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Overnight pulse oximetry for sleep-disordered breathing in adults - A review

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Pulse oximetry is a well-established tool routinely used in many settings of modern medicine to determine a patient's arterial oxygen saturation and heart rate. The decreasing size of pulse oximeters over recent years has broadened their spectrum of use. For diagnosis and treatment of sleep-disordered breathing, overnight pulse oximetry helps determine the severity of disease and is used as an economical means to detect sleep apnea. In this article, we outline the clinical utility and economical benefit of overnight pulse oximetry in sleep and breathing disorders in adults and highlight the controversies regarding its limitations as presented in published studies.
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Overnight Pulse Oximetry for Sleep-
Disordered Breathing in Adults*
A Review
Nikolaus Netzer, MD; Arn H. Eliasson, MD, FCCP; Cordula Netzer, MD;
David A. Kristo, MD, FCCP
Pulse oximetry is a well-established tool routinely used in many settings of modern medicine to
determine a patient’s arterial oxygen saturation and heart rate. The decreasing size of pulse
oximeters over recent years has broadened their spectrum of use. For diagnosis and treatment of
sleep-disordered breathing, overnight pulse oximetry helps determine the severity of disease and
is used as an economical means to detect sleep apnea. In this article, we outline the clinical utility
and economical benefit of overnight pulse oximetry in sleep and breathing disorders in adults and
highlight the controversies regarding its limitations as presented in published studies.
(CHEST 2001; 120:625– 633)
Key words: COPD; desaturation; pulse oximetry; sleep; sleep apnea syndromes; upper airway resistance syndrome
Abbreviations: AHI apnea-hypopnea index; NPSG nocturnal polysomnography; ODI oxygen desaturation
index; OSA obstructive sleep apnea; RDI respiratory disturbance index; Sao
2
arterial oxygen saturation
P
ulse oximetry is one of the most widely used tools
to determine a patient’s cardiorespiratory stabil-
ity. Over the last 40 years, it has often replaced
arterial blood gas analysis because the arterial oxygen
saturation (Sao
2
) frequently gives a sufficient
amount of information about a person’s respiratory
patterns.
1,2
In the early years of pulmonary medi-
cine, pulse oximetry was the key means to identify
patients with pickwickian syndrome or severe sleep
apnea syndrome by detecting the saw-tooth pattern
on oxygen desaturation waveforms (waveform de-
rived as a plot of Sao
2
vs time).
3
Very few clinics had
access to other devices such as pneumotachographs,
esophageal catheters, and respiratory effort belts.
With the broader use of nocturnal polysomnography
(NPSG) in sleep medicine, pulse oximetry has kept
its key role in the interpretation of NPSG but has lost
its status as the sole objective diagnostic parameter
for respiratory disturbance events.
4,5
In the past 5 years, debate has centered on the
effectiveness of overnight pulse oximetry as a screen-
ing tool to identify patients with sleep-disordered
breathing from the larger group of patients with
simple snoring and those with excessive daytime
sleepiness from other causes.
6–8
This controversial
discussion has arisen from needs to reduce the cost
for diagnostic procedures in sleep disorders while
technologic advances have made pulse oximeters
handier, cheaper, and more reliable.
9,10
Using keywords, we found 1,558 articles listed in
the PubMed database over the last 5 years that are
related to pulse oximetry. One individual reviewed
these publications by evaluating the abstracts.
Screening these publications for relevance revealed
that 79 of these articles contained useful information
to outline the actual role of overnight pulse oximetry
in the diagnosis and treatment of sleep-disordered
breathing. We reviewed the full text of these 79
articles. Eleven key articles from previous years were
also reviewed for important background information.
All articles were studied for strategies to use in the
interpretation of data gathered during overnight
pulse oximetry.
Interpretation and Technical Aspects of
Overnight Pulse Oximetry
Common sense dictates that pulse oximetry can be
a useful tool only if the user knows how to interpret
the oximetry data. In a survey performed in 1997
with 203 respondents, only 36% of intensive care
nurses, 4% of medical technicians, and 50% of
*From the Pulmonary and Critical Care Medicine Service,
Department of Medicine, Walter Reed Army Medical Center,
Washington DC.
Manuscript received October 11, 2000; revision accepted Feb-
ruary 1, 2001.
Correspondence to: Arn H. Eliasson, MD, FCCP, Pulmonary and
Critical Care Medicine Service, Department of Medicine, Walter
Reed Army Medical Center, Building 2, Ward 77, 6900 Georgia
Ave, Washington, DC 20307; e-mail: aheliasson@aol.com
CHEST / 120/2/AUGUST, 2001 625
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anesthesia technicians believed that they had re-
ceived adequate training in interpreting pulse oxim-
etry data. Only 68.5% correctly stated what pulse
oximeters actually measure.
11
These survey results
were found despite the fact that practice guidelines
for pulse oximetry were published in 1991 by the
American Association for Respiratory Care.
12
The interpretation skills of overnight pulse oxim-
etry start with a knowledge of normal oxygen satu-
ration values during sleep. In a key validation study
published in 1996 in CHEST, the authors noted a
normal overnight mean (the so-called Sat 50) Sao
2
of
96.5% ( 1.5%) in 350 healthy subjects.
13
Sao
2
decreased slightly with increasing age, the values
ranging from 96.8% in the age group of 1- to
10-year-old patients to 95.1% in the age group 60
years (Table 1). Ethnicity, gender, and weight did
not significantly influence normal values. In a group
of 21 asthmatic patients, Sao
2
did not decrease
significantly, but significantly lower values were
found in a group of 25 patients with obstructive sleep
apnea (OSA) where mean “lowest Sao
2
of 65.9%
( 22.6%) was measured vs 90.4% ( 3.1%) in
normal subjects and 89.0% ( 5.3%) in asthmatic
subjects.
Normal Sao
2
values at night differ with altitude of
course. In six healthy subjects, normal mean Sao
2
values of 97.3%, 83.0%, and 71.0% were measured
respectively at 500 m, 4,200 m, and 6,400 m (three
subjects) of altitude during sleep.
14
The high-quality, portable pulse oximeters of to-
day deliver accurate values of Sao
2
that differ from
arterial blood gas probes by 0.5% (1.8%); there
are no significant differences if probes measure at
the fingertips or ears.
15
Due to the fact that mea-
surements are taken by performing a “running aver-
age” with a moving window that varies from 1 to 15 s
in length, the speed of response to onset of oxygen
breathing is on average 9 to 10 s with finger and ear
probes.
15,16
However, the speed of response is mark-
edly slower with toe probes.
15
The default settings
for the averaging time are different for various pulse
oximeters, and must be known by the user. For
overnight pulse oximetry in sleep medicine, it is
important that the oximeter be set to the shortest
time interval for measurement.
16
The typical cyclical
drop in Sao
2
in patients with OSA lags 45 to 60 s
behind a respiratory event and should be accurately
detected at this measurement speed.
15
Due to move-
ments during sleep, the artifact rate is higher in
overnight pulse oximetry, compared to daytime Sao
2
measurements. With measurement intervals set on
high speed, artifacts are recognized by most pulse
oximeters due to a missing pulse signal, although this
is controversial. In a validation study of three differ-
ent oximeters, Barker and Shah
17
revealed that one
oximeter displayed the Sao
2
value within 7% of
control only 76% of the time after patient motion;
another oximeter did so 87% of the time; and only
one of the three oximeters did so 99% of the time.
Another study
18
also showed that pulse oximeters
detect only 18% ( 11%) of all artifacts in infants.
There is no universally accepted definition of an
oxygen desaturation in sleep-disordered breathing.
However, in most publications, an oxygen desatura-
tion is defined as a decrease of 4% from baseline
Sao
2
.
6,19–22
Rauscher et al
19
tested the detection of
apneas and hypopneas by searching for rapid resatu-
rations of 3% Sao
2
within 10 s at the end of a
respiratory event vs detecting a decrease 4% Sao
2
in a 40-s interval. They found the resaturation to be
a more accurate sign of respiratory events than the
actual desaturation.
19
Taha et al
23
defined an oxygen
desaturation as a fall in oxyhemoglobin saturation of
2% if the rate of descent was 0.1%/s but
4%/s.
Whereas one definition of an oxygen desaturation
is in common use, no such uniform definition exists
for a normal or abnormal oxygen desaturation index
(ODI; oxygen desaturations per hour of sleep).
There are generally three cutoff points for an abnor-
mal ODI that appear to mirror the definition of an
Table 1—Descriptive Statistics of Normal Oxygen Values in Different Age Groups*
Age Group, yr Patients, No. Low Sat (SD), % Sat 10 (SD), % Sat 50 (SD), %
All ages 350 90.4 (3.1) 94.7 (1.6) 96.5 (1.5)
1 30 90.7 (2.6) 95.2 (1.0) 96.4 (1.2)
1–10 180 90.1 (3.6) 95.1 (1.5) 96.8 (1.4)
10–20 46 90.4 (2.7) 94.5 (1.8) 96.5 (1.6)
20–30 12 92.0 (3.4) 94.8 (1.1) 96.3 (1.0)
30–40 24 91.5 (2.2) 94.8 (1.3) 96.3 (1.1)
40–50 25 91.1 (2.0) 94.2 (1.7) 96.0 (1.3)
50–60 16 90.4 (1.9) 93.6 (1.6) 95.8 (1.7)
60 17 89.3 (2.8) 92.8 (2.3) 95.1 (2.0)
*Low Sat lowest oxygen saturation during the night; Sat 10 saturation below which the patient spent 10% of the time; Sat 50 median
saturation during the night; data from Gries and Brooks.
13
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abnormal apnea-hypopnea index (AHI; apneas and
hypopneas per hour of sleep) for that study. The
threshold for an abnormal ODI is either 5 desatu-
rations per hour,
6,20,21,24,25
10 desaturations per
hour,
7,8,22
or 15 desaturations per hour.
26–30
There
is little evidence of one definition having greater
validity than the others.
To properly interpret overnight oximetry data, an
understanding of the Sao
2
vs time waveform mor
-
phologies is essential.
31,32
The waveforms can help
discriminate between obstructive apneas and hypop-
neas, as well as between obstructive and central
apneas, and can give evidence of Cheyne-Stokes
respiration.
33
While obstructive apneas show the
typical saw-tooth waveform with a rapid increase in
Sao
2
during or after the arousal, the “teeth” are not
as sharp in hypopneas and are sometimes completely
missing in central apneas (Fig 1, 2). Central apneas
can act as the great masquerader of oximetry wave-
forms. Especially when part of Cheyne-Stokes respi-
ration, they show a more regular symmetrical wave
due to the more regular breathing pattern, compared
to those of obstructive apneas. However, single
central apneas not in conjunction with Cheyne-
Stokes respiration can also have a saw-tooth config-
uration in the oximetry waveform.
The length of the desaturation waveform can also
help to distinguish desaturations due to COPD from
desaturations caused by obstructive apneas or hy-
popneas. The desaturations secondary to COPD
tend to last much longer and have a much lesser
degree of slope in the waveform.
34,35
This is also
important for the diagnosis of OSA in the presence
of COPD, the so-called overlap syndrome.
The automatic interpretation of the Sao
2
wave
-
form is often a part of modern NPSG and portable
oximetry software. However, the programs are not
yet able to replace interpretation by hand. The same
may be true for the interpretation of heart rate
variability, but here the experience with automatic
analysis is much greater because of the long experi-
ence with automatic analysis in ECG-Holter systems.
The heart rate slows during and at the end of an
upper-airway obstruction (apnea or hypopnea) due
to a reflex bradycardia with high negative intratho-
racic pressure (involuntary Mueller maneuver).
There is a rapid increase in the pulse with rebreath-
ing during the arousal. This strategy does not apply
to the interpretation of central apneas, because there
is no negative intrathoracic pressure during a central
apnea. Adult criteria for the interpretation of over-
night pulse oximetry may not be valid for the evalu-
ation of sleep-disordered breathing in children and
adolescents due to different patterns of normal
respiration and gas exchange.
36,37
Sensitivity and Specificity of Overnight
Pulse Oximetry in Screening for Sleep-
Disordered Breathing
Over the last decade, a debate in the literature has
questioned whether or not pulse oximetry could
effectively screen patients for sleep-disordered
Figure 1. Respiratory patterns during a 3-min time period for a patient with OSA syndrome showing
obstructive apneas with typical saw-tooth morphology of the pulse oximetry curve. Flow
na
nasal and
oral airflow; Resp
th
thoracic respiratory effort; Resp
abd
abdominal respiratory effort;
Resp
sum
sum signal of thoracic and abdominal respiratory effort; O obstructive apnea.
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breathing and possibly replace NPSG in many pa-
tients. Deegan and McNicholas
28
reported 250 con-
secutive Irish patients who underwent NPSG. In one
third of these patients, patient history and pulse
oximetry data would have been sufficient to make a
diagnosis. In the other two thirds, a final diagnosis
could be established only by NPSG.
28
Other studies
38,39
are more encouraging about the
use of overnight oximetry as a less expensive substi-
tute for NPSG. In 1991, Cooper et al
25
studied a
group of 41 patients with suspected sleep apnea and
found that the sensitivity and specificity of pulse
oximetry for identifying OSA was dependent on the
AHI. For patients with an AHI 25 events per
hour, the sensitivity was 100% and the specificity
95%. For patients with AHI 15 events per hour,
these values decreased to 75% and 86%; for patients
with AHI 5 events per hour, to 60% and 80%,
respectively. The authors concluded that pulse oxim-
etry is an effective tool for screening patients with
moderate-to-severe sleep apnea. In the same year,
Williams et al
7
reported a sensitivity of 78% and
specificity of 100% when screening patients with an
AHI 10 events per hour. In a study of 116
subjects, Rauscher et al
8
reported a sensitivity of
94% and a specificity of 45% for detecting OSA with
an AHI 10 events per hour and 95% and 45% with
an AHI 20 events per hour, respectively. Within
the past 5 years, 11 articles on this topic were
published, revealing a broad range of sensitivity and
specificity values for pulse oximetry as a screening
tool for sleep-disordered breathing.
26,27,29,30,4046
The values for sensitivity range from 31 to 98% and
for specificity from 41 to 100% (Table 2). These
validation studies deserve critical comment. Some
authors used methods of pulse oximetry that are not
yet available to the general public. The utility of
these new technologies may not be borne out with
further investigation.
30
Other authors looked only at
a limited patient group in the spectrum of severity of
OSA. Findings from these studies may not be appli-
cable to OSA patients with different levels of severity
from those studied.
Overnight Pulse Oximetry in Combination
With Other Parameters
Pulse oximetry is the most important parameter
for identifying sleep-disordered breathing in many
portable multichannel sleep apnea screening de-
vices. The next most commonly measured parame-
ters are snoring sound via microphone,
47,48
oronasal
airflow measured via thermistor or nasal pressure
cannula,
49–51
and ECG recording.
52
One author
52
argues that the full ECG provides information about
the comorbidity of cardiovascular disease in sleep
apnea better than pulse oximetry alone. In 1998,
Lojander et al
53
described pulse oximetry in combi-
nation with a bed sensitive to static charge in order to
measure body movements. However, if compared to
the sensitivity and specificity values of pulse oximetry
alone as a screening tool, the combination of other
parameters with pulse oximetry does not offer much
improvement.
49,51
Another interesting strategy may be the combina-
Figure 2. Respiratory patterns during a 3-min time period for a patient with OSA syndrome showing
obstructive hypopneas with a more regular up-and-down waveform of the pulse oximetry curve.
H hypopnea; see Figure 1 legend for definition of abbreviations.
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tion of a validated questionnaire with overnight pulse
oximetry. Chervin and Aldrich
54
state that the addi-
tion of the Epworth Sleepiness Scale alone does not
appear to be helpful for the diagnosis of sleep-
disordered breathing compared to NPSG and oxim-
etry. However, there is a report
42
that the combina-
tion of a questionnaire and pulse oximetry doubles
the specificity of oximetry as a screening tool for
sleep apnea. This approach invites further validation.
Other Applications
Overnight pulse oximetry is frequently being used
to assess the response to the surgical interventions
for OSA as well as the effectiveness of therapy with
continuous positive airway pressure. However, this
clinical practice is not established in the literature,
and validation of its use for this indication is lacking.
Continuous pulse oximetry is also in frequent use in
a variety of other settings, including preoperative
evaluations, the operating room, postanesthesia re-
covery suites, ICUs, and stroke units.
55–61
This has
led to an increasing awareness of sleep-disordered
breathing as a comorbidity in patients being treated
for other diagnoses or as a symptom of other dis-
eases, such as stroke,
60,61
neuromuscular diseas-
es,
62,63
and cardiovascular diseases.
64–66
As continu-
ous pulse oximetry has become more accessible and
more widely employed, physicians in specialties
other than sleep medicine have become accustomed
to recognizing oximetry waveforms suggestive of
sleep apneas. These coincidental observations are
frequently leading to patient referrals for definitive
diagnosis and treatment of OSA.
Attempts have been made to capitalize on the
continuous measurement of heart rate provided by
pulse oximetry. Computerized analysis of the heart
rate variability makes it possible to detect sleep
apnea syndrome via the pulse signal.
67,68
Using this
method, Keyl et al
68
report a sensitivity of 90% and
a specificity of 77% for the detection of OSA in
patients with daytime sleepiness. Some authors
69,70
believe that the interpretation of heart rate changes
delivers a better pulse oximetry indicator for OSA
than interpretation of the Sao
2
signal, especially if it
is done using automation. Another aspect used by
some investigators is the waveform generated by the
displacement of capillary walls by the intermittent
pulse signal or so-called “plethysmographic” pulse.
Shamir et al
71
and Schnall et al
72
describe that
apneas lead to transient peripheral vasoconstriction.
Schnall et al
72
conclude in their publication that
pulsatile finger blood flow patterns can be clearly
diagnostic of OSA and other conditions of sleep-
disordered breathing.
Future developments with pulse oximetry will
undoubtedly show marked improvements in artifact
detection. Signal delivery will become more reliable
and less vulnerable to interruptions by movement
using the same technique employed in portable
compact disk players to memorize signals (using new
paradigms for oximeter signal processing).
17,73
The
spectral analysis of oximetry data facilitates precise
analysis with a reported sensitivity of 94% and
specificity of 65% for OSA.
74
Photon density wave
differentials and noninvasive optical oximetry with a
living tissue oximeter may allow monitoring of re-
gional tissue oxygenation in the heart or brain in
conjunction with sleep apnea.
75,76
Another promising
innovation is the improvement of adhesive probes
that would allow for pulse oximetry in sites other
than digits and ears.
77
Table 2—Sensitivity and Specificity of Pulse Oximetry When Used To Screen for OSA Compared to NPSG: Results
From 11 Published Studies*
Author/Year
Study
Population, No.
AHI/ODI
Cutoff Point
Screening
Specificity, %
Screening
Sensitivity, %
Ryan et al
27
/1995 69 15 100 31
Levy et al
29
/1996 301 15 94 77
Rodriguez Gonzalez-Moro et al
40
/1996 96 NA 69 91
Schafer et al
41
/1997 114 NA 41 (92†) 94
Lacassagne et al
44
/1997 329 15 57.8 89
Sano et al
26
/1998 40 15 83.3 73.5
Olson et al
45
/1999 113 15 70 88
Golpe et al
43
/1999 116 10 97 84
Brouillete et al
46
/2000 349 NA 96 58
Nuber et al
42
/2000 70 NA 77.8 85.2–91.8‡
Vazquez et al
30
/2000 246 15 88 98
*NA not available.
†Combined with questionnaire.
‡Higher sensitivity after rereading unclear desaturations.
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Limitations
While pulse oximetry is a useful clinical tool in
sleep medicine, it suffers from major limitations due
to the nature of the parameters that are moni-
tored.
78–80
Limitations result from problems with
blood flow, hemoglobin, or a lack of change in
oxygen saturation.
Pulse oximetry relies on pulsatile blood flow for its
measurements and is vulnerable to the effects of
poor peripheral arterial blood flow. Therefore, body
movements, vasoconstriction, and hypotension can
cause artifacts through an interruption of the pulse
signal. In sleep medicine, movement artifacts are
common since patients often have fragmented sleep
with a lot of body movements. Oximeters do not
always detect movement artifacts, and this would
tend to overestimate desaturations.
17
Changes in the hemoglobin structure and quantity
will also cause artificially high (in cases of methemo-
globinemia and carboxyhemoglobinemia) or low
readings (anemia) that are not due to respiratory
disturbances.
78
Anemia would also tend to be mis-
read by overestimating respiratory-caused desatura-
tions. Tissue optics in very obese patients can cause
the same effect.
81
Herer et al
82
found that oximetric
data do not reliably predict OSA in obese patients.
Mower et al
83
studied Sao
2
data from 12,096 patients
at the UCLA Emergency Medicine Center. They
believed that no conclusions could be drawn from
the data due to high variations in respiratory rates
among the patients and the artifacts that this
caused.
83
Another type of limitation of pulse oximetry is due
to the inability of technology to detect other forms of
sleep-disordered breathing where oxygen desatura-
tion does not occur. These disorders include upper
airway resistance syndrome or pure central sleep
apnea in diseases like Ondine’s curse. A normal
minute ventilation in upper airway resistance syn-
drome maintains normal oxygen levels, but high
respiratory workload causes arousals and daytime
sleepiness. Understandably, pulse oximetry would
appear normal in this setting.
24,84
The limitations of pulse oximetry might not have
much impact in the sleep laboratory, where several
other parameters are monitored to aid in the inter-
pretation of the study. However, these limitations
become of major importance in the application of
pulse oximetry alone as a screening tool for breath-
ing-disordered sleep.
Cost-effectiveness
Bennet and Kinnear
10
call pulse oximetry “sleep
on the cheap” in their 1999 editorial because it
generates a lot of data at a very low cost. Perhaps the
only competitor for cost-effectiveness is a structured
and validated questionnaire. In other fields of med-
icine, the cost-effectiveness of pulse oximetry is
more or less accepted.
85
In sleep medicine, the
clinical value of overnight pulse oximetry alone for
the diagnosis of sleep apnea syndrome has become
controversial since NPSG has been widely available.
However, the recent advent of managed care and
pressures for cost reduction have stimulated a variety
of investigations
22,8689
that substantiate the econo-
mies of overnight pulse oximetry at home as a
screening test for sleep-disordered breathing. Ep-
stein and Dorlac
22
state that initial diagnosis with
home-based overnight pulse oximetry would save
$4,290 per 100 patients vs diagnostic NPSG or
split-night studies. However, they showed that oxim-
etry is not very sensitive for patients with mild sleep
apnea.
22
Chiner et al
89
subsequently analyzed how
many NPSGs could be saved by overnight pulse
oximetry in the initial diagnosis for patients with
differing severity of OSA. They concluded that in
275 suspected cases, of which 216 patients were
confirmed to have OSA, pulse oximetry could have
saved 140 polysomnographic studies in the group
with a respiratory disturbance index (RDI) 5, 119
in the group with an RDI 10, and 10 in the group
with an RDI 15.
89
Because of its low cost, there is
almost no alternative to overnight pulse oximetry as
a sole diagnostic tool, except for patient history and
questionnaires.
90
If the pressure for cost reduction
Figure 3. Flow diagram for the use of overnight pulse oximetry to screen for sleep-disordered
breathing with a descending progressive therapeutic approach for patients with an ODI 15
desaturations per hour. PSG polysomnography; CPAP continuous positive airway pressure.
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continues, proposals may arise to perform pulse
oximetry with reusable finger and ear probes, or
validated questionnaires may become the sole “pro-
cedure” of first choice in the diagnostic evaluation of
sleep disorders.
91
Conclusion
Overnight pulse oximetry is a very useful tool for
the diagnosis of sleep-disordered breathing. Author-
itatively establishing a final diagnosis is very difficult
without oximetry data. As a screening tool for the
diagnosis of OSA, pulse oximetry is cost-effective
and shows substantial accuracy. Sensitivity and spec-
ificity remain controversial, however, and deserve
further clarification through controlled studies.
Technical limitations, limited user knowledge, and
the lack of consensus on interpretation of data all
play a role in diminishing the value of pulse oximetry
as a diagnostic tool. The authors suggest a flow
diagram to delineate the clinical use of overnight
pulse oximetry as a screening tool for sleep-disor-
dered breathing (Fig 3). The establishment of clini-
cal practice guidelines that outline technical require-
ments and strategies for interpretation, along with
improved automated analysis, may improve the clin-
ical utility of pulse oximetry in the future.
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... Recent studies have demonstrated that oxygen saturation can offer valuable information for detecting SAE, but it also has some limitations [18]. First, pulse oximetry is susceptible to poor peripheral arterial blood flow, so vasoconstriction and hypotension may cause SpO2 artifacts. ...
... Variations in the structure and quantity of hemoglobin can also cause artificial increases or decreases that are not due to SAE. Additionally, some forms of sleep-disordered breathing may not result in oxygen desaturation, such as central sleep apnea [18]. ...
Preprint
Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a sleep-related breathing disorder associated with significant morbidity and mortality worldwide. The gold standard for OSAHS diagnosis, polysomnography (PSG), faces challenges in popularization due to its high cost and complexity. Recently, radar has shown potential in detecting sleep apnea-hypopnea events (SAE) with the advantages of low cost and non-contact monitoring. However, existing studies, especially those using deep learning, employ segment-based classification approach for SAE detection, making the task of event quantity estimation difficult. Additionally, radar-based SAE detection is susceptible to interference from body movements and the environment. Oxygen saturation (SpO2) can offer valuable information about OSAHS, but it also has certain limitations and cannot be used alone for diagnosis. In this study, we propose a method using millimeter-wave radar and pulse oximeter to detect SAE, called ROSA. It fuses information from both sensors, and directly predicts the temporal localization of SAE. Experimental results demonstrate a high degree of consistency (ICC=0.9864) between AHI from ROSA and PSG. This study presents an effective method with low-load device for the diagnosis of OSAHS.
... Hypoxemia results in a poor clinical outcome, making pulse oximetry an important tool to monitor patient oxygenation routinely both in primary care and in hospital. (1) Pulse oximetry is a spectrophotometry technology which determines the arterial oxygen saturation by the detection of pulsatile blood ow and is based on differing absorption spectra of oxyhaemoglobin and deoxyhaemoglobin which includes the red and near-infrared wavelengths of light. (2) The oxyhaemoglobin absorbs near-infrared light and dissipates the red component of light which makes it appear bright red. ...
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Hypoxemia results in a poor clinical outcome, making pulse oximetry an important tool to monitor patient oxygenation routinely both in primary care and in hospital. Overnight pulse oximetry (OPO) also has emerged as one of the most widely used techniques to determine the Respiratory status and oxygen saturation status, as it provides adequate information about patient's oxygenation. Overnight pulse oximetry alone is often used and also a good screening tool in the primary care setting. It can be used as a primary screening tool in detecting Obstructive Sleep Apnoea. It aides in the Management of Chronic Obstructive Pulmonary Disease and Interstitial Lung Diseases.
... 4 These oral factors increase the risk of obstructive sleep apnea (OSA), which is linked to many health outcomes through several associated mechanisms, such as compromising the quality of sleep by repetitive brief disruptions (arousals), hindering oxygen supply to vital organs such as the heart, lungs, and brain, sleep bruxism, and temporomandibular disorder (TMD). 1,2,[5][6][7][8][9][10] Research has shown that OSA correlates with chronic bruxism both as an attempt to prevent obstruction and as part of the arousals from sleep, which can cause significant damage to the teeth. 1,5,6,[11][12][13] In addition to bruxism, OSA is also associated with other maneuvers in attempts to open the airway, such as tongue thrusting, which not only can move compromised teeth but also contribute to the development of an anterior open bite. ...
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Software has greatly enhanced the ability of dental teams to plan treatments integrating esthetics, function, and airway health. Over the past decade, the compromised or underdeveloped airway has become an increasingly important focus in dentistry. Using a guided digital workflow, the collaborative team can virtually plan, manage, and execute treatment with greater accuracy and predictability. This case report demonstrates the use of a digital workflow in interdisciplinary collaboration, incorporating airway analysis and smile design to treat a complex case in a 38‐year‐old patient. A 2‐year follow‐up showed sustained improvements in both airway health and esthetic outcomes. The transparency provided by digital tools also improved patient communication, case acceptance, and documentation, contributing to more predictable and satisfying results.
... Monitoring of a patient through wireless telemetry can be done to view data from numerous remote patients on a single display [1]. In addition, many screening devices for sleep apnea use pulse oximetry as its most important parameter [2]. By recording oxygen saturation and pulse readings during sleep, pulse oximetry can be an effective and low-cost screening tool that may be used away from the hospital. ...
Conference Paper
Full-text available
The goal of this paper is the presentation of a prototype wireless pulse oximeter patient monitoring device that is low cost, high performance in signal detection and has good battery life. For patients at risk of respiratory failure, it is important to monitor the blood oxygen saturation of such individuals to ensure proper perfusion of blood in their system. Preferably this information should be received on a continuous basis. Both of these objectives can be reached via the non−invasive method of pulse oximetry. Wireless pulse oximetry adds many advantages to the traditional wired units. They are more convenient for the patient to use, and can be more comfortable.
... The primary exposures were nocturnal mean (average) SpO 2 (%), minimum (the recorded lowest value) SpO 2 (%) and ODI (average number of≥3% desaturation episodes per hour). 24 SpO 2 measurements were conducted by in-home overnight finger pulse oximetry using the FM-800 device (Fukuda Denshi, Tokyo, Japan) and the Konica Minolta Personal Probe SD-5C (Konica Minolta, Tokyo, Japan). All the recordings were scanned, and the data were accessed through SCM-510 software (Fukuda Denshi, Tokyo, Japan). ...
Article
Full-text available
Objective We investigated the associations of nocturnal oxygen saturation (SpO 2 ) with prevalence of coronary artery calcification (CAC) and its level of burden, and whether the associations differ by obesity and mediate through diabetes mellitus (DM), dyslipidaemia and hypertension. Design Observational study. Setting Kusatsu, Shiga. Participants We analysed data from 510 Japanese men (aged 46–76 years) with no history of myocardial infarction. Primary and secondary outcomes Mean SpO 2 , minimum SpO 2 and oxygen desaturation index (ODI) were measured using overnight pulse oximetry (primary exposures), while CAC was assessed using CT. Prevalence of CAC (>0) and its burden (CAC 0, >0–100, >100–400 and>400) were evaluated as outcomes. Body mass index≥25.0 kg/m ² defined as obesity. Results Mean±SD age was 66.7±7.2 years. The prevalence of CAC was 64.7% (CAC scores>0–100, 31.4%; >100–400, 20.0% and>400, 13.3%). In multivariable binary logistic regression, the OR and 95% CI for the prevalence of CAC were 1.25 (1.02 to 1.53) per 1-SD decrement in mean SpO 2 and 1.25 (1.01 to 1.55) per 1-SD increment in ODI. The associations lost their significance while further adjusted for DM and dyslipidaemia. Similar trends were observed for the level of CAC burden in multivariable ordinal logistic regression. Obesity did not show significant interaction with SpO 2 on CAC. In mediation analysis, the OR (95% CI) for natural indirect effect; percentage mediated through dyslipidaemia in association of 1-SD decrement in mean SpO 2 with prevalence of CAC were 1.06 (1.01 to 1.10); 25.4%. These estimates for mediation through DM and dyslipidaemia for 1-SD increment in ODI in the associations were 1.07 (1.01 to 1.12); 29.6% and 1.04 (1.00 to 1.08); 17.5%, respectively. Conclusions Lower mean SpO 2 and higher ODI are associated with CAC among Japanese men, independent of age, lifestyle factors and obesity. The associations became non-significant after adjusting for diabetes and dyslipidaemia, but were mediated through these factors.
... SpO2 can be obtained by a low-burden pulse oximeter. Recent studies have shown that SpO2 provides useful information for SAE detection [34][35][36][37], but using it solely for OSAHS diagnosis also has certain limitations [38]. For example, changes in hemoglobin levels can artificially raise or lower SpO2, which is unrelated to SAE. ...
Preprint
Objective: The aim of the study is to develop a novel method for improved diagnosis of obstructive sleep apnea-hypopnea syndrome (OSAHS) in clinical or home settings, with the focus on achieving diagnostic performance comparable to the gold-standard polysomnography (PSG) with significantly reduced monitoring burden. Methods: We propose a method using millimeter-wave radar and pulse oximeter for OSAHS diagnosis (ROSA). It contains a sleep apnea-hypopnea events (SAE) detection network, which directly predicts the temporal localization of SAE, and a sleep staging network, which predicts the sleep stages throughout the night, based on radar signals. It also fuses oxygen saturation (SpO2) information from the pulse oximeter to adjust the score of SAE detected by radar. Results: Experimental results on a real-world dataset (>800 hours of overnight recordings, 100 subjects) demonstrated high agreement (ICC=0.9870) on apnea-hypopnea index (AHI) between ROSA and PSG. ROSA also exhibited excellent diagnostic performance, exceeding 90% in accuracy across AHI diagnostic thresholds of 5, 15 and 30 events/h. Conclusion: ROSA improves diagnostic accuracy by fusing millimeter-wave radar and pulse oximeter data. It provides a reliable and low-burden solution for OSAHS diagnosis. Significance: ROSA addresses the limitations of high complexity and monitoring burden associated with traditional PSG. The high accuracy and low burden of ROSA show its potential to improve the accessibility of OSAHS diagnosis among population.
... Objective methods analyze signals from wearables, such as electrocardiogram signals combined with cardiopulmonary coupling and cyclic variation of heart rate, achieving 89% sensitivity and 79% specificity [18]. Pulse oximeters are popular in research due to their simplicity and affordability [19]. ...
Article
Background Obstructive sleep apnea (OSA) is a prevalent sleep disorder characterized by frequent pauses or shallow breathing during sleep. Polysomnography, the gold standard for OSA assessment, is time consuming and labor intensive, thus limiting diagnostic efficiency. Objective This study aims to develop 2 sequential machine learning models to efficiently screen and differentiate OSA. Methods We used 2 datasets comprising 8444 cases from the Sleep Heart Health Study (SHHS) and 1229 cases from Taipei Veterans General Hospital (TVGH). The Questionnaire Model (Model-Questionnaire) was designed to distinguish OSA from primary insomnia using demographic information and Pittsburgh Sleep Quality Index questionnaires, while the Saturation Model (Model-Saturation) categorized OSA severity based on multiple blood oxygen saturation parameters. The performance of the sequential machine learning models in screening and assessing the severity of OSA was evaluated using an independent test set derived from TVGH. Results The Model-Questionnaire achieved an F1-score of 0.86, incorporating demographic data and the Pittsburgh Sleep Quality Index. Model-Saturation training by the SHHS dataset displayed an F1-score of 0.82 when using the power spectrum of blood oxygen saturation signals and reached the highest F1-score of 0.85 when considering all saturation-related parameters. Model-saturation training by the TVGH dataset displayed an F1-score of 0.82. The independent test set showed stable results for Model-Questionnaire and Model-Saturation training by the TVGH dataset, but with a slightly decreased F1-score (0.78) in Model-Saturation training by the SHHS dataset. Despite reduced model accuracy across different datasets, precision remained at 0.89 for screening moderate to severe OSA. Conclusions Although a composite model using multiple saturation parameters exhibits higher accuracy, optimizing this model by identifying key factors is essential. Both models demonstrated adequate at-home screening capabilities for sleep disorders, particularly for patients unsuitable for in-laboratory sleep studies.
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INTRODUCTION Sleep patterns change with aging, yet their relationship with brain health, particularly Alzheimer's disease (AD)‐related MRI patterns among diverse older adults is not clear. METHODS We cross‐sectionally studied community‐dwelling Non‐Hispanic White (NHW), Hispanic, and Black participants recruited from the Health and Aging Brain Study‐Health Disparities (HABS‐HD)‐Dormir Study, who underwent WatchPAT and brain MRI. RESULTS A total of 842 participants (34% male; 42% NHW, 33% Hispanic, and 25% Black; mean age 66.1 ± 8.6 years) were included. Greater light sleep percentage and longer rapid‐eye movement (REM) sleep latency were independently associated with thinner cortex in AD‐signature regions, while inverse pattern was observed for greater deep sleep percentage. Higher Apnea‐Hypopnea Index (AHI) in REM sleep was independently associated with greater white matter hyperintensities volume. There were no ethnoracial interactions for these associations. DISCUSSION Light and deep sleep percentage, REM sleep latency, and AHI in REM sleep were associated with AD‐related MRI patterns. Highlights Greater light sleep percentage and longer rapid‐eye movement sleep latency were associated with thinner cortex in the Alzheimer's Disease‐siganture regions, while greater deep sleep percentage was associated with thicker cortex in those regions. Higher apnea hypoonea index in rapid eye movement sleep was associated with greater white matter hyperintensities volume. No moderation effects by race/ethnicity were observed among Non‐Hispanic White/Hispanic/Black adults.
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Recently, numerous new diagnostic possibilities based on technical innovations have emerged in sleep medicine, especially in the field of sleep-disordered breathing. This article highlights selected new diagnostic approaches as well as technical advancements of already established methods, with which sleep physicians are already confronted in their clinical practice. The article discusses alternative approaches based on reduced systems compared with current standard diagnostics. These include systems that are based on a reduced number of recording channels compared to current standard diagnostics, such as peripheral pulse oximetry or cardiopulmonary coupling, but also wearable devices (wearables) and smartphone applications as well as diagnostics using ambulatory electroencephalographic derivation. Furthermore, alternatives to the established out- and inpatient recordings are available, among others based on peripheral arterial tonometry. Innovative approaches are shown in the field of radar-based systems for contactless monitoring of sleep, as well as the use of artificial intelligence, such as for acoustic analysis of breathing sounds during sleep. Overall, these technologies represent promising advancements in sleep medicine that have the potential to improve the diagnosis and monitoring of sleep disorders. In particular, the ability to longitudinally record multiple nights in the home setting could compensate for reduced precision in the recording of biological parameters. However, only a small number of these methods has been sufficiently validated to date; furthermore, for the majority of these procedures, there is still no possibility for reimbursement under the German statutory health insurance.
Article
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Objectives To evaluate the diagnostic accuracy for obstructive sleep apnea and hypopnea (OSAH) of the OxiFlow (OF) device which combines oximetry with recording of thermistor airflow. Design & Setting Patients scheduled for overnight diagnostic polysomnography (PSG) were studied with OF either simultaneously during laboratory PSG (L-OF, n=86), at home on a separate night (H-OF, n=66), or both (n=55). Patients 97 patients with suspected OSAH, of whom 40 had OSAH defined as an apnea-hypopnea index (AHI) of more than 15 events per hour of sleep on PSG. Interventions NA Measurements & Results The automated respiratory disturbance index (RDI) generated by the OF software considerably underestimated the AHI by PSG for both L-OF and H-OF. Altering the parameters for hypopnea identification by the software did not improve this. Visual inspection of the computerized OF tracings added considerable diagnostic information, but a manual count of RDI during visual review overestimated AHI. For the identification of cases vs. non-cases of OSAH, receiver operating characteristic area-under-the-curve statistics ranged from 0.77 – 0.90 for L-OF and from 0.71 – 0.77 for H-OF. Combining automated analysis with subsequent visual inspection of OF tracings yielded an overall sensitivity of 86% and specificity of 74% for the diagnosis of OSAH during H-OF recordings. Analysis of potential technician time saved indicated a benefit from the use of OF. Conclusions OF has diagnostic utility for the identification of OSAH. However, because of hardware and software limitations, it is unclear whether this device is superior to oximetry alone.
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