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Effect of an Interdisciplinary Weight Loss and Lifestyle Intervention on Obstructive Sleep Apnea Severity: The INTERAPNEA Randomized Clinical Trial

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Importance: Obesity is the leading cause of obstructive sleep apnea (OSA); however, the effects of weight loss and lifestyle interventions on OSA and comorbidities remain uncertain. Objective: To evaluate the effect of an interdisciplinary weight loss and lifestyle intervention on OSA and comorbidities among adults with moderate to severe OSA and overweight or obesity. Design, setting, and participants: The Interdisciplinary Weight Loss and Lifestyle Intervention for OSA (INTERAPNEA) study was a parallel-group open-label randomized clinical trial conducted at a hospital-based referral center in Granada, Spain, from April 1, 2019, to October 23, 2020. The study enrolled 89 Spanish men aged 18 to 65 years with moderate to severe OSA and a body mass index (calculated as weight in kilograms divided by height in meters squared) of 25 or greater who were receiving continuous positive airway pressure (CPAP) therapy. The sole inclusion of men was based on the higher incidence and prevalence of OSA in this population, the differences in OSA phenotypes between men and women, and the known effectiveness of weight loss interventions among men vs women. Interventions: Participants were randomized to receive usual care (CPAP therapy) or an 8-week weight loss and lifestyle intervention involving nutritional behavior change, aerobic exercise, sleep hygiene, and alcohol and tobacco cessation combined with usual care. Main outcomes and measures: The primary end point was the change in the apnea-hypopnea index (AHI) from baseline to the intervention end point (8 weeks) and 6 months after intervention. Secondary end points comprised changes in other OSA sleep-related outcomes, body weight and composition, cardiometabolic risk, and health-related quality of life. Results: Among 89 men (mean [SD] age, 54.1 [8.0] years; all of Spanish ethnicity; mean [SD] AHI, 41.3 [22.2] events/h), 49 were randomized to the control group and 40 were randomized to the intervention group. The intervention group had a greater decrease in AHI (51% reduction; change, -21.2 events/h; 95% CI, -25.4 to -16.9 events/h) than the control group (change, 2.5 events/h; 95% CI, -2.0 to 6.9 events/h) at the intervention end point, with a mean between-group difference of -23.6 events/h (95% CI, -28.7 to -18.5 events/h). At 6 months after intervention, the reduction in AHI was 57% in the intervention group, with a mean between-group difference of -23.8 events/h (95% CI, -28.3 to -19.3 events/h). In the intervention group, 18 of 40 participants (45.0%) no longer required CPAP therapy at the intervention end point, and 6 of 40 participants (15.0%) attained complete OSA remission. At 6 months after intervention, 21 of 34 participants (61.8%) no longer required CPAP therapy, and complete remission of OSA was attained by 10 of 34 participants (29.4%). In the intervention vs control group, greater improvements in body weight (change, -7.1 kg [95% CI, -8.6 to -5.5 kg] vs -0.3 kg [95% CI, -1.9 to 1.4 kg]) and composition (eg, change in fat mass, -2.9 kg [95% CI, -4.5 to -1.3 kg] vs 1.4 kg [95% CI, -0.3 to 3.1 kg]), cardiometabolic risk (eg, change in blood pressure, -6.5 mm Hg [95% CI, -10.3 to -2.6 mm Hg] vs 2.2 mm Hg [95% CI, -2.1 to 6.6 mm Hg]), and health-related quality of life (eg, change in Sleep Apnea Quality of Life Index, 0.8 points [95% CI, 0.5-1.1 points] vs 0.1 points [95% CI, -0.3 to 0.4 points]) were also found at the intervention end point. Conclusions and relevance: In this study, an interdisciplinary weight loss and lifestyle intervention involving Spanish men with moderate to severe OSA and had overweight or obesity and were receiving CPAP therapy resulted in clinically meaningful and sustainable improvements in OSA severity and comorbidities as well as health-related quality of life. This approach may therefore be considered as a central strategy to address the substantial impact of this increasingly common sleep-disordered breathing condition. Trial registration: ClinicalTrials.gov Identifier: NCT03851653.
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Original Investigation | Pulmonary Medicine
Effect of an Interdisciplinary Weight Loss and Lifestyle Intervention
on Obstructive Sleep Apnea Severity
The INTERAPNEA Randomized Clinical Trial
Almudena Carneiro-Barrera, PhD; Francisco J. Amaro-Gahete, PhD; Alejandro Guillén-Riquelme, PhD; Lucas Jurado-Fasoli, MSc; Germán Sáez-Roca, MD; Carlos Martín-
Carrasco, MD; Gualberto Buela-Casal, PhD; Jonatan R. Ruiz, PhD
Abstract
IMPORTANCE Obesity is the leading cause of obstructive sleep apnea (OSA); however, the effects
of weight loss and lifestyle interventions on OSA and comorbidities remain uncertain.
OBJECTIVE To evaluate the effect of an interdisciplinary weight loss and lifestyle intervention on
OSA and comorbidities among adults with moderate to severe OSA and overweight or obesity.
DESIGN, SETTING, AND PARTICIPANTS The Interdisciplinary Weight Loss and Lifestyle
Intervention for OSA (INTERAPNEA) study was a parallel-group open-label randomized clinical trial
conducted at a hospital-based referral center in Granada, Spain, from April 1, 2019, to October 23,
2020. The study enrolled 89 Spanish men aged 18 to 65 years with moderate to severe OSA and a
body mass index (calculated as weight in kilograms divided by height in meters squared) of 25 or
greater who were receiving continuous positive airway pressure (CPAP) therapy. The sole inclusion
of men was based on the higher incidence and prevalence of OSA in this population, the differences
in OSA phenotypes between men and women, and the known effectiveness of weight loss
interventions among men vs women.
INTERVENTIONS Participants were randomized to receive usual care (CPAP therapy) or an 8-week
weight loss and lifestyle intervention involving nutritional behavior change, aerobic exercise, sleep
hygiene, and alcohol and tobacco cessation combined with usual care.
MAIN OUTCOMES AND MEASURES The primary end point was the change in the apnea-hypopnea
index (AHI) from baseline to the intervention end point (8 weeks) and 6 months after intervention.
Secondary end points comprised changes in other OSA sleep-related outcomes, body weight and
composition, cardiometabolic risk, and health-related quality of life.
RESULTS Among 89 men (mean [SD] age, 54.1 [8.0] years; all of Spanish ethnicity; mean [SD] AHI,
41.3 [22.2] events/h), 49 were randomized to the control group and 40 were randomized to the
intervention group. The intervention group had a greater decrease in AHI (51% reduction; change,
–21.2 events/h; 95% CI, –25.4 to –16.9 events/h) than the control group (change, 2.5 events/h; 95%
CI, –2.0 to 6.9 events/h) at the intervention end point, with a mean between-group difference of
–23.6 events/h (95% CI, –28.7 to –18.5 events/h). At 6 months after intervention, the reduction in AHI
was 57% in the intervention group, with a mean between-group difference of –23.8 events/h (95%
CI, –28.3 to –19.3 events/h). In the intervention group, 18 of 40 participants (45.0%) no longer
required CPAP therapy at the intervention end point, and 6 of 40 participants (15.0%) attained
complete OSA remission. At 6 months after intervention, 21 of 34 participants (61.8%) no longer
required CPAP therapy, and complete remission of OSA was attained by 10 of 34 participants
(continued)
Key Points
Question Is an interdisciplinary weight
loss and lifestyle intervention combined
with usual care (continuous positive
airway pressure [CPAP] therapy)
effective for the treatment of moderate
to severe obstructive sleep apnea (OSA)
in men with overweight or obesity?
Findings In this randomized clinical trial
involving 89 Spanish men with
moderate to severe OSA who had
overweight or obesity and were
receiving CPAP therapy, an 8-week
interdisciplinary weight loss and lifestyle
intervention significantly improved OSA
severity and other outcomes compared
with usual care alone. At 8 weeks, 45%
of participants in the intervention group
no longer required CPAP therapy; at 6
months, 62% of participants in the
intervention group no longer required
CPAP therapy.
Meaning This study’s findings suggest
that this weight loss and lifestyle
intervention might be considered as a
central strategy to address OSA and
comorbidities.
+Visual Abstract
+Supplemental content
Author affiliations and article information are
listed at the end of this article.
Open Access. This is an open access article distributed under the terms of the CC-BY License.
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Abstract (continued)
(29.4%). In the intervention vs control group, greater improvements in body weight (change, –7.1 kg
[95% CI, −8.6 to −5.5 kg] vs −0.3 kg [95% CI, −1.9 to 1.4 kg]) and composition (eg, change in fat mass,
−2.9 kg [95% CI, −4.5 to −1.3 kg] vs 1.4 kg [95% CI, −0.3 to 3.1 kg]), cardiometabolic risk (eg, change
in blood pressure, −6.5 mm Hg [95% CI, −10.3 to −2.6 mm Hg] vs 2.2 mm Hg [95% CI, −2.1 to 6.6 mm
Hg]), and health-related quality of life (eg, change in Sleep Apnea Quality of Life Index, 0.8 points
[95% CI, 0.5-1.1 points] vs 0.1 points [95% CI, −0.3 to 0.4 points]) were also found at the intervention
end point.
CONCLUSIONS AND RELEVANCE In this study, an interdisciplinary weight loss and lifestyle
intervention involving Spanish men with moderate to severe OSA and had overweight or obesity and
were receiving CPAP therapy resulted in clinically meaningful and sustainable improvements in OSA
severity and comorbidities as well as health-related quality of life. This approach may therefore be
considered as a central strategy to address the substantial impact of this increasingly common sleep-
disordered breathing condition.
TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03851653
JAMA Network Open. 2022;5(4):e228212. doi:10.1001/jamanetworkopen.2022.8212
Introduction
Obstructive sleep apnea (OSA), characterized by recurrent sleep state–dependent upper airway
collapse, is a globally recognized major public health problem affecting up to 936 million adults in the
general population, with obesity as the leading cause.
1,2
Obstructive sleep apnea has emerged as a
primary target of medical research and practice owing to its increasing prevalence and association
with increasing rates of obesity
3
and its wide spectrum of clinical and socioeconomic
consequences.
4-6
The intermittent pharyngeal obstructions occurring during sleep result in long-
term exposure to hypoxia, hypercapnia, increased sympathetic activity, oxidative stress, and
systemic inflammation.
7
Given these pathophysiological responses, OSA has been independently
associated with substantial increases in the likelihood of hypertension, dyslipidemia, diabetes, life-
threatening cardiovascular diseases, and all-cause death.
8-12
The first-line treatment for OSA is the use of a continuous positive airway pressure (CPAP)
device, which maintains upper airway patency through positive pressure applied with a nasal or
oronasal interface.
13
Although CPAP therapy is effective in reducing upper airway occlusions when
used as prescribed, adherence rates are suboptimal, and long-term benefits remain uncertain.
13-15
Although some studies have found that CPAP therapy has beneficial effects on blood pressure and
insulin resistance,
16,17
other large observational and experimental studies have reported no
significant reductions in metabolic risk or cardiovascular events after long-term CPAP therapy,
15,18-20
which suggests a complex and reciprocal interaction between OSA and obesity.
21
Weight loss attained through alternative or combined behavioral interventions appears to
substantially improve OSA and coexisting conditions among adults.
22-29
However, previous clinical
trials of alternative and behavioral interventions, although enlightening, have had limitations
inherent to study design or methods, including but not limited to stringent eligibility criteria, limited
reported outcomes, and/or nonrandomized allocation, which restricted the generalizability of
results.
24,30
Furthermore, weight loss has only been addressed through restricted diets or exercise,
without using either a combination of both components or behavioral approaches to promote
maintenance of benefits.
24
Notably, no study has, to our knowledge, focused on alcohol avoidance
and smoking cessation,
24
which are well-established behavioral risk factors associated with the
occurrence and worsening of OSA.
31,32
The Interdisciplinary Weight Loss and Lifestyle Intervention
for OSA (INTERAPNEA) randomized clinical trial sought to determine the effects of a novel
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interdisciplinary weight loss and lifestyle intervention on OSA severity and comorbidities among
adults with moderate to severe OSA who had overweight or obesity and were receiving
CPAP therapy.
33
Methods
Study Design and Oversight
The INTERAPNEA study was an investigator-initiated parallel-group open-label randomized clinical
trial designed to evaluate the effects of an 8-week interdisciplinary weight loss and lifestyle
intervention combined with usual care (ie, CPAP therapy) vs usual care alone on OSA severity
(measured by the apnea-hypopnea index [AHI]) and OSA-related comorbidities among adults with
moderate to severe OSA. The clinical trial rationale, design, and methods have been published
previously,
33
and the full protocol and statistical analysis plan are available in Supplement 1. The study
was registered and approved by all regulatory authorities and ethics committees of each
collaborating center in Spain (University of Granada, Virgen de las Nieves University Hospital, and
Junta de Andalucía), with all participants providing written informed consent. This study followed
the Consolidated Standards of Reporting Trials (CONSORT) reporting guideline for randomized
clinical trials.
Study Population
Eligible participants were men aged 18 to 65 years with moderate to severe OSA (AHI 15 events/h
of sleep) who were receiving CPAP therapy and had a body mass index (BMI; calculated as weight in
kilograms divided by height in meters squared) of 25 or greater. The sole inclusion of men was based
on the higher incidence and prevalence of OSA in this population,
2
the well-established differences in
OSA phenotypes between men and women,
34
and the effectiveness of weight loss interventions
among men vs women.
24,35-37
Exclusion criteria were current participation in a weight loss program,
presence of any psychological or psychiatric disorder, and coexistence of any other primary sleep
disorder. The eligibility criteria were based on a thorough consideration of the potential
generalizability of results; thus, no criteria regarding potential responsiveness, comorbidities,
adherence rates, or use of nonhypnotic medications were established. The study sample therefore
reflected the heterogeneity of men with OSA. Details about eligibility criteria and assessments used
to ensure inclusion feasibility are provided in Supplement 1 and eMethods 1 in Supplement 2.
Study Recruitment, Enrollment, and Randomization
Recruitment, enrollment, and randomization of participants were performed among 3 consecutive
sets of 30 to 35 participants from April 1, 2019, to January 24, 2020, with a study completion date of
October 23, 2020. Participants were recruited from the outpatient sleep-disordered breathing unit
of the collaborating hospital (Virgen de las Nieves University Hospital, Granada, Spain). Before
enrollment, potential participants received clinical and physical examinations and completed
baseline measurements to ensure inclusion feasibility. Enrolled participants were successively
randomized to receive either usual care (control group) or a weight loss and lifestyle intervention
combined with usual care (intervention group). Randomization was performed via a computer-
generated simple (unrestricted) randomization process.
38
Given the nature of the intervention, participants and clinicians were aware of clinical trial group
assignments after randomization. However, the research personnel responsible for data collection
and analysis were blinded to group assignments at the follow-up visits. In addition, rigorous
standardization procedures for data collection and intervention were followed to ensure internal and
external validity of the clinical trial.
39
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Study Assessments and End Points
Assessments at baseline, the intervention end point (8 weeks), and 6 months after intervention
included a full-night polysomnography conducted in a laboratory, a set of questionnaires, a full-body
dual-energy x-ray absorptiometry scan, and a fasting blood test. The primary end point of the
INTERAPNEA clinical trial was the change in AHI at the intervention end point and 6 months after
intervention, which was objectively measured during a level 1 sleep study (ie, polysomnography). The
AHI measures the number of apnea and hypopnea events per hour of sleep, with 0 to 4 events
indicating normal (no OSA), 5 to 14 events indicating mild OSA, 15 to 30 events indicating moderate
OSA, and more than 30 events indicating severe OSA; a change of at least 15 events is considered
clinically meaningful and would move a participant 2 levels in severity status (eg, from severe to mild
OSA, indicating a benefit for health).
Secondary end points comprised changes in other sleep-related variables (including
oxyhemoglobin desaturation index, oxygen saturation, sleep efficiency and maintenance, sleep
architecture, and subjective sleep quality [measured by the Pittsburgh Sleep Quality Index
40
; score
range, 0-21 points, with higher scores indicating worse sleep quality] and sleepiness [measured by
the Epworth Sleepiness Scale
41
; score range, 0-24 points, with higher scores indicating more daytime
sleepiness]), body weight and composition (including BMI; neck, chest, and waist circumference;
visceral adipose tissue, and lean mass), and cardiometabolic risk measurements (including blood
pressure, glucose and lipid metabolism, and liver function). Health-related quality of life (measured
by the Sleep Apnea Quality of Life Index
42
[score range, 1-7 points, with higher scores indicating
better health-related quality of life] and the physical and mental components of the Medical
Outcomes Study 36-Item Short-Form Health Survey
43,44
[score range, 0 to 100 points, with higher
scores indicating better health-related quality of life with respect to either the physical or mental
component]) and lifestyle habits (including physical activity, dietary behavior [measured by the Food
Behavior Checklist
45
; score range, 23-85 points, with higher scores indicating healthier dietary
patterns], alcohol consumption, and smoking) were also included as additional end points. Primary
and secondary sleep-related end points as well as self-reported end points related to general physical
and psychological health were measured at each study assessment after 1 week without CPAP use.
All adverse events, regardless of severity or relationship to the study intervention or
participation, were systematically recorded at each of the study assessments. Serious adverse events
were determined based on the guidelines adopted by the International Conference on
Harmonization of Good Clinical Practice.
46
Full descriptions of study assessments and end points are
provided in eMethods 2 in Supplement 2.
Study Intervention and Control Condition
The interdisciplinary weight loss and lifestyle intervention was precisely designed and implemented
based on previous research
24
and existing evidence-based clinical practice guidelines for the
management of obesity
47,48
and OSA.
4,5,22,23
Feasible implementation in clinical practice was also
considered. As a result, the intervention was conducted for 8 weeks and comprised 5 components or
modules: nutritional behavior change, moderate aerobic exercise, smoking cessation, alcohol intake
avoidance, and sleep hygiene. Each component included group-based weekly sessions of 60 to 90
minutes that were led and supervised by trained professionals (A.C.-B., F.J.A.-G., and L.J.-F.) in each
field. Participants in the intervention group also continued to receive usual care with CPAP therapy.
A detailed intervention description, including assessment of intervention adherence and integrity,
has previously been published
33
and is also provided in eMethods 3 and eMethods 4 in
Supplement 2.
In addition to usual care with CPAP therapy, participants randomized to the usual care group
received general advice on weight loss and lifestyle changes from a sleep-disordered breathing
specialist in a single 30-minute session. The opportunity to receive the INTERAPNEA clinical trial
intervention was offered to all participants at the end of the study.
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Statistical Analysis
The sample size and power of the INTERAPNEA clinical trial were estimated based on previous
studies synthesized in a recent systematic review and meta-analysis.
24
Assuming an SD of 11.98 (the
AHI pooled SD found in previous research
24
) for our primary end point, we estimated that enrollment
of 35 participants per arm would provide statistical power of 90% at α = .05 to detect a minimum
effect size of –8.36 (the pooled mean difference of previous clinical trials included in the
meta-analysis
24
) for the AHI. However, considering a maximum study withdrawal rate of 17.25% (the
mean withdrawal rate of previous studies in the meta-analysis
24
), we decided to recruit 42
participants for each study group. Owing to practical and feasibility reasons, the clinical trial was
conducted among 3 consecutive sets of 30 to 35 participants.
33
Intervention effects on primary and secondary end points were assessed using linear mixed-
effects models, with individual measures of growth being modeled as the function of randomization
group, assessment time (baseline, 8 weeks, and 6 months after intervention), and the interaction
between group and time.
49
Estimations were performed using the restricted maximum likelihood
method, including an unstructured covariance matrix to adjust for within-participant clustering
resulting from the repeated-measures design.
The model assumed that missing values were missing at random; therefore, all values presented
in the tables were model-based estimates. Nevertheless, attrition propensity was calculated using a
logistic model estimating attrition with baseline values of the set of participants, randomization
group, OSA severity, age, and BMI. Among these variables, only the set of participants significantly
estimated attrition, which was attributable to the emergence of the COVID-19 pandemic at the
clinical trial end point (the end point assessment of the third set of participants). Thus, the
assumption that missing values in the models were missing at random was further supported; the
missing at random assumption has been advocated in recent recommendations for handling missing
data in randomized clinical trials affected by a pandemic, which occurred during our study.
50
Missing
data in primary and secondary sleep-related end points and secondary body composition end points
were the result of participants withdrawing from the study before completion. The number of
missing values in secondary cardiometabolic risk end points, including glucose and lipid metabolism
and liver function end points are provided in eTable 1 in Supplement 2.
In addition, the association between changes in BMI and changes in AHI over time was
examined using repeated measures correlation analysis. This statistical technique is used to
determine the within-individual association for paired measures assessed on 2 or more occasions
among multiple individuals.
51
All estimations and analyses were performed using an intention-to-treat approach (including all
participants as they were originally randomized) and an additional per-protocol approach that was
restricted to participants with CPAP use of 4 hours or more per night on 70% of nights and, among
the intervention group, an 80% or greater attendance rate for intervention sessions. Hypothesis
testing was 2-sided, with P< .05 considered statistically significant. All analyses were conducted
using R software, version 4.0.3 (R Foundation for Statistical Computing); linear mixed-effects models
were performed using the lme4 package for R software.
49
Intervention effect assessments were based not only on statistical and practical significance but
on a practical benefit approach emphasizing and reporting unadjusted values that are intuitive to
human judgment and readily replicable considering the design and methods used in this study.
52,53
Results
Study Participants
Among 156 men initially screened for participation, 89 were enrolled and randomized to either the
control group (49 participants) or the intervention group (40 participants) (Figure 1). Overall, 14
participants (15.7%; all from the control group) were unavailable for follow-up at the intervention end
point, owing mainly to the onset of the COVID-19 pandemic (10 participants). A total of 89
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participants were thus included in the intention-to-treat analysis and, according to prespecified
adherence criteria, 75 participants were included in the additional per-protocol analysis (information
about intervention adherence is available in eMethods 4 in Supplement 2).
Among 89 men, the mean (SD) age was 54.1 (8.0) years, the mean (SD) AHI was 41.3 (22.2)
events/h, and the mean (SD) BMI was 34.4 (5.4). All participants were of Spanish ethnicity.
Participants had a mean (SD) walking distance of 5.6 (3.9) km/d; 24 participants (27.0%) were
current smokers, and 65 participants (73.0%) reported light to moderate alcohol intake. Baseline
sociodemographic and clinical characteristics were fairly well balanced between the intervention vs
control group (eg, mean [SD] age, 52.6 [7.1] years vs 55.3 [8.5] years; mean [SD] AHI, 41.6 [23.5]
events/h vs 41.1 [21.3] events/h; mean [SD] BMI, 35.0 [6.0] vs 33.9 [4.8]) (Table 1). Baseline
characteristics were equivalent when adopting a per-protocol approach (eTable 2 in Supplement 2).
Figure 1. Study Flow Diagram
156 Patients interested in participating
122 Invited to attend a compulsory
informational meeting
95 Included in baseline measurement
106 Attended meeting and were asked
to provide written informed consent
34 Did not meet eligibility criteria
16 Did not attend meeting
11 Declined to participate
6Unavailable for follow-up
3Did not attend 6-mo follow-up
assessment owing to COVID-19
pandemic
2Received positive test result for
COVID-19
1Underwent bariatric surgery
14 Unavailable for follow-up
10 Did not attend 8-wk follow-up
assessment owing to COVID-19
pandemic
2Medical reasons
2Unknown reasons
9Unavailable for follow-up
9Did not attend 6-mo follow-up
assessment owing to COVID-19
pandemic
6Did not meet inclusion criteria
5Had apnea-hypopnea index
score ≤15
1Had central apnea
89 Randomized
40 Randomized to receive intervention
40 Completed 8-wk follow-up assessment 35 Completed 8-wk follow-up assessment
34 Completed 6-mo follow-up assessment
49 Included in intention-to-treat analysis
35 Included in per-protocol analysis
40 Included in intention-to-treat analysis
40 Included in per-protocol analysis
26 Completed 6-mo follow-up assessment
49 Randomized to receive usual care
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Table 1. Baseline Participant Characteristics
Characteristic
a
Participants, No. (%)
Control group Intervention group
Total participants, No. 49 40
Age, mean (SD), y 55.3 (8.5) 52.6 (7.1)
Educational level
Primary education 13 (26.5) 10 (25.0)
Secondary education 10 (20.4) 6 (15.0)
Vocational education 13 (26.5) 17 (42.5)
Higher education 13 (26.5) 7 (17.5)
Marital status
Single 7 (14.3) 2 (5.0)
Married 34 (69.4) 34 (85.0)
Divorced 8 (16.3) 4 (10.0)
Occupational status
Employed 27 (55.1) 21 (52.5)
Self-employed 8 (16.3) 12 (30.0)
Unemployed 4 (8.2) 5 (12.5)
Retired 10 (20.4) 2 (5.0)
Medical conditions
b
Hypertension 33 (67.3) 27 (67.5)
Type 2 diabetes 12 (24.5) 10 (25.0)
Cardiovascular disease 9 (18.4) 7 (17.5)
Other 29 (59.2) 26 (65.0)
Medications
b
Antihypertensive 31 (63.3) 24 (60.0)
Statin 15 (30.6) 7 (17.5)
Oral antidiabetic 5 (10.2) 2 (5.0)
Insulin 3 (6.1) 1 (2.5)
α-Blocker 7 (14.3) 5 (12.5)
Polymedication
c
14 (28.6) 6 (15.0)
Body height, mean (SD), cm 171 (7.9) 172 (6.3)
Body weight status
Overweight 10 (20.4) 5 (12.5)
Obese
Class 1 21 (42.9) 19 (47.5)
Class 2 16 (32.7) 11 (27.5)
Class 3 2 (4.1) 5 (12.5)
OSA
Moderate 20 (40.8) 15 (37.5)
Severe 29 (59.2) 25 (62.5)
Time since OSA diagnosis, mean (SD), y 7.4 (5.7) 6.5 (6.5)
Physical activity, mean (SD), km/d 5.2 (3.9) 6.1 (3.8)
Food Behavior Checklist score, mean (SD)
d
59.1 (9.3) 59.5 (8.5)
Alcohol consumption
Never 11 (22.4) 13 (32.5)
Occasionally 12 (24.5) 8 (20.0)
Frequently 15 (30.6) 12 (30.0)
Daily 11 (22.4) 7 (17.5)
Tobacco consumption
Nonsmoker 17 (34.7) 15 (37.5)
Ex-smoker 18 (36.7) 15 (37.5)
Smoker 14 (28.6) 10 (25.0)
Abbreviation: OSA, obstructive sleep apnea.
a
No significant between-group differences were
observed in any of the baseline characteristics.
b
Participants could have more than 1 condition or
medication.
c
Defined as the use of 5 or more medications.
d
Score range, 23-85 points, with higher scores
indicating healthier dietary patterns.
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Primary and Secondary Sleep-Related End Points
Participants in the intervention group experienced a reduction in AHI from 41.6 events/h at baseline
to 20.4 events/h at the intervention end point (51% reduction; change in AHI, –21.2 events/h; 95%
CI, –25.4 to –16.9 events/h) and 17.8 events/h at 6 months after intervention (57% reduction; change
in AHI, –23.8 events/h; 95% CI, –28.3 to –19.3 events/h). No discernible differences in AHI were
observed in the control group at the intervention end point (change, 2.5 events/h; 95% CI, –2.0 to
6.9 events/h) or at 6 months after intervention (change, –0.8 events/h; 95% CI, –5.8 to 4.1 events/h).
The mean difference in AHI change between groups was –23.6 events/h (95% CI, –28.7 to –18.5
events/h; P< .001) at the intervention end point and –23.0 events/h (95% CI, –28.4 to −17.4
events/h; P< .001) at 6 months after intervention (Table 2).
According to AHI thresholds for OSA severity, at the intervention end point, 23 of 40
participants (57.5%) in the intervention group improved by 1 category, with 3 of 25 participants
(12.0%) improving from severe to mild OSA and 6 of 40 participants (15.0%) experiencing complete
remission of OSA (Figure 2; eFigure 1 in Supplement 2). At 6 months after intervention, 14 of 34
participants (41.1%) in the intervention group improved by 1 category, with 5 of 21 participants
(23.8%) improving from severe to mild OSA and 10 of 34 participants (29.4%) experiencing complete
remission of OSA. Notably, in the intervention group, 18 of 40 participants (45.0%) no longer
required CPAP therapy at the intervention end point, and 21 of 34 participants (61.8%) no longer
required CPAP therapy at 6 months after intervention; cessation of this therapy was counseled based
on OSA severity reduction to a mild category and the absence of concomitant symptoms of
sleepiness, impaired cognition, mood disturbance, insomnia, or other conditions, such as
hypertension, ischemic heart disease, or history of stroke.
In the intervention group, similar results were observed for changes in oxyhemoglobin
saturation end points (eg, oxyhemoglobin desaturation index: change at 8 weeks, −16.0 events/h
[95% CI, −21.4 to −10.7 events/h]; change at 6 months, −23.5 events/h [95% CI, −29.2 to −17.8
events/h]), sleep efficiency (change at 8 weeks, 5.7% [95% CI, 2.5%-8.8%]; change at 6 months,
7.6% [95% CI, 4.3%-10.9%]), sleep maintenance (eg, wake after sleep onset: change at 8 weeks,
−17.2 minutes [95% CI, −32.5 to −1.9 minutes]; change at 6 months, −25.8 minutes [95% CI, −41.9 to
−9.7 minutes]), sleep architecture (eg, rapid eye movement sleep: change at 8 weeks, 2.5% [95% CI,
0.3%-4.7%]; change at 6 months, 4.5% [95% CI, 2.2%-6.8%]), subjective sleep quality (Pittsburgh
Sleep Quality Index: change at 8 weeks, −2.8 points [95% CI, −3.8 to −1.8 points]; change at 6
months, −3.6 points [95% CI, −4.7 to −2.5 points]), and sleepiness (Epworth Sleepiness Scale: change
at 8 weeks, −4.6 points [95% CI, −6.3 to −2.9 points]; change at 6 months, −6.8 points [95% CI, −8.6
to −5.0 points]). These results were almost identical to those obtained using the per-protocol
approach (eTable 3 in Supplement 2).
With regard to changes from the intervention end point to 6 months after intervention,
participants in the intervention group not only maintained improvements in all sleep-related end
points but continued to experience significant improvements in oxyhemoglobin desaturation index
(change, −7.4 events/h; 95% CI, −13.1 to −1.7 events/h) and sleepiness (change in Epworth Sleepiness
Scale score, −2.2 points; 95% CI, −4.0 to −0.4 points) (eFigure 2 and eTable 4 in Supplement 2).
Individual values at baseline, the intervention end point, and 6 months after intervention and
changes in AHI (primary end point) by group are shown in Figure 2. Reductions in BMI were
significantly associated with changes in AHI over time; decreases in BMI were correlated with
reductions in AHI (r= 0.83; P< .001) (eFigure 3 in Supplement 2).
Body Composition and Cardiometabolic Risk
Participants in the intervention group had greater reductions in body weight at the intervention end
point (change, –7.1 kg; 95% CI, –8.6 to –5.5 kg) than participants in the control group (change, –0.3
kg; 95% CI, –1.9 to 1.4 kg), with a mean difference of –6.8 kg (95% CI, –8.7 to –4.9 kg; P< .001)
between groups (Table 3). Similar results were found at 6 months after intervention (change, –6.9 kg
[95% CI, –8.5 to 5.2 kg] in the intervention group vs –1.2 kg [95% CI, –3.0 to 0.6 km] in the control
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Table 2. Primary and Secondary Sleep-Related End Points
End point Control group (n = 49) Intervention group (n = 40) Mean difference between groups
a
Primary
AHI, events/h (95% CI)
Baseline 41.1 (35.3 to 46.9) 41.6 (35.1 to 48.0) NA
Change at 8 wk 2.5 (–2.0 to 6.9) –21.2 (–25.4 to –16.9) –23.6 (–28.7 to –18.5)
b
Change at 6 mo –0.8 (–5.8 to 4.1) –23.8 (–28.3 to –19.3) –23.0 (–28.4 to –17.4)
b
Secondary
Oxyhemoglobin desaturation index ≥3%, events/h (95% CI)
Baseline 45.4 (39.0 to 51.7) 45.4 (38.4 to 52.5) NA
Change at 8 wk 3.0 (–2.7 to 8.6) –16.0 (–21.4 to –10.7) –19.0 (–25.4 to –12.6)
b
Change at 6 mo –0.8 (–7.0 to 5.5) –23.5 (–29.2 to –17.8) –22.7 (–29.6 to –15.7)
b
Mean SpO
2
, % (95% CI)
Baseline 90.3 (89.3 to 91.2) 91.3 (90.3 to 92.3) NA
Change at 8 wk –0.6 (–1.8 to 0.5) 1.5 (0.4 to 2.6) 2.1 (0.8 to 3.4)
c
Change at 6 mo –0.8 (–2.1 to 0.5) 2.6 (1.4 to 3.8) 3.4 (1.9 to 4.8)
b
SpO
2
nadir, % (95% CI)
Baseline 76.8 (74.2 to 79.3) 78.1 (75.2 to 80.9) NA
Change at 8 wk 0.3 (–1.6 to 2.2) 2.8 (1.0 to 4.6) 2.5 (0.3 to 4.7)
d
Change at 6 mo –1.6 (–3.7 to 0.6) 4.4 (2.5 to 6.4) 6.0 (3.6 to 8.4)
b
Sleep time with SpO
2
<90%, % (95% CI)
Baseline 11.3 (8.2 to 14.3) 9.1 (5.7 to 12.5) NA
Change at 8 wk 1.7 (–1.8 to 5.2) –4.4 (–7.8 to –1.1) –6.1 (–10.1 to 2.1)
e
Change at 6 mo 1.1 (–2.7 to 5.0) –5.5 (–9.0 to –1.9) –6.6 (–10.9 to –2.3)
e
Sleep efficiency, % (95% CI)
Baseline 85.6 (83.6 to 87.7) 86.0 (83.8 to 88.3) NA
Change at 8 wk –1.7 (–4.9 to 1.5) 5.7 (2.5 to 8.8) 7.4 (3.7 to 11.1)
b
Change at 6 mo –1.6 (–5.2 to 1.9) 7.6 (4.3 to 10.9) 9.2 (5.2 to 13.2)
b
Sleep latency, min (95% CI)
Baseline 21.5 (17.5 to 25.6) 23.0 (18.5 to 27.5) NA
Change at 8 wk 2.9 (–4.3 to 10.1) –7.1 (–14.3 to 0.1) –10.0 (–18.3 to –1.6)
f
Change at 6 mo 4.5 (–3.3 to 12.3) –11.2 (–18.8 to –3.7) –15.7 (–24.6 to –6.8)
b
Wake after sleep onset, min (95% CI)
Baseline 54.4 (44.4 to 64.4) 47.6 (36.5 to 58.7) NA
Change at 8 wk 11.7 (–3.8 to 27.3) –17.2 (–32.5 to –1.9) –28.9 (–46.8 to –11.0)
c
Change at 6 mo 9.4 (–7.7 to 26.5) –25.8 (–41.9 to –9.7) –35.2 (–54.4 to –15.8)
b
N1 plus N2 sleep, % (95% CI)
Baseline 64.9 (62.5 to 67.3) 63.4 (60.8 to 66.0) NA
Change at 8 wk 3.4 (–0.4 to 7.1) –6.2 (–9.8 to –2.5) –9.5 (–13.9 to –5.2)
b
Change at 6 mo 4.9 (0.7 to 9.0) –8.9 (–12.8 to –5.0) –13.8 (–18.4 to –9.1)
b
N3 sleep, % (95% CI)
Baseline 20.6 (18.6 to 22.5) 20.4 (18.2 to 22.6) NA
Change at 8 wk –4.2 (–7.4 to –1.0) 3.7 (0.5 to 6.9) 7.9 (4.1 to 11.6)
b
Change at 6 mo –7.4 (–10.9 to –3.8) 4.5 (1.1 to 7.8) 11.8 (7.8 to 15.9)
b
REM sleep, % (95% CI)
Baseline 14.5 (13.2 to 15.8) 16.2 (14.8 to 17.7) NA
Change at 8 wk 0.9 (–1.3 to 3.1) 2.5 (0.3 to 4.7) 1.6 (–1.0 to 4.1)
Change at 6 mo 2.7 (0.3 to 5.1) 4.5 (2.2 to 6.8) 1.8 (–0.9 to 4.5)
AHI during REM sleep, events/h (95% CI)
Baseline 41.6 (36.0 to 47.2) 45.1 (39.0 to 51.3) NA
Change at 8 wk 5.2 (–2.6 to 13.0) –22.6 (–30.2 to –15.1) –27.8 (–36.7 to –18.9)
b
Change at 6 mo –3.6 (–12.2 to 4.9) –26.6 (–34.6 to –18.6) –23.0 (–32.6 to –13.3)
b
(continued)
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group), with a mean difference of –5.7 kg (95% CI, –7.7 to –3.6 kg; P< .001) between groups.
Participants in the intervention vs control group had greater reductions in BMI (change at 8 weeks,
−2.5 [95% CI, −3.0 to −1.9] vs −0.2 [95% CI, −0.8 to 0.4]; change at 6 months, −2.4 [95% CI, −3.0 to
−1.8] vs −0.6 [95% CI, −1.2 to 0.02]), neck circumference (change at 8 weeks, −2.3 cm [95% CI, −2.8
to −1.7 cm] vs −0.3 cm [95% CI, −0.9 to 0.2 cm]; change at 6 months, −2.9 cm [95% CI, −3.5 to −2.3]
vs 0.2 cm [95% CI, −0.5 to 0.8 cm]), chest circumference (change at 8 weeks, −3.4 cm [95% CI, −4.6
to −2.1 cm] vs 0.5 cm [95% CI, −0.8 to 1.8 cm]; change at 6 months, −4.1 cm [95% CI, −5.4 to −2.8 cm]
vs 0.7 cm [95% CI, −0.8 to 2.1 cm]), waist circumference (change at 8 weeks, −6.9 cm [95% CI, −8.3
to −5.5 cm] vs −0.2 cm [95% CI, −0.2 to 1.3 cm]; change at 6 months, −8.8 cm [95% IC, −10.3 to −7.2
cm] vs 0.3 cm [95% CI, −1.4 to 2.0 cm]), fat mass (change at 8 weeks, −2.9 kg [95% CI, −4.5 to −1.3
kg] vs 1.4 kg [95% CI, −0.3 to 3.1 kg]; change at 6 months, −6.5 kg [95% CI, −8.2 to −4.8 kg] vs 0.2 kg
[−1.7 to 2.1 kg]), and visceral adipose tissue (change at 8 weeks, −106.2 g [95% CI, −187.2 to −25.3 g]
vs 32.6 g [95% CI, −52.0 to 117.1 g]; change at 6 months, −268.4 g [95% CI, −354.3 to −182.6 g] vs
−26.3 g [95% CI, −119.7 to 67.1 g]). At 6 months after intervention, body weight decreased by 7%, fat
mass by 19%, and visceral adipose tissue by 26% in the intervention group.
Greater improvements in cardiometabolic risk (including blood pressure and glucose and lipid
metabolism) and liver function end points were also found in the intervention vs control group at
both the intervention end point (eg, change in blood pressure, −6.5 mm Hg [95% CI, −10.3 to −2.6
mm Hg] vs 2.2 mm Hg [95% CI, −2.1 to 6.6 mm Hg]; change in γ-glutamyltransferase level, −11.2 IU/L
[95% CI, −18.9 to −3.5 IU/L] vs 3.7 IU/L [95% CI, −4.7 to 12.0 IU/L]; to convert to μkat/L, multiply by
0.017) and 6 months after intervention (eg, change in blood pressure, −9.6 mm Hg [95% CI, −13.6 to
−5.5 mm Hg] vs 2.3 mm Hg [95% CI, −2.2 to 6.8 mm Hg]; change in γ-glutamyltransferase level, −14.0
IU/L [95% CI, −22.2 to −5.9 IU/L] vs 0.5 IU/L [95% CI, −8.4 to 9.5 IU/L]) (Table 3). These results were
almost identical to those obtained using the per-protocol approach (eTable 5 in Supplement 2). With
regard to changes from the intervention end point to 6 months after intervention, benefits in body
composition and cardiometabolic risk end points among the intervention group were not only
sustained but significantly increased, as revealed by significant reductions in neck circumference
(change, −0.7 cm; 95% CI, −1.2 to −0.1 cm), waist circumference (change, −1.8 cm; 95% CI, −3.3 to
Table 2. Primary and Secondary Sleep-Related End Points (continued)
End point Control group (n = 49) Intervention group (n = 40) Mean difference between groups
a
AHI during NREM sleep, events/h (95% CI)
Baseline 40.6 (34.5 to 46.7) 41.0 (34.2 to 47.8) NA
Change at 8 wk 2.2 (–2.8 to 7.1) –21.0 (–25.7 to –16.3) –23.2 (–28.7 to –17.6)
b
Change at 6 mo –1.2 (–6.6 to 4.3) –23.5 (–28.5 to –18.6) –22.4 (–28.5 to –16.3)
b
Pittsburgh Sleep Quality Index, score (95% CI)
g
Baseline 8.8 (7.7 to 9.9) 7.2 (6.0 to 8.4) NA
Change at 8 wk –0.4 (–1.5 to 0.6) –2.8 (–3.8 to –1.8) –2.3 (–3.5 to –1.1)
b
Change at 6 mo 0.2 (–1.0 to 1.3) –3.6 (–4.7 to –2.5) –3.7 (–5.0 to –2.4)
b
Epworth Sleepiness Scale, score (95% CI)
h
Baseline 9.0 (7.7 to 10.3) 10.3 (8.8 to 11.7) NA
Change at 8 wk –0.2 (–2.0 to 1.5) –4.6 (–6.3 to –2.9) –4.3 (–6.3 to –2.3)
b
Change at 6 mo –1.0 (–2.9 to 1.0) –6.8 (–8.6 to –5.0) –5.8 (–8.0 to –3.7)
b
Abbreviations: AHI, apnea-hypopnea index; N1, non–rapid eye movement stage1; N2,
non–rapid eye movement stage 2; N3, non–rapideye movement stage 3; NA, not
applicable; NREM, non–rapid eye movement; REM, rapid eye movement;SpO
2
, oxygen
saturation.
a
Derived using the group × visit interaction term from a linear mixed-effects model that
included study group, time (baseline, 8 weeks, and 6 months), and study group × time
interaction term as fixed effects and participant as random effect.
b
P< .001 for time × study group interactions.
c
P= .002 for time × study group interactions.
d
P= .03 for time × study group interactions.
e
P= .003 for time × study group interactions.
f
P= .02 for time × study group interactions.
g
Score range, 0 to 21 points, with higher scores indicating worse sleep quality.
h
Score range, 0 to 24 points, with higher scores indicating more daytime sleepiness.
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−0.3 cm), fat mass (change, −3.6 kg; 95% CI, −5.3 to −1.9 kg), and systolic blood pressure (change,
−6.0 mm Hg; 95% CI, −10.4 to −1.5 mm Hg), among others (eTable 6 in Supplement 2).
Health-Related Quality of Life and Lifestyle
Health-related quality of life in the intervention vs control group was significantly improved at the
intervention end point and 6 months after intervention, as shown by changes in scores on the Sleep
Apnea Quality of Life Index (change at 8 weeks, 0.8points [95% CI, 0.5-1.1 points] vs 0.1 points [95%
CI, −0.3 to 0.4 points]; change at 6 months, 1.1 points [95% CI, 0.7-1.5 points] vs 0.1 points [95% CI,
Figure 2. Apnea-Hypopnea Index End Point
125
100
75
50
25
0
Apnea-hypopnea index, events/h
8 wk After intervention
A
50
25
0
–25
–50
Change from baseline to 8 wk, events/h
Control Intervention
Time
Baseline 8 wk
No. of participants Time
Baseline 8 wk
49 11 40
Control group
Intervention group
125
100
75
50
25
0
Apnea-hypopnea index, events/h
6 mo After intervention
B
20
0
–20
–40
–60
Change from baseline to 6 mo, events/h
Control Intervention
Time
Baseline 6 mo
No. of participants Time
Baseline 6 mo
49 11 40
The ends of the boxes in the box plots are located at the first and third quartiles, with the
black line in the middle illustrating the median. Whiskers extend to the upper and lower
adjacent values, the location of the furthest point within a distance of 1.5 IQRs from the
first and third quartiles. The parallel line plot contains 1 vertical line for each participant,
which extends from their baseline value to their 8-week or 6-month value. Descending
lines indicate an improvement in the outcome. Baseline values are placed in ascending
order for the control group and descending order for the intervention group. The apnea-
hypopnea index measures the number of apnea and hypopnea events per hour of sleep,
with 0-4 events indicating normal (no obstructive sleep apnea [OSA]), 5-14 events
indicating mild OSA, 15-30 events indicating moderate OSA, and >30 eventsindicating
severe OSA; a change of at least 15 events is considered clinically meaningful and would
move a participant 2 levels in severity status (eg, from severe to mild OSA, indicating a
benefit for health).
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Table 3. Secondary Body Composition and Cardiometabolic Risk End Points
End point Control group (n = 49) Intervention group (n = 40)
Mean difference
between groups
a
Body weight and composition
Body weight, kg (95% CI)
Baseline 99.6 (94.5 to 104.6) 103.3 (97.6 to 108.9) NA
Change at 8 wk –0.3 (–1.9 to 1.4) –7.1 (–8.6 to –5.5) –6.8 (–8.7 to –4.9)
b
Change at 6 mo –1.2 (–3.0 to 0.6) –6.9 (–8.5 to –5.2) –5.7 (–7.7 to –3.6)
b
BMI (95% CI)
Baseline 33.9 (32.4 to 35.5) 35.0 (33.4 to 36.7) NA
Change at 8 wk –0.2 (–0.8 to 0.4) –2.5 (–3.0 to –1.9) –2.3 (–2.9 to –1.6)
b
Change at 6 mo –0.6 (–1.2 to 0.02) –2.4 (–3.0 to –1.8) –1.8 (–2.5 to –1.1)
b
Neck circumference, cm
(95% CI)
Baseline 45.5 (44.4 to 46.5) 45.0 (43.9 to 46.2) NA
Change at 8 wk –0.3 (–0.9 to 0.2) –2.3 (–2.8 to –1.7) –1.9 (–2.6 to –1.3)
b
Change at 6 mo 0.2 (–0.5 to 0.8) –2.9 (–3.5 to –2.3) –3.1 (–3.8 to –2.4)
b
Chest circumference, cm
(95% CI)
Baseline 117.4 (114.5 to 120.2) 118.0 (114.9 to 121.2) NA
Change at 8 wk 0.5 (–0.8 to 1.8) –3.4 (–4.6 to –2.1) –3.8 (–5.3 to –2.4)
b
Change at 6 mo 0.7 (–0.8 to 2.1) –4.1 (–5.4 to –2.8) –4.8 (–6.4 to –3.2)
b
Waist circumference, cm
(95% CI)
Baseline 117.9 (114.3 to 121.5) 119.0 (115.0 to 122.9) NA
Change at 8 wk –0.2 (–1.7 to 1.3) –6.9 (–8.3 to –5.5) –6.8 (–8.5 to –5.0)
b
Change at 6 mo 0.3 (–1.4 to 2.0) –8.8 (–10.3 to –7.2) –9.0 (–10.9 to –7.2)
b
Fat mass, kg (95% CI)
Baseline 33.8 (31.0 to 36.7) 34.9 (31.8 to 38.0) NA
Change at 8 wk 1.4 (–0.3 to 3.1) –2.9 (–4.5 to –1.3) –4.3 (–6.2 to –2.4)
b
Change at 6 mo 0.2 (–1.7 to 2.1) –6.5 (–8.2 to –4.8) –6.6 (–8.7 to –4.6)
b
Visceral adipose tissue, g
(95% CI)
Baseline 1049.2 (969.8 to 1128.5) 1017.3 (929.5 to 1105.2) NA
Change at 8 wk 32.6 (–52.0 to 117.1) –106.2 (–187.2 to –25.3) –138.8 (–234.7 to –42.6)
c
Change at 6 mo –26.3 (–119.7 to 67.1) –268.4 (–354.3 to –182.6) –242.2 (–346.1 to –137.8)
b
Lean mass, kg (95% CI)
Baseline 60.8 (58.3 to 63.4) 63.0 (60.2 to 65.8) NA
Change at 8 wk –2.2 (–3.5 to –0.9) –2.7 (–4.0 to –1.5) –0.5 (–2.0 to 0.9)
Change at 6 mo –1.3 (–2.7 to –0.2) 0.3 (–1.0 to 1.6) 1.6 (–0.1 to 3.2)
Cardiometabolic risk
BP
Systolic, mm Hg (95% CI)
Baseline 142.3 (138.3 to 146.3) 143.7 (139.2 to 148.1) NA
Change at 8 wk –0.7 (–5.1 to 3.6) –7.9 (–12.1 to –3.7) –7.2 (–12.2 to –2.2)
c
Change at 6 mo 2.6 (–2.2 to 7.4) –13.9 (–18.3 to –9.5) –16.5 (–21.9 to –11.1)
b
Diastolic, mm Hg
(95% CI)
Baseline 82.1 (79.0 to 85.2) 84.0 (80.6 to 87.4) NA
Change at 8 wk 0.2 (–4.4 to 4.8) –5.7 (–10.3 to –1.2) –6.0 (–11.3 to –0.6)
d
Change at 6 mo 2.0 (–3.1 to 7.1) –7.4 (–12.1 to –2.6) –9.3 (–15.1 to –3.6)
e
Mean BP, mm Hg (95% CI)
Baseline 102.2 (99.2 to 105.2) 103.9 (100.6 to 107.2) NA
Change at 8 wk 2.2 (–2.1 to 6.6) –6.5 (–10.3 to –2.6) –6.4 (–10.9 to –1.9)
c
Change at 6 mo 2.3 (–2.2 to 6.8) –9.6 (–13.6 to –5.5) –11.8 (–16.6 to –6.9)
b
(continued)
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Table 3. Secondary Body Composition and Cardiometabolic Risk End Points (continued)
End point Control group (n = 49) Intervention group (n = 40)
Mean difference
between groups
a
Glucose metabolism
Glucose, mg/dL (95% CI)
Baseline 102.0 (96.0 to 107.9) 95.5 (89.1 to 102.0) NA
Change at 8 wk 0.1 (–4.9 to 5.1) –6.7 (–11.4 to –2.0) –6.8 (–12.4 to –1.2)
f
Change at 6 mo 3.6 (–1.9 to 9.0) –6.6 (–11.6 to –1.6) –10.2 (–16.2 to –4.1)
g
Insulin, IU/mL (95% CI)
Baseline 14.1 (11.9 to 16.2) 13.0 (10.7 to 15.3) NA
Change at 8 wk 1.6 (–0.5 to 3.7) –4.9 (–6.9 to –2.9) –6.5 (–8.9 to –4.2)
b
Change at 6 mo 0.3 (–2.0 to 2.5) –5.2 (–7.3 to –3.1) –5.4 (–8.0 to –2.9)
b
HOMA-IR index,
score (95% CI)
h
Baseline 3.5 (2.7 to 4.2) 3.2 (2.3 to 4.0) NA
Change at 8 wk 0.5 (–0.6 to 1.6) –1.3 (–2.4 to –0.3) –1.9 (–3.1 to –0.6)
i
Change at 6 mo 0.4 (–0.8 to 1.6) –1.4 (–2.5 to –0.3) –1.8 (–3.1 to –0.5)
j
Lipid metabolism
Total cholesterol,
mg/dL (95% CI)
Baseline 176.4 (165.8 to 187.1) 189.6 (178.1 to 201.0) NA
Change at 8 wk 6.4 (–4.4 to 17.2) –19.4 (–29.5 to –9.3) –25.8 (–37.9 to –13.7)
b
Change at 6 mo 5.7 (–6.0 to 17.4) –16.6 (–27.3 to –5.9) –22.3 (–35.3 to –9.3)
g
HDL-C, mg/dL (95% CI)
Baseline 44.7 (41.5 to 47.8) 47.1 (43.9 to 50.3) NA
Change at 8 wk 1.9 (–0.9 to 4.8) 0.2 (–2.2 to 2.6) –1.7 (–4.7 to 1.3)
Change at 6 mo 0.7 (–2.5 to 3.8) 3.0 (0.5 to 5.4) 2.3 (–1.0 to 5.6)
LDL-C, mg/dL (95% CI)
Baseline 113.0 (103.7 to 122.3) 119.5 (110.1 to 128.9) NA
Change at 8 wk 0.5 (–8.9 to 10.0) –15.0 (–22.9 to –7.1) –15.5 (–25.5 to –5.5)
k
Change at 6 mo 8.2 (–2.3 to 18.7) –14.2 (–22.4 to –6.0) –22.4 (–33.3 to –11.6)
b
Triglycerides, mg/dL
(95% CI)
Baseline 156.5 (136.3 to 176.7) 129.5 (107.7 to 151.2) NA
Change at 8 wk 1.5 (–19.1 to 22.2) –24.5 (–43.7 to –5.2) –26.0 (–49.2 to –2.9)
d
Change at 6 mo 8.3 (–14.0 to 30.6) –23.7 (–44.1 to –3.3) –32.0 (–56.9 to –7.3)
j
Apolipoprotein A1,
mg/dL (95% CI)
Baseline 128.1 (122.4 to 133.7) 131.0 (124.9 to 137.1) NA
Change at 8 wk 5.7 (–0.5 to 12.0) –0.6 (–6.5 to 5.4) –6.3 (–13.4 to 0.7)
Change at 6 mo 0.9 (–5.5 to 7.4) 9.5 (3.6 to 15.5) 8.6 (1.4 to 15.8)
f
Apolipoprotein B,
mg/dL (95% CI)
Baseline 96.2 (89.9 to 102.6) 102.5 (95.6 to 109.3) NA
Change at 8 wk 2.2 (–4.3 to 8.8) –11.9 (–18.2 to –5.6) –14.1 (–21.6 to –6.7)
b
Change at 6 mo –1.1 (–7.8 to 5.7) –15.2 (–21.5 to –8.9) –14.1 (–21.7 to –6.6)
b
Liver function
AST, IU/L (95% CI)
Baseline 25.3 (22.3 to 28.3) 25.3 (22.2 to 28.4) NA
Change at 8 wk 0.7 (–3.6 to 5.0) –2.4 (–6.3 to 1.5) –3.1 (–7.8 to 1.6)
Change at 6 mo –0.7 (–5.1 to 3.6) –4.8 (–8.7 to –0.9) –4.0 (–8.8 to 0.7)
ALT, IU/L (95% CI)
Baseline 28.9 (24.9 to 32.9) 29.6 (25.3 to 34.0) NA
Change at 8 wk 0.5 (–4.6 to 5.6) –4.0 (–8.9 to 0.8) –4.6 (–10.4 to 1.2)
Change at 6 mo –0.2 (–5.8 to 5.3) –7.1 (–12.3 to –2.0) –6.9 (–13.1 to –0.6)
b
(continued)
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−0.3 to 0.5 points]) and the 36-Item Short-Form Health Survey (eg, physical component summary
score: change at 8 weeks, 6.0 points [95% CI, 2.4-9.7 points] vs 2.5 points [95% CI, −1.3 to 6.2
points]; change at 6 months, 6.5 points [95% CI, 2.6-10.3 points] vs −0.02 points [95% CI, −4.2 to 4.1
points]) (eTable 7 in Supplement 2). No significant changes in these health-related quality of life end
points from the intervention end point to 6 months after intervention were found (eTable 8 in
Supplement 2).
Participants in the intervention group who reported light to moderate alcohol consumption at
baseline (27 of 40 individuals [67.5%]) reduced their alcohol intake to complete abstinence from the
first week of the intervention to the intervention end point. At 6 months after intervention, 6 of 34
participants (17.5%) reported occasional alcohol intake (<1 drink/week), and 28 participants (87.5%)
maintained complete abstinence. Seven of 10 participants (70.0%) in the intervention group who
were current smokers at baseline attained complete smoking cessation at the intervention end point,
and 3 of 10 participants (30.0%) reduced their tobacco consumption by 45% to 75%. At 6 months
after intervention, 9 of 10 participants (90.0%) achieved and maintained complete smoking
cessation.
Participants in the intervention group also had significant improvements in physical activity and
dietary behaviors at both the intervention end point (change in physical activity, 8.8 km/d [95% CI,
7.3-10.4 km/d]; change in Food Behavior Checklist score, 12.0 points [95% CI, 9.5-14.5 points]) and 6
Table 3. Secondary Body Composition and Cardiometabolic Risk End Points (continued)
End point Control group (n = 49) Intervention group (n = 40)
Mean difference
between groups
a
γ-GT, IU/L (95% CI)
Baseline 44.1 (34.6 to 53.6) 38.2 (27.9 to 48.5) NA
Change at 8 wk 3.7 (–4.7 to 12.0) –11.2 (–18.9 to –3.5) –14.9 (–24.2 to –5.6)
e
Change at 6 mo 0.5 (–8.4 to 9.5) –14.0 (–22.2 to –5.9) –14.6 (–24.5 to –4.6)
i
Fatty liver index,
score (95% CI)
Baseline 85.7 (80.5 to 90.8) 86.2 (80.6 to 91.7) NA
Change at 8 wk –1.5 (–6.3 to 3.3) –13.7 (–18.0 to –9.4) –12.2 (–17.5 to –6.9)
b
Change at 6 mo –0.1 (–5.1 to 5.0) –17.5 (–22.1 to –12.9) –17.4 (–23.0 to –11.8)
b
Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index (calculated as
weight in kilograms divided by height in meters squared); BP, blood pressure; HDL-C, high-density lipoprotein cholesterol;
HOMA-IR, Homeostasis Model Assessment for Insulin Resistance; LDL-C,low-density lipoprotein cholesterol; γ-GT,
γ-glutamyltransferase; NA, not applicable.
SI conversion factors: Toconvert ALT to μkat/L, multiply by 0.017; to convert apolipoprotein A1 to g/L, multiply by 0.01; to
convert apolipoprotein B to g/L, multiply by 0.01; to convert AST to μkat/L, multiply by 0.017; to convert γ-GT to μkat/L,
multiply by 0.017; to convert glucose to mmol/L, multiply by 0.05551; to convert HDL-C to mmol/L, multiply by 0.02586;
to convert insulin to pmol/L, multiply by 6.945; to convert LDL-C to mmol/L, multiply by 0.02586; to convert total
cholesterol to mmol/L, multiply by 0.02586;to convert triglycerides to mmol/L, multiply by 0.01129.
a
Derived using the group × visit interaction term from a linear mixed-effects model that included study group, time
(baseline, 8 weeks, and 6 months), and study group × time interaction term as f ixedeffects and par ticipant as
random effect.
b
P< .001 for time × study group interactions.
c
P= .006 for time × study group interactions.
d
P= .03 for time × study group interactions.
e
P= .002 for time × study group interactions.
f
P= .02 for time × study group interactions.
g
P= .001 for time × study group interactions.
h
The HOMA-IR range in the study sample was 0.09 to 11.7. Values higher than 1.85 were considered to be indicators of
insulin resistance in this sample of Spanish men.
i
P= .005 for time × study group interactions.
j
P= .01 for time × study group interactions.
k
P= .003 for time × study group interactions.
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months after intervention (change in physical activity, 6.0 km/d [95% CI, 4.3-7.6 km/d]; change in
Food Behavior Checklist score, 9.2 points [95% CI, 6.5-11.9 points]) (eTable 9 in Supplement 2),
although slight reductions from the intervention end point to 6 months after intervention were
found in both end points (change in physical activity, −2.8 km/d [95% CI, −4.5 to −1.2 km/d]; change
in Food Behavior Checklist score, −2.8 points [95% CI, −5.5 to −0.1 points]) (eTable 10 in
Supplement 2). No discernible differences in lifestyle habits were found among participants in the
control group from baseline to the intervention end point or from baseline to 6 months after
intervention.
Adverse Events
No serious adverse events that led to death, life-threatening illness, permanent impairment, or
hospitalization with serious health conditions, related or unrelated to the study intervention or
participation, occurred from baseline to the intervention end point or from baseline to 6 months
after intervention.
Discussion
This randomized clinical trial showed that a novel 8-week interdisciplinary weight loss and lifestyle
intervention that was carefully designed to conform to existing evidenced-based clinical practice
guidelines
22,23,47,48
led to improvement or even remission of OSA and coexisting conditions among
adults with moderate to severe OSA who had overweight or obesity and were receiving CPAP
therapy. Although recommended, weight loss and lifestyle interventions for OSA treatment are rarely
implemented for the care of patients with this condition because of the modest quality of evidence
and the methodological weaknesses present in this field of research.
22,23
The weight loss and lifestyle intervention group had a clinically meaningful reduction in AHI of
51% at the intervention end point; 15.0% of participants attained complete remission of OSA, and
45.0% no longer required CPAP therapy. After 6 months, the reduction in AHI was 57%; complete
remission of OSA was attained by 29.4% of participants, and 61.8% no longer required CPAP therapy.
The intervention group notably exhibited similar reductions of 7% in body weight, 19% in fat mass,
and 26% in visceral adipose tissue at 6 months after intervention. Furthermore, these results were
strengthened by the evidence of significant improvement in important cardiometabolic end points
involved in the pathogenesis of cardiovascular diseases. Based on reductions in systolic and diastolic
blood pressure observed at the intervention end point, which were not only sustained but
significantly increased at 6 months after intervention, the intervention group may have lowered their
risk of stroke death by 40% and lowered their risk of death from ischemic heart disease or other
vascular causes by 30%.
54
To our knowledge, these results are representative of the best achieved using current
behavioral approaches.
24
The mechanisms by which weight loss and lifestyle changes substantially
ameliorate OSA and coexisting conditions are probably multifactorial. Gathered evidence suggests
that almost 60% of moderate to severe OSA is associated with obesity,
55
which contributes to
alterations of the airway anatomy and collapsibility as well as respiratory modulation.
21
We found
that reductions in BMI were significantly associated with changes in AHI over time. Adverse lifestyle
behaviors, such as poor diet, low physical activity levels, smoking, and alcohol intake, have also been
reported to be associated with OSA independent of body habitus.
31-33,56
Thus, a combination of both
weight loss and lifestyle changes may even resolve OSA in individuals with overweight or obesity.
5,23
In addition, there is a well-recognized dose-dependent relationship between weight loss and
improvement in cardiometabolic end points, with weight loss of even 5% resulting in enhanced
metabolic function.
57
Given that OSA and obesity act synergistically and have independent
associations with cardiovascular risk,
21
the beneficial effects of weight loss on cardiometabolic risk
factor profiles are likely to be heightened in patients with both obesity and OSA.
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Strengths and Limitations
This study has several strengths. A major strength is the balance in the efficacy-effectiveness
continuum achieved by our clinical trial, with a satisfactory internal validity accompanied by a high
degree of generalizability due to our inclusion and exclusion criteria.
30
The eligibility criteria were
based on a thorough consideration of the potential generalizability of results; thus, no criteria
regarding potential responsiveness, comorbidities, adherence rates, or use of nonhypnotic
medications were established. Our sample therefore reflected the heterogeneity of the population
with OSA. Given the study design and significant results obtained, this clinical trial may provide a
clear and compelling rationale for the use of an alternative approach that is readily adaptable to real-
world practice settings. Another strength is the study’s inclusion of smoking and alcohol avoidance,
factors that have not been previously considered despite their recognized association with the
occurrence and worsening of OSA.
31,32
The study also has limitations. A main limitation is the sole inclusion of men in the study sample;
the generalization of our findings is therefore limited to this population. The sample also included
only Spanish participants; thus, our results are restricted to this ethnic population. Although this
study included a 6-month follow-up assessment, the study’s duration may not have been sufficient
to determine long-term intervention effects and maintenance of benefits. Due to ethical
considerations, we did not include any group for whom no therapy was provided; CPAP therapy is the
standard of care for moderate to severe OSA, and the inclusion of a group not receiving CPAP therapy
may not be feasible.
22
Conclusions
In this randomized clinical trial involving Spanish men with moderate to severe OSA receiving CPAP
therapy, an 8-week interdisciplinary weight loss and lifestyle intervention resulted in clinically
meaningful and sustainable improvements in specific OSA-related outcomes and cardiometabolic
comorbidities as well as increased health-related quality of life. Given the high prevalence of OSA, its
complex and reciprocal interaction with obesity, and the fact that both conditions are readily
treatable through an integrated behavioral intervention, health care professionals and policy makers
might consider this approach as a central strategy to address the substantial impact of OSA on the
health and welfare of populations.
ARTICLE INFORMATION
Accepted for Publication: February 28, 2022.
Published: April 22, 2022. doi:10.1001/jamanetworkopen.2022.8212
Open Access: This is an open access article distributed under the terms of the CC-BY License.©2022
Carneiro-Barrera A et al. JAMA Network Open.
Corresponding Author: Almudena Carneiro-Barrera, PhD, Sleep and Health Promotion Laboratory, Mind, Brain
and Behavior Research Centre (CIMCYC), University of Granada, 18011 Granada, Spain (acarneiro@ugr.es).
Author Affiliations: Sleep and Health Promotion Laboratory, Mind, Brain and Behavior ResearchCentre,
University of Granada, Granada, Spain (Carneiro-Barrera, Guillén-Riquelme, Buela-Casal); Clinical
Psychophysiology and Health Promotion Research Group, Ciencias y Técnicas de la Salud 261, University of
Granada, Granada, Spain (Carneiro-Barrera, Guillén-Riquelme, Buela-Casal); Department of Personality, Evaluation
and Psychological Treatment, Faculty of Psychology, University of Granada, Granada, Spain (Carneiro-Barrera,
Buela-Casal); Promoting Fitness and Health Through Physical Activity Research Group, Sport and Health University
Research Institute, Department of Physical Education and Sports, Facultyof Spor t Sciences, Universityof Granada,
Granada, Spain (Carneiro-Barrera, Amaro-Gahete, Jurado-Fasoli, Ruiz); EFFECTS-262 Research Group,
Department of Medical Physiology, School of Medicine, University of Granada,Granada, Spain (Amaro-Gahete,
Jurado-Fasoli); Unidad de Trastornos Respiratorios del Sueño, Servicio de Neumología, Hospital Universitario
Virgen de las Nieves, Granada, Spain (Sáez-Roca, Martín-Carrasco).
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Author Contributions: Dr Carneiro-Barrera had full access to all of the data in the study and takes responsibility for
the integrity of the data and the accuracy of the data analysis.
Concept and design: Carneiro-Barrera, Amaro-Gahete, Guillén-Riquelme, Jurado-Fasoli, Sáez-Roca, Buela-
Casal, Ruiz.
Acquisition, analysis, or interpretation of data: Carneiro-Barrera, Amaro-Gahete, Guillén-Riquelme, Martín-
Carrasco, Buela-Casal, Ruiz.
Drafting of the manuscript: Carneiro-Barrera, Amaro-Gahete, Ruiz.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Carneiro-Barrera, Amaro-Gahete, Guillén-Riquelme.
Obtained funding: Carneiro-Barrera, Amaro-Gahete, Buela-Casal.
Administrative, technical, or material support: Carneiro-Barrera, Amaro-Gahete, Guillén-Riquelme, Jurado-Fasoli,
Martín-Carrasco, Buela-Casal, Ruiz.
Supervision: Carneiro-Barrera, Amaro-Gahete, Martín-Carrasco, Buela-Casal, Ruiz.
Conflict of Interest Disclosures: None reported.
Funding/Support: This study was supported by grants FPU16/01093 (Dr Carneiro-Barrera), FPU14/04172 (Dr
Amaro-Gahete), and FPU19/01609 (Mr Jurado-Fasoli) from the Spanish Ministry of Education and Vocational
Training; grant SOMM17/6107/UGR (via European Regional Development Funds) from the Junta de Andalucía,
Consejería de Conocimiento, Investigación y Universidades (Dr Ruiz); and funding from the University of Granada-
LoMonaco S.L. Sleep Research Cathedra and the University of Granada Plan Propio de Investigación 2016–
Excellence Actions: Unit of Excellence on Exercise and Health.
Role of the Funder/Sponsor:The funding organizations had no role in the design and conduct of the study;
collection, management, analysis, and interpretation of the data; preparation, review, or approval of the
manuscript; and decision to submit the manuscript for publication.
Data Sharing Statement: See Supplement 3.
Additional Contributions: We express our deepest gratitude to the participants for their involvement in the study.
Lo Monaco S.L. and TEA Ediciones S.A. provided valuable equipment and technical support for research. Imran
Khan, MSc, of the University of Greenwich, London, United Kingdom, provided diligent writing assistance and
language editing. He was not compensated outside his usual salary.
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SUPPLEMENT 1.
Trial Protocol
SUPPLEMENT 2.
eMethods 1. Study Organization and Eligibility Criteria
eMethods 2. Study Assessments and End Points
eMethods 3. Weight Loss and Lifestyle Intervention
eMethods 4. Assessment of Adherence and Integrity of Intervention and Intervention Adherence
eTable 1. Missing Values in Secondary Cardiometabolic Risk End Points
eTable 2. Baseline Characteristics of Study Participants (Per-Protocol Approach)
eTable 3. Primary and Secondary Sleep-Related End Points (Per-Protocol Approach)
eTable 4. Primary and Secondary Sleep-Related End Points (Change From 8 Weeks to 6 Months)
eTable 5. Secondary Body Composition and Cardiometabolic Risk End Points (Per-ProtocolApproach)
eTable 6. Secondary Body Composition and Cardiometabolic Risk End Points (Change From 8 Weeks to 6 Months)
eTable 7. Health-Related Quality of Life End Points
eTable 8. Health-Related Qualityof Life End Points (Change From 8 Weeks to 6 Months)
eTable 9.Physical Activity and Dietar y BehaviorEnd Points
eTable 10.Physical Ac tivityand Die tary Behavior End Points(Change From 8 Weeks to 6 Months)
eFigure 1. Obstructive Sleep Apnea Severity at Baseline and 8 Weeks After Intervention in the Intervention Group
eFigure 2. Apnea-Hypopnea Index End Point (Change From 8 Weeks to 6 Months)
eFigure 3. Association Between Changes in Apnea-Hypopnea Index Over Time and Changes in Body Mass Index
eReferences
SUPPLEMENT 3.
Data Sharing Statement
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... BMI ranked second in importance, highlighting obesity as a significant risk factor for OSA. Obesity contributes to reduced lung volume, pharyngeal diameter reduction, and fatty deposits in the pharyngeal wall, all contributing to airway narrowing (Carneiro-Barrera et al., 2022). Age also featured prominently as important parameters, with older populations and males being more prone to OSA. ...
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Objective To develop a robust machine learning prediction model for the automatic screening and diagnosis of obstructive sleep apnea (OSA) using five advanced algorithms, namely Extreme Gradient Boosting (XGBoost), Logistic Regression (LR), Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), and Random Forest (RF) to provide substantial support for early clinical diagnosis and intervention. Methods We conducted a retrospective analysis of clinical data from 439 patients who underwent polysomnography at the Affiliated Hospital of Xuzhou Medical University between October 2019 and October 2022. Predictor variables such as demographic information [age, sex, height, weight, body mass index (BMI)], medical history, and Epworth Sleepiness Scale (ESS) were used. Univariate analysis was used to identify variables with significant differences, and the dataset was then divided into training and validation sets in a 4:1 ratio. The training set was established to predict OSA severity grading. The validation set was used to assess model performance using the area under the curve (AUC). Additionally, a separate analysis was conducted, categorizing the normal population as one group and patients with moderate-to-severe OSA as another. The same univariate analysis was applied, and the dataset was divided into training and validation sets in a 4:1 ratio. The training set was used to build a prediction model for screening moderate-to-severe OSA, while the validation set was used to verify the model's performance. Results Among the four groups, the LightGBM model outperformed others, with the top five feature importance rankings of ESS total score, BMI, sex, hypertension, and gastroesophageal reflux (GERD), where Age, ESS total score and BMI played the most significant roles. In the dichotomous model, RF is the best performer of the five models respectively. The top five ranked feature importance of the best-performing RF models were ESS total score, BMI, GERD, age and Dry mouth, with ESS total score and BMI being particularly pivotal. Conclusion Machine learning-based prediction models for OSA disease grading and screening prove instrumental in the early identification of patients with moderate-to-severe OSA, revealing pertinent risk factors and facilitating timely interventions to counter pathological changes induced by OSA. Notably, ESS total score and BMI emerge as the most critical features for predicting OSA, emphasizing their significance in clinical assessments. The dataset will be publicly available on my Github.
... In these circumstances, lifestyle changes such as physical exercise and diet can favor significant improvements. A study from 2022 showed that these habits significantly reduced the AHI, with 15% of the observed group achieving complete remission of OSA and 45% not requiring CPAP [46]. According to Gambino and colleagues (2022), even if the expected effects do not meet the estimates, weight loss and physical activity should always be recommended to obese patients with OSA. ...
Article
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Introduction Obstructive sleep apnea (OSA) is a chronic disease with a high populational prevalence that is characterized as airway closure during sleep. Treatment is multidisciplinary and varies according to each case. Continuous positive airway pressure (CPAP), oral appliances, and surgery are the primary therapeutic options. Non-invasive conservative treatments such as sleep hygiene, positional therapy, physical exercises, and weight loss aim to reduce the worsening of the disease while being complementary to the invasive primary treatment. Objective To analyze the impact of non-invasive conservative therapies on the clinical manifestations of OSA syndrome (OSA), compared with other interventions. Method This was a systematic review with meta-analysis. The searches were performed without filters for the time period, type of publication, or language. Randomized clinical trials on subjects over 18 years of age diagnosed with untreated OSA were included. Responses to non-invasive conservative treatment were compared with responses to the primary intervention. Primary outcomes were assessed using the Epworth Sleepiness Scale and/or Functional Outcomes of Sleep Questionnaire (FOSQ). Results A total of eight studies were included in the review. The heterogeneity of the effect was estimated at 89.77%. Six studies compared conservative treatment with CPAP, one with oral appliances, and one with oropharyngeal exercises. Using the Epworth Sleepiness Scale measurements, the standardized difference in the estimated means, based on the random-effects model, was 0.457 (95% CI (1.082 to 0.169)) and the mean result did not differ significantly from zero (z = 1.43; p = 0.153). The conservative therapies assessed in this study improved the subjective quality of sleep, although the post-treatment ESE scores did not show significant results. The reduction in AHI and better outcomes in the evaluated domains, as well as in cognition and mood, were superior in the groups that received CPAP and IOD. Conclusion The most commonly used treatments of choice for OSA are invasive, including the use of CPAP, oral appliances, and surgeries, being the most utilized options. This study demonstrated that non-invasive conservative treatments, such as sleep hygiene, yield results as effective as invasive treatments. Further studies are needed to confirm this result and to predict whether invasive treatment can be used as the primary treatment or only as a supplement.
... As discussed, obesity imposes mechanical stress on the UA and co-occurring obese physiology results in the genesis of a dysmetabolic state. As such, weight loss attained from either lifestyle intervention (diet and/or exercise) or pharmacological treatments should be considered central to OSA/MetS to mitigate onset, severity and future cardiometabolic risk [125]. Current obesity guidelines advocate 5-10% weight loss over 6 months to provide health benefits for most overweight and obese individuals; however, beyond this consensus, official and specific dietary guidelines for MetS and OSA are lacking [126]. ...
Article
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Obstructive sleep apnoea (OSA) and components of metabolic syndrome (MetS) are inextricably connected. Considering the increasing burden of MetS and OSA, in the present review, we aimed to collate and summarise the potential pathophysiological mechanisms linking these pathologies. In short, obesity appears to promote OSA development via multiple pathways, some of which are not directly related to mass but rather to metabolic complications of obesity. Simultaneously, OSA promotes weight gain through central mechanisms. On the other hand, diabetes mellitus contributes to OSA pathophysiology mainly through effects on peripheral nerves and carotid body desensitization, while intermittent hypoxia and sleep fragmentation are the principal culprits in OSA-mediated diabetes. Apart from a bidirectional pathophysiological relationship, obesity and diabetes mellitus together additively increase cardiovascular risk in OSA patients. Additionally, the emergence of new drugs targeting obesity and unequivocal results of the available studies underscore the need for further exploration of the mechanisms linking MetS and OSA, all with the aim of improving outcomes in these patients.
Article
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Purpose The reciprocal comorbidity of obstructive sleep apnea (OSA) and body mass index (BMI) has been observed, yet the shared genetic architecture between them remains unclear. This study aimed to explore the genetic overlaps between them. Methods Summary statistics were acquired from the genome-wide association studies (GWASs) on OSA (Ncase = 41,704; Ncontrol = 335,573) and BMI (Noverall = 461,460). A comprehensive genome-wide cross-trait analysis was performed to quantify global and local genetic correlation, infer the bidirectional causal relationships, detect independent pleiotropic loci, and investigate potential comorbid genes. Results A positive significant global genetic correlation between OSA and BMI was observed (rg = 0.52, P = 2.85e-122), which was supported by three local signal. The Mendelian randomization analysis confirmed bidirectional causal associations. In the meta-analysis of cross-traits GWAS, a total of 151 single-nucleotide polymorphisms were found to be pleiotropic between OSA and BMI. Additionally, we discovered that the genetic association between OSA and BMI is concentrated in 12 brain regions. Finally, a total 134 expression-tissue pairs were observed to have a significant impact on both OSA and BMI within the specified brain regions. Conclusion Our comprehensive genome-wide cross-trait analysis indicates a shared genetic architecture between OSA and BMI, offering new perspectives on the possible mechanisms involved.
Chapter
Obstructive sleep apnea is a sleep-related breathing disorder characterized by repetitive upper airway obstruction and is associated with significant morbidity and mortality. Obesity is one of the primary modifiable risk factors for the management of patients with sleep apnea as there is a positive association between the increasing obesity prevalence and sleep apnea prevalence. Several mechanisms link obesity and sleep apnea pathogenesis, including the potential increase in additional mechanical load on the upper and lower respiratory systems from regional adiposity, possible effects of obesity-related inflammation on neuromuscular and neuroventilatory function of the upper airway, or a combination of these effects. By examining the relationship between obesity and obstructive sleep apnea as well as the mechanisms by which obesity may contribute to the development of sleep apnea and its related comorbidities, we can evaluate the effect of weight reduction on the management of sleep apnea.
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A apneia obstrutiva do sono (AOS) é uma patologia de alta prevalência e impacto deletério na saúde em função disso é um distúrbio o qual vem sendo cada vez mais estudado. A AOS é caracterizada por colapsos repetidos das vias aéreas superiores durante o sono, trazendo à esfacelação do sono, hipóxia e outros problemas. A obesidade, a idade, os hábitos de vida destoantes e o sexo são fatores de risco para a AOS. O tratamento padrão é o uso de pressão positiva contínua nas vias aéreas (CPAP), porém mudanças no estilo de vida, como modificação na dieta, exercícios e perda de peso, também são recomendadas. Foi realizada uma busca por trabalhos prévios nas bases de dados PubMed e Portal Regional da BVS e um total de 17 artigos científicos foram incluídos após a aplicação de critérios de inclusão e exclusão. Através das análises dos estudos foi visto que grande parte disserta a favor da mudança no estilo de vida e redução de peso evidenciando que são favoráveis na melhora da AOS, reduzindo a gravidade da doença e melhorando a qualidade de vida, outros artigos divulgam a importância da inclusão da tecnologia na busca por tal causa de se beneficiar na melhora da patologia e por fim há alguns pontos que abordam o tempo nesse quesito de tratamento. Visto isso, é fundamental que possamos fornecer e saber a devida importância das alterações na maneira de viver sobre a patologia AOS, redução de peso, exercícios físicos e outras medidas saudáveis são impactantes.
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Introduction Obstructive sleep apnoea (OSA) and obesity commonly coexist. Weight loss and exercise are recommended management options for OSA. However, most of the current evidence on diet and OSA is focused on calorie restriction rather than diet quality. The aim of the present study was to determine the association of plant-based dietary indices (PDI) with OSA risk. Methods Cross-sectional data from 14 210 participants of the National Health and Nutrition Examination Survey who provided dietary information using the 24-hour recall method were used. PDI – including healthy (hPDI), unhealthy (uPDI) and pro-vegetarian diet index (PVDI) – were determined. OSA risk was determined using the STOP-BANG questionnaire. Logistic regression was used to determine the relationship between dietary indices and OSA risk. Results Higher adherence to PDI (odds ratio (OR) Q5 versus Q1 =0.81; 95% confidence interval (CI): 0.66–1.00), hPDI (OR=0.83; 95% CI: 0.69–1.01) and PVDI (OR=0.84; 95% CI: 0.68–1.05) was inversely associated with OSA risk, whereas higher consumption of an unhealthy plant-based diet (OR=1.22; 95% CI: 1.00–1.49) was positively associated with OSA. Sex differences in estimates were observed for PDI in males (OR=0.71; 95% CI: 0.56–0.90) versus females (OR=0.93; 95% CI: 0.68–1.28), hPDI in males (OR=0.90; 95% CI: 0.68–1.18) versus females (OR=0.77; 95% CI: 0.54–1.09) and uPDI in males (OR=1.13; 95% CI: 0.89–1.44) versus females (OR=1.42; 95% CI: 1.03–1.97) but not for PVDI. Conclusions Higher adherence to a healthy plant-based diet is associated with reduced OSA risk, while an unhealthy plant-based diet has a positive association. The magnitude of these associations differs by sex. Further longitudinal studies are warranted.
Article
Purpose of review This review addresses the evolving intersection of sleep-disordered breathing (SDB) and heart failure, a topic of increasing clinical significance due to the high prevalence of SDB in heart failure patients and its impact on morbidity and mortality. It reflects recent advancements in diagnostic methodologies and therapeutic strategies. It emphasizes the need for heightened awareness among healthcare providers about the complex relationship between SDB and various forms of heart failure. Recent findings Recent studies underscore the high incidence of SDB in heart failure patients, varying with the cause of heart failure. Emerging diagnostic tools, including home sleep tests and advanced inpatient screening methods, have improved the early detection and accurate diagnosis of SDB. Novel treatment modalities, like hypoglossal and phrenic nerve stimulation, are promising, especially where conventional therapies are inadequate. The review also discusses the complexities of managing SDB in the context of different heart failure subtypes. Summary Findings from recent literature suggest that improved screening, diagnosis, and innovative treatment of SDB in heart failure patients can reduce morbidity, mortality, and healthcare costs. This review emphasizes the need for personalized treatment approaches tailored to individual patient profiles, highlighting the potential of new technologies and multidisciplinary strategies in clinical practice.
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Background: The coronavirus pandemic (Covid-19) presents a variety of challenges for ongoing clinical trials, including an inevitably higher rate of missing outcome data, with new and non-standard reasons for missingness. International drug trial guidelines recommend trialists review plans for handling missing data in the conduct and statistical analysis, but clear recommendations are lacking. Methods: We present a four-step strategy for handling missing outcome data in the analysis of randomised trials that are ongoing during a pandemic. We consider handling missing data arising due to (i) participant infection, (ii) treatment disruptions and (iii) loss to follow-up. We consider both settings where treatment effects for a 'pandemic-free world' and 'world including a pandemic' are of interest. Results: In any trial, investigators should; (1) Clarify the treatment estimand of interest with respect to the occurrence of the pandemic; (2) Establish what data are missing for the chosen estimand; (3) Perform primary analysis under the most plausible missing data assumptions followed by; (4) Sensitivity analysis under alternative plausible assumptions. To obtain an estimate of the treatment effect in a 'pandemic-free world', participant data that are clinically affected by the pandemic (directly due to infection or indirectly via treatment disruptions) are not relevant and can be set to missing. For primary analysis, a missing-at-random assumption that conditions on all observed data that are expected to be associated with both the outcome and missingness may be most plausible. For the treatment effect in the 'world including a pandemic', all participant data is relevant and should be included in the analysis. For primary analysis, a missing-at-random assumption - potentially incorporating a pandemic time-period indicator and participant infection status - or a missing-not-at-random assumption with a poorer response may be most relevant, depending on the setting. In all scenarios, sensitivity analysis under credible missing-not-at-random assumptions should be used to evaluate the robustness of results. We highlight controlled multiple imputation as an accessible tool for conducting sensitivity analyses. Conclusions: Missing data problems will be exacerbated for trials active during the Covid-19 pandemic. This four-step strategy will facilitate clear thinking about the appropriate analysis for relevant questions of interest.
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Obesity is a major risk factor for obstructive sleep apnoea (OSA), the most common sleep-disordered breathing related to neurocognitive and metabolic syndromes, type II diabetes, and cardiovascular diseases. Although strongly recommended for this condition, there are no studies on the effectiveness of an interdisciplinary weight loss and lifestyle intervention including nutrition, exercise, sleep hygiene, and smoking and alcohol cessation. INTERAPNEA is a randomised controlled trial with a two-arm parallel design aimed at determining the effects of an interdisciplinary tailored weight loss and lifestyle intervention on OSA outcomes. The study will include 84 males aged 18-65 with a body mass index of ≥25 kg/m 2 and severe to moderate OSA randomly assigned to usual care (i.e., continuous positive airway pressure), or interdisciplinary weight loss and lifestyle intervention combined with usual care. Outcomes will be measured at baseline, intervention end-point, and six-month post-intervention, including apnoea-hypopnoea index (primary outcome), other neurophysical and cardiorespiratory polysomnographic outcomes, sleep quality, daily functioning and mood, body weight and composition, physical fitness, blood biomarkers, health-related quality of life, and cost-effectiveness. INTERAPNEA may serve to establish a cost-effective treatment not only for the improvement of OSA and its vast and severe comorbidities, but also for a potential remission of this condition.
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Relying on effect size as a measure of practical significance is turning out to be just as misleading as using p-values to determine the effectiveness of interventions for improving clinical practice in complex organizations such as schools. This article explains how effect sizes have misdirected practice in education and other disciplines. Even when effect size is incorporated into RCT research the recommendations of whether interventions are effective are misleading and generally useless to practitioners. As a result, a new criterion of practical benefit is recommended for evaluating research findings about the effectiveness of interventions in complex organizations where benchmarks of existing performance exist. Practical benefit exists when the unadjusted performance of an experimental group provides a noticeable advantage over an existing benchmark. Some basic principles for determining practical benefit are provided. Practical benefit is more intuitive and is expected to enable leaders to make more accurate assessments as to whether published research findings are likely to produce noticeable improvements in their organizations. In addition, practical benefit is used routinely as the research criterion for the alternative scientific methodology of improvement science that has an established track record of being a more efficient way to develop new interventions that improve practice dramatically than RCT research. Finally, the problems with practical significance suggest that the research community should seek different inferential methods for research designed to improve clinical performance in complex organizations, as compared to methods for testing theories and medicines.
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Introduction: Obstructive sleep apnea (OSA) is a widely prevalent sleep-related breathing disorder, which leads to several life-threatening diseases. OSA has systemic effects on various organ systems. Untreated OSA is associated with long-term health consequences including hypertension, heart disease, diabetes, depression, metabolic disorders, and stroke. In addition, untreated OSA was reported to be associated with cognitive dysfunction, impaired productivity at the workplace and increased risk of motor vehicle accidents (MVAs) resulting in injury and fatality. Other consequences of OSA include, but not limited to, impaired vigilance, daytime somnolence, performance deficits, morning headaches, mood disturbances, neurobehavioral impairments, and general malaise. Additionally, OSA has become an economic burden on most health systems all over the world. Many legal driving license regulations have been developed to reduce MVAs among OSA patients. Methods: The personal, societal, public health and legal aspects of OSA are reviewed. Data were collected through the following databases: MEDLINE, Google Scholar, Scopus, SAGE Research Methods, and ScienceDirect. Conclusion: OSA leads to worsening of patients’ personal relationships, decreasing work productivity, and increasing occupational accidents as well as MVAs. The costs of undiagnosed and untreated OSA to healthcare organizations are excessive. Thus, proper management of OSA will benefit not only the patient but also provide widespread benefits to society as a whole
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Importance Cardiovascular disease is the leading cause of death in the US, and poor diet and lack of physical activity are major factors contributing to cardiovascular morbidity and mortality. Objective To review the benefits and harms of behavioral counseling interventions to improve diet and physical activity in adults with cardiovascular risk factors. Data Sources MEDLINE, PubMed, PsycINFO, and the Cochrane Central Register of Controlled Trials through September 2019; literature surveillance through July 24, 2020. Study Selection English-language randomized clinical trials (RCTs) of behavioral counseling interventions to help people with elevated blood pressure or lipid levels improve their diet and increase physical activity. Data Extraction and Synthesis Data were extracted from studies by one reviewer and checked by a second. Random-effects meta-analysis and qualitative synthesis were used. Main Outcomes and Measures Cardiovascular events, mortality, subjective well-being, cardiovascular risk factors, diet and physical activity measures (eg, minutes of physical activity, meeting physical activity recommendations), and harms. Interventions were categorized according to estimated contact time as low (≤30 minutes), medium (31-360 minutes), and high (>360 minutes). Results Ninety-four RCTs were included (N = 52 174). Behavioral counseling interventions involved a median of 6 contact hours and 12 sessions over the course of 12 months and varied in format and dietary recommendations; only 5% addressed physical activity alone. Interventions were associated with a lower risk of cardiovascular events (pooled relative risk, 0.80 [95% CI, 0.73-0.87]; 9 RCTs [n = 12 551]; I² = 0%). Event rates were variable; in the largest trial (Prevención con Dieta Mediterránea [PREDIMED]), 3.6% in the intervention groups experienced a cardiovascular event, compared with 4.4% in the control group. Behavioral counseling interventions were associated with small, statistically significant reductions in continuous measures of blood pressure, low-density lipoprotein cholesterol levels, fasting glucose levels, and adiposity at 12 to 24 months’ follow-up. Measurement of diet and physical activity was heterogeneous, and evidence suggested small improvements in diet consistent with the intervention recommendation targets but mixed findings and a more limited evidence base for physical activity. Adverse events were rare, with generally no group differences in serious adverse events, any adverse events, hospitalizations, musculoskeletal injuries, or withdrawals due to adverse events. Conclusions and Relevance Medium- and high-contact multisession behavioral counseling interventions to improve diet and increase physical activity for people with elevated blood pressure and lipid levels were effective in reducing cardiovascular events, blood pressure, low-density lipoproteins, and adiposity-related outcomes, with little to no risk of serious harm.
Article
Importance Obstructive sleep apnea (OSA) affects 17% of women and 34% of men in the US and has a similar prevalence in other countries. This review provides an update on the diagnosis and treatment of OSA. Observations The most common presenting symptom of OSA is excessive sleepiness, although this symptom is reported by as few as 15% to 50% of people with OSA in the general population. OSA is associated with a 2- to 3-fold increased risk of cardiovascular and metabolic disease. In many patients, OSA can be diagnosed with home sleep apnea testing, which has a sensitivity of approximately 80%. Effective treatments include weight loss and exercise, positive airway pressure, oral appliances that hold the jaw forward during sleep, and surgical modification of the pharyngeal soft tissues or facial skeleton to enlarge the upper airway. Hypoglossal nerve stimulation is effective in select patients with a body mass index less than 32. There are currently no effective pharmacological therapies. Treatment with positive airway pressure lowers blood pressure, especially in patients with resistant hypertension; however, randomized clinical trials of OSA treatment have not demonstrated significant benefit on rates of cardiovascular or cerebrovascular events. Conclusions and Relevance OSA is common and the prevalence is increasing with the increased prevalence of obesity. Daytime sleepiness is among the most common symptoms, but many patients with OSA are asymptomatic. Patients with OSA who are asymptomatic, or whose symptoms are minimally bothersome and pose no apparent risk to driving safety, can be treated with behavioral measures, such as weight loss and exercise. Interventions such as positive airway pressure are recommended for those with excessive sleepiness and resistant hypertension. Managing asymptomatic OSA to reduce cardiovascular and cerebrovascular events is not currently supported by high-quality evidence.
Article
Background: There is a scarcity of published data on the global prevalence of obstructive sleep apnoea, a disorder associated with major neurocognitive and cardiovascular sequelae. We used publicly available data and contacted key opinion leaders to estimate the global prevalence of obstructive sleep apnoea. Methods: We searched PubMed and Embase to identify published studies reporting the prevalence of obstructive sleep apnoea based on objective testing methods. A conversion algorithm was created for studies that did not use the American Academy of Sleep Medicine (AASM) 2012 scoring criteria to identify obstructive sleep apnoea, allowing determination of an equivalent apnoea-hypopnoea index (AHI) for publications that used different criteria. The presence of symptoms was not specifically analysed because of scarce information about symptoms in the reference studies and population data. Prevalence estimates for obstructive sleep apnoea across studies using different diagnostic criteria were standardised with a newly developed algorithm. Countries without obstructive sleep apnoea prevalence data were matched to a similar country with available prevalence data; population similarity was based on the population body-mass index, race, and geographical proximity. The primary outcome was prevalence of obstructive sleep apnoea based on AASM 2012 diagnostic criteria in individuals aged 30-69 years (as this age group generally had available data in the published studies and related to information from the UN for all countries). Findings: Reliable prevalence data for obstructive sleep apnoea were available for 16 countries, from 17 studies. Using AASM 2012 diagnostic criteria and AHI threshold values of five or more events per h and 15 or more events per h, we estimated that 936 million (95% CI 903-970) adults aged 30-69 years (men and women) have mild to severe obstructive sleep apnoea and 425 million (399-450) adults aged 30-69 years have moderate to severe obstructive sleep apnoea globally. The number of affected individuals was highest in China, followed by the USA, Brazil, and India. Interpretation: To our knowledge, this is the first study to report global prevalence of obstructive sleep apnoea; with almost 1 billion people affected, and with prevalence exceeding 50% in some countries, effective diagnostic and treatment strategies are needed to minimise the negative health impacts and to maximise cost-effectiveness. Funding: ResMed.
Article
Obstructive sleep apnea is common and is associated with daytime sleepiness and increased risks of motor vehicle accidents and cardiovascular disease. CPAP is considered first-line therapy for symptomatic or moderate-to-severe obstructive sleep apnea; mandibular-advancement devices and various surgical options are other approaches.