are not clear. *From the Centre Hospitalier Universitaire Brugmann (Drs. Le Bon, Hoffmann, Tecco, Noseda, and Pelc), Universite´ Libre de Bruxelles, Brussels, Belgium; Sleep Laboratory (Dr. Staner), FORENAP, Centre Hospitalier Rouffach, France; Hoˆpital Universitaire Erasme (Dr. Linkowski), Universite´ Libre de Bruxelles, Brussels, Belgium. This work was entirely funded by SOMALCPE (Brussels), a private association dedicated to the scientific study of sleep. Manuscript received August 10, 1999; revision accepted April 12, 2000. Correspondence to: Olivier Le Bon, MD, CHU Brugmann, Service de Psychiatrie, S48, Place Van Gehuchten 4, 1020 Bruxelles, Belgium; e-mail: [email protected]
A negative result for a first PSG session did not eliminate the diagnosis of SAHS in subjects presenting with various complaints,1 in samples from an elderly community,5,8,9 in subjects suspected of having SAHS,2,3 or in subjects complaining of impotence.7 However, a study of a healthy community sample4 and a study of subjects suspected of having SAHS6 concluded that one night of recording generally should suffice. The American Thoracic Society Consensus Conference on Cardio-Pulmonary Sleep Studies10 similarly concluded that “a single polysomnogram is sufficient to exclude clinically important sleep apnea.” In practice, it appears that most sleep laboratories record only one night and, in many, only the first few hours. SAHS is a major general health problem, yet it can be treated effectively when detected. Therefore, it is CHEST / 118 / 2 / AUGUST, 2000
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of interest to determine whether recording patients for only one night might lead to the underdiagnosis of a significant cohort of patients who subsequently do not benefit from the treatment they deserve. This retrospective study compared classic sleep variables and sleep respiratory events in a middleaged population presenting with a suspicion of sleep respiratory events. The study included a large number of patients with two sequential PSG recordings and examined sleep apnea parameters (AHI, microarousals, O2 saturation, maximal O2 drop, number of saturation drops, and low-heart-rate events). Gender, age, body mass index (BMI), and, when relevant, AHI were taken into consideration as cofactors or covariates.
rationale was the following: according to Belgian Social Security guidelines, sleep apnea patients may benefit from a free nCPAP treatment if they have an AHI of ⱖ 20 on one PSG recording. Thus, patients who show AHIs of ⱖ 20 on N1 can readily try nCPAP on N2. If the threshold is exceeded only on N2, patients are invited to return for another appointment for nCPAP titration. When the AHI level remains ⬍ 20, patients are referred for otorhinolaryngology surgery, maxillofacial surgery, or mandibular advancement devices, where appropriate, unless they are willing to assume the cost of purchasing or renting a nCPAP device. The patient distribution was as follows (Fig 1): among the 243 patients who were admitted, 101 had AHIs ⱖ 20 on N1. Of these 101 patients, 74 used nCPAP devices on N2 and 27 had a second normal PSG recording. All remaining patients (n ⫽ 142) had a second normal full PSG recording. Patients trying the nCPAP on N2 were not suitable for the comparison of sleep and respiratory parameters between the two nights and were not included in these calculations. PSG
Materials and Methods Patients Two hundred forty-three patients were admitted to the Brugmann Hospital Sleep Unit between 1992 and 1998 for the exclusion of SAHS. They presented with excessive daytime sleepiness, fatigue, snoring, or a description by their spouse of respiratory interruptions during sleep. They were referred by pneumology, ear-nose-throat, or sleep disorders outpatient clinics or were self-referred. There were no exclusion criteria, since the object was to describe the sample in a natural way. Patients were required to be free of psychotropic medications for the 2 weeks prior to PSG. All patients admitted to the sleep unit were recorded for two consecutive nights. If an AHI threshold of ⱖ 20 was exceeded on the first night (N1), a trial of nasal continuous positive airway pressure (nCPAP) was carried out on the second night (N2), according to device availability and patient consent. The remaining patients were recorded on N2 to observe whether they would exceed the AHI threshold or to consolidate their results if the threshold already had been exceeded on N1 but they did not wish to try a nCPAP trial at that time or no device was available. The
The sleep unit is located in a pleasant, old refurbished one-story building dedicated solely to sleep testing. The five individual rooms (size, 25 m2) are practically identical and include a window with a view of a park, a small bathroom with toilet, a comfortable bed, an armchair, a chair, a table, and a computer for psychological testing, when needed. The rooms are reasonably soundproof, with thick walls and double glass, and are located in the heart of a pavilion-style hospital campus where few cars are admitted. Patients can adjust the lighting using a light dimmer and dark curtains. According to a recent inquiry, 94% of all of our patients come from the Brussels area or its immediate surroundings (maximum distance, 20 km from home). Recordings were performed for two consecutive nights between Mondays and Wednesdays or between Wednesdays and Fridays. Patients were prepared for the recordings between 10:00 and 11:00 pm and were allowed to retire when they wished (goodnight time). They were awakened around 7:00 am, had they not arisen spontaneously (good morning time). PSG involved an electroencephalogram, recording from the FZp1-A1, C4-A1, and O2-A1 sites, with electrooculogram, and submental and anterior tibial electromyograms. Oral and nasal airflow using thermoresistors at the nose and the mouth, respiratory effort via thoracic and abdominal belts, and arterial oxygen saturation were re-
Figure 1. Study design for N2: (a) all patients are admitted for the detection of sleep respiratory disorders (a second PSG session immediately followed N1 in all cases); (b) patients who showed an AHI ⱖ 20 on N1; (c) patients used their N2 session to test the nCPAP device; (d) for patients who refused the nCPAP trial or for whom no nCPAP device was available, a second PSG recording was performed for further evaluation; (e) no difference in AHI was observed statistically between (c) and (d) on N1; (f) for patients with AHIs ⬍ 20 on N1, a second PSG recording again was performed for further evaluation; (g) the comparisons between the two PSG sessions were performed for all patients who did not use a nCPAP device on N2; and (h) calculations on the increase in diagnostic precision gained by adding a recording on N2 included data for the patients using the nCPAP on N2 who had already had their condition diagnosed on the basis of N1 recordings alone. 354
Clinical Investigations
corded on both nights. Body position was encoded in eight categories: supine, lateral (left and right), lateral-prone (left and right), lateral-supine (left and right), and sitting. Encoding for the sitting position was added for the supine group. Encoding for the lateral position included all other positions. Recordings were randomly analyzed by one of two well-trained technicians, on a 21-inch screen (Alice; Respironics; Plattsburgh, PA) displaying 30-s polysomnograph epochs, except for microarousal detection, which was always performed by the same person. As demonstrated in another study,11 interrater reliability () exceeded 0.90 for all scored sleep variables. Classic criteria were used for sleep-stage scoring.12 Visual scoring was performed in the following three steps: (1) determination of sleep stages; (2) detection and quantification of respiratory sleep events and periodic limb movements; and (3), added in 1996, the detection and quantification of microarousals. Sleep-onset latency (SOL) was defined as the time between lights out and the first period of stage 2. Wake time did not include sleep latency (wake time after sleep onset [WASO]). Sleep efficiency was defined as total sleep time (TST) divided by time in bed. Non-rapid eye movement sleep (NREMS) included sleep stages 1 to 4. Rapid eye movement sleep (REMS) latency (RL) was defined as the time between the first epoch of stage 2 and the first epoch of REMS. An episode of apnea was defined as a ⬎ 80% reduction in airflow for at least 10 s during sleep. A hypopneic episode was defined as a 50 to 80% reduction of airflow amplitude accompanied either by a reduction in oxygen saturation of ⱖ 3% or by an arousal. In a modification of the criteria established by Bonnet et al,13 microarousals were considered present only when associated with increases in electromyogram tonus. Respiratory microarousals were defined as arousals that immediately followed a respiratory event. Statistical Analysis SOL, RL, WASO, and apnea scores and indexes were logtransformed to reach normal distributions and were used in that form in all statistical analyses. Raw data were used for staging and classification. Between-group comparisons were computed using Student’s t test for unpaired series. Stepwise linear regression was used for dependent ratio measures, and logistic regression was used for binary outcomes. Analysis of covariance (ANCOVA) was used for repeated measures, with gender as a cofactor, and AHI, BMI, and age were used as covariates when appropriate. One type of computer software (SPSS, version 6.1; SPSS Inc; Chicago, IL) was used for regression analyses and ANCOVA, and another (StatView, version 5.0; SAS Institute; Cary, NC) was used for stratifications and Bland-Altman plots.
Results Two hundred forty-three patients entered the study (mean [⫾ SD] age, 48.4 ⫾ 11.9; men, 179 [74%]; mean BMI, 28.7 ⫾ 5.8). One hundred one patients had AHIs ⱖ 20 on N1, and 74 of them tried an nCPAP device on N2. Unpaired t tests performed between patients with AHIs ⬎ 20 who underwent a nCPAP trial (n ⫽ 74) and those who did not (n ⫽ 27) showed no significant difference in AHIs on N1. Only the subgroup of 169 patients who did not use a nCPAP device on N2 (mean age, 47.2 ⫾ 12.1; men, 113 [67%]; mean BMI, 27.4 ⫾ 5.5) was considered for sleep and respiratory night-to-night (N1 vs N2) comparisons.
Regression analyses on N1 data in this subgroup (n ⫽ 169), using age as a dependent variable, were significant for AHI (p ⫽ 0.003), sleep efficiency (p ⫽ 0.004), and SOL (p ⫽ 0.021). The same analyses using BMI as a dependent variable showed a significant relationship with AHI (p ⫽ 0.009). Using AHI as dependent variable, significant relationships were found for the number of awakenings (p ⫽ 0.001), gender (p ⫽ 0.001), age (p ⫽ 0.011), and BMI (p ⫽ 0.0471). Logistic regression using gender as a dependent variable showed a significant relationship with AHI (p ⫽ 0.028) and slow-wave sleep (SWS) (p ⫽ 0.012). Data for N2 were largely comparable. Due to the significant relationships described above, gender was introduced as a cofactor in all analyses. Age, BMI, and AHI were introduced as covariates in the ANCOVA of sleep variables. Age and BMI were introduced as covariates for sleep respiratory variables. Selected sleep variables are presented in Table 1. The comparison between N1 and N2 recordings indicates a clear classic first-night effect (FNE) with shorter sleep period time (SPT) and TST, less sleep efficiency, longer SOL, more WASO, higher awakening index, less REMS time, and a longer RL on N1 compared to N2. NREMS measures (NREMS and SWS) and stage-shifts indexes also were decreased on N1. Nonrespiratory microarousals showed a significant decrease between N1 and N2, whereas respiratory microarousal indexes were not significantly different. To allow comparison with previous reports, the same calculations were performed using only patients with AHIs ⱖ 5 on either N1 or N2 (n ⫽ 116); outcomes were comparable to analyses of the overall sample (data not shown). In order to ascertain its potential influence on night-to-night variation, body position was measured and was not found to be significantly different between the two nights. Table 2 presents data on sleep respiratory events. The first PSG recording showed significantly fewer severe indexes of obstructive apnea, total apnea, hypopnea, and combined apnea-hypopnea. The levels of mean O2 saturation and maximum O2 drop were stable across nights. There were fewer instances of desaturation of ⱖ 3% in absolute number on N1, but the index of desaturations of ⱖ 3% showed fewer desaturations on N2. The frequency of low heart rate was stable across nights. Again, to allow comparisons with other studies, the same calculations were performed only on patients with AHIs ⱖ 5 on either N1 or N2 (n ⫽ 116). Comparable results were obtained for hypopneas and total indexes, but apnea indexes were no longer significantly different between N1 and N2 (data not CHEST / 118 / 2 / AUGUST, 2000
355
Table 1—Selected Sleep Measures (n ⴝ 169)* Measures
N1
N2
p Value†
TIB, min SPT, min TST, min Efficiency Sleep latency, min‡ Stage shifts, index/h WASO, min‡ Awakenings, index/h Nonrespiratory microarousals, index/h§ Respiratory microarousals, index/h§ NREMS, min SWS, min REMS, min RL, min‡ Body position, min Supine Lateral
434.8 (52.4) 385.9 (82.2) 308.6 (87.0) 71.9 (18.2) 41.0 (49.8) 37.7 (29.8) 73.2 (60.7) 7.9 (8.7) 36.7 (20.3) 7.8 (11.9) 270.8 (73.6) 37.9 (33.3) 42.5 (32.5) 95.5 (85.7)
443.9 (37.8) 407.3 (45.3) 340.1 (62.6) 77.9 (13.1) 31.6 (29.6) 33.5 (19.7) 64.8 (55.9) 6.2 (6.5) 28.9 (14.9) 10.8 (11.8) 291.6 (57.7) 42.2 (34.2) 49.9 (30.1) 88.0 (69.6)
NS 0.006 0.001 0.001 0.015 0.019 0.002 0.019 0.0351 NS 0.001 0.029 0.002 0.040
182.9 (136.1) 251.3 (148.8)
199.7 (145.2) 242.1 (152.6)
NS NS
*Values given as mean (SD). TIB ⫽ time in bed; NS ⫽ not significant. †ANCOVA for repeated measures, with gender as a cofactor, and age, BMI, and AHI (on N1) as covariates. ‡Log-transformed values. §Starting in 1996, n ⫽ 89.
shown). The correlation between N1 and N2 for AHI was highly significant (r ⫽ 0.770; p ⫽ 0.0001). Table 3 displays the distribution of AHI by 5-point intervals from 0 to 20 across the two nights. Respiratory microarousal indexes increased with each increasing AHI interval, paralleling the evolution of AHI. The total number of patients who shifted upward in AHI interval from N1 to N2 (n ⫽ 62) is almost double the number who shifted downward
(n ⫽ 32). This finding underscores the larger proportion of subjects having more severe respiratory events on N2. Bland-Altman plots14 were performed to assess the observed test-retest variability of AHIs between the two nights. A positive correlation between the mean of the two measurements and the difference between them would indicate that the differences observed between AHIs on N1 and N2 increased
Table 2—Sleep Cardiorespiratory Variables (n ⴝ 169)* N1
N2
Variables
Absolute No.
Index
Absolute No.
Index
p Value†
Central apneas Obstructive apneas Mixed apneas Total apneas REMS NREMS Hypopneas REMS NREMS Total apneas/hypopneas REMS NREMS Mean O2 saturation Max O2 saturation drop O2 desaturations ⬎ 3% Low heart rate
2.6 (7.6) 17.4 (37.4) 2.3 (6.5) 19.9 (40.2) 4.2 (11.5) 17.7 (37.8) 39.6 (38.2) 9.3 (11.2) 30.2 (32.6) 59.8 (65.4) 13.5 (17.9) 47.9 (59.6) 93.2 (4.4) 6.5 (7.0) 11.2 (39.1) 7.2 (50.7)
0.50 (1.4) 3.7 (8.7) 0.51 (1.6) 4.2 (9.3) 0.8 (2.1) 3.9 (9.2) 7.9 (8.6) 1.6 (1.9) 6.2 (7.9) 12.3 (14.7)‡ 2.5 (3.1) 3.9 (9.2)
4.1 (10.5) 24.1 (49.5) 4.0 (10.5) 28.3 (54.0) 6.0 (12.7) 26.4 (55.6) 57.5 (51.9) 13.5 (14.7) 43.6 (45.9) 85.5 (90.6) 19.5 (21.6) 69.7 (88.6) 93.3 (4.5) 9.8 (7.4) 15.7 (48.6) 8.1 (36.2)
0.75 (1.9) 4.7 (10.7) 0.72 (1.9) 5.4 (11.8) 1.0 (2.2) 5.1 (12.2) 10.2 (8.9) 2.3 (2.5) 7.8 (8.0) 15.5 (17.4)‡ 3.3 (3.7) 5.1 (12.2)
NS 0.033 NS 0.022 NS 0.029 0.005 0.005 0.023 0.001 0.004 0.005 NS NS 0.010 NS
5.4 (36.4) 1.2 (8.5)
3.5 (14.1) 1.3 (6.1)
*Values given as mean (SD). See Table 1 for abbreviations not in text. All apnea and hypopnea variables were log-transformed. ANCOVA for repeated values was performed using gender as a cofactor, with age and BMI as covariates. †ANCOVA performed on indexes, except for mean O2 saturation and maximal O2 saturation drop, where indexes did not make sense. ‡AHI. 356
Clinical Investigations
Table 3—Descriptive Stratification of AHI and Respiratory Microarousals Values, and Changes Between AHI Interval From Night to Night (n ⴝ 169)* N1
Interval Change, No.§
N2
AHI
No. (%)†
AHI (SD)
RMI (SD)‡
⬍5 05–10 10–15 15–20 ⱖ 20 Total Mean
57 (33.7) 48 (28.4) 20 (11.8) 17 (10.1) 27 (16.0) 169 (100)
1.8 (1.4) 7.3 (1.4) 11.8 (1.2) 17.5 (1.6) 40.3 (20.1)
1.4 (1.8) 5.9 (3.5) 9.4 (6.1) 15.4 (7.6) 33.3 (25.2)
12.3 (14.7)
7.8 (11.9)
No. (%)†
AHI (SD)
RMI (SD)‡
44 (26.0) 41 (24.3) 24 (14.2) 15 (8.9) 45 (26.6) 169 (100)
2.2 (1.6) 6.8 (1.2) 12.2 (1.4) 17.0 (1.0) 38.7 (22.8)
4.0 (4.9) 5.7 (4.7) 12.4 (7.3) 32.6 (16.7) 28.9 (16.1)
15.5 (17.4)
10.8 (11.8)
Up 28 21 8 5 62
Down
r Value㛳
11 7 7 7 32
0.940 0.965 0.962 0.885 0.490 0.291
*RMI ⫽ respiratory microarousal index (per TST). †Percentages represent the fraction of the total number of subjects by interval (N1 and N2). Raw data were used. ‡Starting in 1996, n ⫽ 89. §Up is from the corresponding interval to any higher interval; Down is from the corresponding interval to any lower interval. 㛳Bland-Altman plot. The average between AHI for N1 and AHI for N2 is plotted against the difference between the two measurements, according to the AHI interval in N1.
with the magnitude of the measurement. For the whole group, r ⫽ 0.291 (p ⫽ 0.0001; 95% confidence interval, 0.146 to 0.420; R2 ⫽ 0.085), indicating a weak positive relationship. Outcomes of the plots by AHI interval for N1 are given in Table 3. The plot then was analyzed with only patients having AHIs ⬍ 20 on N1, in order to measure this correlation only among the patients with lower AHIs on N1, and the correlation was stronger than in the whole group, as r ⫽ 0.560 (p ⫽ 0.0001; 95% confidence interval, 0.435 to 663; R2 ⫽ 0.313). Subsequent analyses then were performed to assess whether a prediction could be made about patients who had AHIs ⬍ 20 on N1 (n ⫽ 142) and then crossed the threshold of AHI ⱖ 20 on N2. First, patients with AHIs ⬍ 20 on N1 and ⱖ 20 on N2 (n ⫽ 25) were compared by unpaired t tests with those having AHIs ⬍ 20 on N2 (n ⫽ 117) for sleep and respiratory variables. No sleep variable was associated with changing from the low-AHI group to the high-AHI group on N2. Only a higher AHI on N1 (9.3 ⫾ 5.9 vs 6.5 ⫾ 5.2) was found to be associated (p ⫽ 0.0191) with a change to AHI ⱖ 20 on N2. Second, the patients with AHIs ⬍ 20 on N1 and AHIs ⱖ 20 on N2 were spread equally among all ranges of AHI for N1: six patients had AHIs ⬍ 5; eight had AHIs between 5 and 10; six had AHIs between 10 and 15); and five had AHIs between 15 and 20). In order to eliminate the potential influence of poor sleep quality on N1, only those patients who had SPTs of ⱖ 360 min were considered in a consecutive analysis. The results from the ANCOVA for AHI and total apneas/hypopneas and for the changes in AHI interval were almost identical to those for the whole group (data not shown). Again, patients with
AHIs ⬍ 20 on N1 and ⱖ 20 on N2 (n ⫽ 97) were compared with those patients with AHIs ⬍ 20 on N1 who maintained AHIs ⬍ 20 on N2. There was no significant difference between these two groups for any of the sleep variables. Only a higher AHI on N1 (10.0 ⫾ 6.1 vs 6.6 ⫾ 5.1) was associated with changing to an AHI ⱖ 20 on N2 (p ⫽ 0.0119). Table 4 presents, for each 5-point increase in AHI cutoff, the diagnostic sensitivity data for N1 alone, N2 alone (which corresponds to a PSG immediately following an habituation night), and the combination of N1 and N2. The diagnostic sensitivity increases by 12% for AHI ⱖ 5 and to 67% for AHI ⱖ 20 when using an habituation night over N1 alone. Using a second PSG recording when the results of the first were negative (from the point of view of AHI detection at a given threshold) on N1 alone, showed increases in test sensitivity varying from 25% (AHI, ⱖ 5) to 92% (AHI, ⱖ 20). To obtain the diagnostic sensitivity increases for the overall sample (n ⫽ 243), the 74 patients who had already had their condition diagnosed according to N1 results and had had an CPAP trial on N2 must be considered. For those patients, the following increases in diagnostic sensitivity were less dramatic, although still quite substantial: 7% (AHI, ⱖ 5); 14% (AHI, ⱖ 10); 14% (AHI, ⱖ 15); 18% (AHI, ⱖ 20) for N2 with a prior habituation night; 15% (AHI ⱖ 5); 23% (AHI, ⱖ 10); 23% (AHI, ⱖ 15); and 25% (AHI, ⱖ 20) for N2 when N1 is negative.
Discussion In this comparison of two sequential nights of PSG recordings in patients suspected of SAHS, a typical CHEST / 118 / 2 / AUGUST, 2000
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Table 4 —Diagnostic Sensitivity Comparisons (n ⴝ 169)* N1 Alone
N2 Alone
N1 or N2†
N2 With Habituation‡
AHI
No. (%)
No. (%)
No. (%)
No. (%)
Increase in Test Sensitivity vs N1 Alone, %
ⱖ 5 ⱖ 10 ⱖ 15 ⱖ 20
112 (66.2) 64 (37.8) 44 (26.0) 27 (15.9)
125 (73.9) 84 (49.7) 60 (35.5) 45 (26.6)
140 (82.8) 96 (56.8) 71 (42.0) 52 (30.7)
13 (7.6) 20 (11.8) 16 (9.4) 18 (10.6)
11.6 31.1 36.3 66.6
N2⫹ when N1⫺§ No. (%)
Increase in Test Sensitivity vs N1 Alone, %
28 (16.5) 32 (18.9) 27 (15.9) 25 (14.7)
25.0 50.0 61.1 92.5
*⫹ ⫽ positive; ⫺ ⫽ negative. †Conditions diagnosed on either one of two consecutive PSG sessions. ‡Increase in patients whose conditions were diagnosed using N2 data on an habituation night. §Increase in patients whose conditions were diagnosed by using a second PSG session when threshold AHI was not reached on N1.
FNE was found, including a reduction of NREMS and stage-shift values, which are less consistently observed in studies on FNEs. Though a partial FNE has been observed before in patients evaluated for possible SAHS, this is the first time that a full FNE clearly has been demonstrated, taking into account the potential influences of age, BMI, and AHI. Similarly, sleep respiratory events, measured by their indexes to eliminate the influence of TST, also were associated with an FNE, since most AHIs were reduced on the N1 PSG recording compared to that for N2. A slight difference in the mean AHIs for N1 and N2 has been demonstrated previously.5 BlandAltman tests plots confirmed that the AHIs obtained for the two nights differed significantly for all intervals of AHI. This difference between the two nights was also evident for microarousals; nonrespiratory microarousals were significantly more frequent on N1, whereas respiratory microarousal indexes showed nonsignificant differences. Interestingly, more severe AHIs were present when sleep quality was better, which is rather counterintuitive. This illustrates the complex relationships among sleep, respiratory function, and FNE. The differences observed between the two nights were found at all four 5-point AHI intervals. In all cases, PSG recordings on N2 were more efficient in detecting patients with sleep apneas than were those on N1, which is what would occur with an N1 recording immediately following a habituation night. The most efficient approach, however, would be to perform a second PSG recording when the results of the first one are negative. The search for predictors of which patients having an AHI ⬍ 20 on N1 would have an AHI ⱖ 20 on N2 was almost entirely fruitless. First, the only variable that was associated with the change was a small increment in AHI on N1. However, as the patients were equally spread over the four AHI intervals on N1, no efficient prediction could be made about what level of AHI they would attain on N2. Though 358
we hypothesized that differences in sleeping position between the two nights could have been associated with different AHI outcomes, no difference in sleep position patterns was observed between nights. Thus, it is unlikely that this factor played an important role in the FNE observed here. Third, waking the patients at a time bound to hospital routine could have artificially reduced the sleep time on N1, when the patients were getting accustomed to the new environment, vs that on N2. However, all the respiratory data were computed as indexes, which allowed for comparisons between different sleep times. Furthermore, analyses of a subgroup of the patients with SPTs ⬎ 360 min provided the same results as in the overall group. Fourth, studies have shown that improving the environment of the room or studying patients at home could reduce night-to-night variations.15,16 However, a large study performed by our group on healthy control subjects (unpublished data) does not support this hypothesis, since classic FNEs were found in a comparable number of subjects as those found in sleep laboratory settings. Considering the above, the reasons why N2 provided a better detection of sleep respiratory events seem unclear at present and need to be studied in the context of the complex phenomena of FNEs in general. The fact that a negative result on N1 does not necessarily exclude SAHS has been described by many authors, but the percentage of patients misdiagnosed in a N1 PSG recording has varied considerably, from 43%,8 to 32%,7 to 23%,5 to 17%,4 to 15%,17 to 9%.6 These results cannot be compared easily, however, since different populations and different diagnostic cutoff points were used. Moreover, the sensitivity of a test is a function of the composition of the group selected, which varied substantially in these studies. In addition, the frequency of the event that the test is measuring is not known with certainty, since apneas possibly could appear only on a later night that has not yet been recorded. Clinical Investigations
The results and conclusions presented here diverge significantly with the largest published study on a comparable group of subjects,6 in which no FNE was demonstrated on respiratory variables and the night-to-night variability did not influence diagnosis significantly. Patients in that study had a very high mean AHI (51.7) on N1, a score that is far superior to that in our group (12.3). In the study by Mendelson,6 patients were self-selected to contact the sleep center, perhaps creating a selection bias toward severely affected subjects. Second, the methodology differed; only patients presenting with AHIs ⱖ 5 on either N1 or N2 were analyzed by paired t tests in that study, while we used an ANCOVA with AHI, BMI, and age as covariates and gender as a cofactor. Analyses of our patients presenting with AHIs ⱖ 5 replicated the analyses of the entire sample, however. Finally, we benefited here from a larger group of patients. In terms of criteria, we used data from the worst night, that is, the night with the highest AHI index, for diagnosis. An alternative approach could be to use the mean of the two nights, or N2 alone, or a combination of variables, but, presently, there are no guidelines as to which approach would be best correlated with good clinical outcome. The rationale used here was that significant morbidity due to SAHS, such as accidents related to excessive daytime sleepiness, is more likely to occur immediately following a night with many respiratory events, and, hence, we preferred to capture the full severity of the syndrome by using the worst night for diagnosis. This study has the usual limitations of retrospective protocols, such as the relatively loose definition of the studied group. However, most findings were homogeneous among all AHI intervals, showing a robust inner stability. A second limitation is that only two nights were recorded when it is likely that, given the large variability observed, a few more cases of SAHS would have appeared with subsequent PSG recordings. Data on the consumption of alcohol or caffeine were not available. In conclusion, the present study demonstrates a classic FNE in a population of patients suspected of sleep respiratory disorders. It confirms the high night-to-night variability of AHIs and microarousal indexes. An important number of subjects presented false-negative results on N1, which turned out to be more frequent among severe cases. The major health and economic implications of SAHS,18 as well as the consequences of missing the diagnosis, underscore
the need for a second PSG recording when the results on N1 are negative. ACKNOWLEDGMENT: The authors thank Anita Bessemans and Marleen Bocken for their meticulous scoring of PSG sessions.
References 1 Wittig RM, Romaker A, Zorick FJ, et al. Night-to-night consistency of apneas during sleep. Am Rev Respir Dis 1984; 129:244 –246 2 Dean RJ, Chaudhary BA. Negative polysomnogram in patients with obstructive sleep apnea syndrome. Chest 1992; 101;105–108 3 Meyer TJ, Eveloff SE, Kline LR, et al. One negative polysomnogram does not exclude obstructive sleep apnea. Chest 1993; 3:756 –760 4 Lord S, Sawyer B, O’Connell D, et al. Night-to-night variability of disturbed breathing during sleep in an elderly community sample. Sleep 1991; 14:252–258 5 Bliwise DL, Benkert RE, Ingham RH. Factors associated with nightly variability in sleep-disordered breathing in the elderly. Chest 1991; 100;4:973–976 6 Mendelson WB. Use of the sleep laboratory in suspected sleep apnea syndrome: is one night enough? Cleve Clin J Med 1994; 61:299 –303 7 Chediack AD, Acevedo-Crespo JC, Seiden DJ, et al. Nightly variability in the indices of sleep-disordered breathing in men being evaluated for impotence with consecutive night polysomnograms. Sleep 1996; 19:589 –592 8 Mosko SS, Dickel MJ, Ashurst J. Night-to-night variability in sleep apnea and sleep-related periodic limb movements in the elderly. Sleep 1988; 11:340 –348 9 Aber WR, Block AJ, Hellard DW, et al. Consistency of respiratory measurements from night-to-night during the sleep of elderly men. Chest 1989; 96:747–751 10 American Thoracic Society Consensus Conference on Cardio-Pulmonary Sleep Studies. Indications and standards for cardiopulmonary sleep studies. Am Rev Respir Dis 1969; 139:559 –568 11 Le Bon O, Verbanck P, Hoffmann G, et al. Sleep in detoxified alcoholics: impairment of most standard sleep parameters and increased risk for sleep apnea, but not for myoclonias; a controlled study. J Stud Alcohol 1997; 58:30 –36 12 Rechtschaffen A, Kales A, eds. A manual of standardized terminology techniques and scoring system for sleep states of human subjects. Washington DC: US Govt Printing Office, 1968 13 Bonnet M, Carley D, Carskadon M, et al. EEG arousals: scoring rules and examples. Sleep 1992; 15:173–184 14 Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1:307–310 15 Coble P, McPartland RJ, Silva WJ, et al. Is there a first-night effect? (a revisit). Biol Psychiatry 1974; 9:215–219 16 Browman CP, Cartwright RD. The first-night effect on sleep and dreams. Biol Psychiatry 1980; 15:809 – 812 17 Kramer M, Silva C. Night-to-night variability of apneas [abstract]. Sleep Res 1986; 15:138 18 Leger D. The cost of sleepiness. Sleep 1995; 18:281–284
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