Download 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;
André 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
eports on the night-to-night variability of the
R 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), Université Libre de
Bruxelles, Brussels, Belgium; Sleep Laboratory (Dr. Staner),
FORENAP, Centre Hospitalier Rouffach, France; Hôpital Universitaire Erasme (Dr. Linkowski), Université 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
Downloaded From: http://publications.chestnet.org/pdfaccess.ashx?url=/data/journals/chest/21950/ on 05/13/2017
353
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
Downloaded From: http://publications.chestnet.org/pdfaccess.ashx?url=/data/journals/chest/21950/ on 05/13/2017
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
Downloaded From: http://publications.chestnet.org/pdfaccess.ashx?url=/data/journals/chest/21950/ on 05/13/2017
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
Downloaded From: http://publications.chestnet.org/pdfaccess.ashx?url=/data/journals/chest/21950/ on 05/13/2017
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
Downloaded From: http://publications.chestnet.org/pdfaccess.ashx?url=/data/journals/chest/21950/ on 05/13/2017
357
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
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.
358
Downloaded From: http://publications.chestnet.org/pdfaccess.ashx?url=/data/journals/chest/21950/ on 05/13/2017
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
Downloaded From: http://publications.chestnet.org/pdfaccess.ashx?url=/data/journals/chest/21950/ on 05/13/2017
359