Abstract
Background:
Obstructive sleep apnea is associated with COVID-19 infection. Less clear is whether obstructive sleep apnea is a risk factor for the development of Post-Acute Sequelae of SARS-CoV-2 infection (PASC).
Study Design:
Cross-sectional survey of a general population of 24,803 U.S. adults to determine the association of obstructive sleep apnea with PASC.
Results:
COVID-19 infection occurred in 10,324 (41.6%) participants. Prevalence of persistent (> 3 months post infection) putative PASC-related physical and mental health symptoms ranged from 6.5% (peripheral edema) to 19.6% (nervous/anxious). In logistic regression models, obstructive sleep apnea was associated with all putative PASC-related symptoms with the highest adjusted odds ratios (aOR) being fever (2.053) and nervous/anxious (1.939). In 4 logistic regression models of overall PASC derived from elastic net regression, obstructive sleep apnea was associated with PASC (range of aORs: 1.934–2.071); this association was mitigated in those with treated obstructive sleep apnea. In the best fitting overall model requiring ≥3 symptoms, PASC prevalence was 21.9%.
Conclusion:
In a general population sample, obstructive sleep apnea is associated with the development of PASC-related symptoms and a global definition of PASC. Treated obstructive sleep apnea mitigates the latter risk. The presence of 3 or more PASC symptoms may be useful in identifying cases and for future research.
Keywords: PASC, Post-Acute Sequelae of SARS-CoV-2 infection, Long COVID, Obstructive Sleep Apnea, COVID-19
Introduction
One devastating consequence of the COVID-19 pandemic was the emergence of persistent and/or relapsing physical, cognitive and mental health symptoms commonly known as “long COVID” or more formally as Post-Acute Sequelae of SARS-CoV-2 infection (PASC).1–4 Prevalence estimates of PASC range from 7.5 to 41% in non-hospitalized adults depending on the criteria used to identify cases.5 The etiology of PASC has not been established although risk factors have been identified including greater severity of initial COVID-19 infection, multiple infections, female sex and preexisting health conditions.4,6
Obstructive sleep apnea is a common sleep disorder characterized by repeated episodes of partial or complete obstruction of the upper airway during sleep. A number of studies have confirmed a strong association between obstructive sleep apnea and COVID-19 infection.7–12 Multiple studies also have reported a high prevalence of symptoms observed with obstructive sleep apnea among individuals with PASC, such as fatigue, insomnia and cognitive difficulties.1,3,13 Recently, a retrospective analysis of data from three large health networks found an elevated risk of PASC in those with preexisting obstructive sleep apnea.14 However, the association of obstructive sleep apnea with specific symptoms associated with PASC was not explored. In this study, we aimed to determine in a large general population cohort whether preexisting obstructive sleep apnea is associated with the development of individual symptoms of PASC as well as with an overall definition of PASC based on frequency of symptoms.
Methods
Study Design and Participants
From March 10, 2022 to October 15, 2022, the COVID-19 Outbreak Public Evaluation (COPE) Initiative (http://www.thecopeinitiative.org) administered five successive cross-sectional surveys to approximately 5000 participants each focused on accumulating data on the prevalence and sequelae of COVID-19 infection. Recruitment approximated population estimates for age, sex, race, and ethnicity based on the 2020 U.S. census and was conducted online by Qualtrics, LLC (Provo, Utah, and Seattle, Washington, U.S.). Informed consent was obtained electronically. The study was approved by the Monash University Human Research Ethics Committee (Study #24036).
Survey Items (eMethods in Supplement)
Participants self-reported age, race, ethnicity, sex, height and weight, education level, employment status and household income. They also provided information on several current and past medical conditions by answering the question: “Have you ever been diagnosed with any of the following conditions?” obstructive sleep apnea, high blood pressure, cardiovascular disease, gastrointestinal disorder, cancer, chronic kidney disease, liver disease, sickle cell disease, chronic obstructive pulmonary disease, and asthma. Response options allowed for affirming the condition and whether participants were treated currently or in the past. COVID-19 vaccination status was ascertained by asking “How many COVID-19 vaccine doses have you received?
Symptoms of obstructive sleep apnea were obtained from responses to the embedded Pittsburgh Sleep Quality Index which included items related to roommate or bedpartner reported snoring and self-reported sleepiness.15 Participants were considered to have symptoms of obstructive sleep apnea if they had either of the following combinations of symptoms: 1) snoring “Three or more times a week” and witnessed apnea or sleepiness “Once or twice a week”; 2) witnessed apnea and sleepiness “Once or twice a week”.
Each survey contained identical items related to COVID-19 infection status and the number of COVID-19 vaccinations participants had obtained. Ascertainment of past COVID-19 infection was obtained using responses from following questions related to COVID-19 testing or the presence of loss of taste or smell:
“Have you ever tested positive?”
“Despite never testing positive, are you confident that you have had COVID-19?”
“Despite never testing positive, have you received a clinical diagnosis of COVID-19?”
“Have you experienced a problem with decreased sense of smell or taste at any point since January 2020?”
Participants who endorsed having had any of aforementioned items #1–4 were asked to provide the date of their positive test or onset of infection. Additionally, they were asked if they experienced any of the general health symptoms listed in Table 1 more than 2 weeks after their infection. For each symptom, participants who endorsed having experienced the symptom more than 2 weeks after their COVID-19 infection or indicated that they were currently having the symptom were asked how long their symptoms persisted after their infection.
Table 1:
Prevalence of Candidate Symptoms Associated with PASC Stratified by COVID-19 Infection Status
| COVID-19 | COVID-19 | COVID-19 Symptoms > 3 months | ||||
|---|---|---|---|---|---|---|
| Negative N=14479 | Positive N=10324 | |||||
| N | % | N | % | N | % | |
| GENERAL HEALTH SYMPTOMS * | ||||||
| Fever | 77 | 0.5 | 5339 | 51.7 | 1110 | 10.8 |
| Fatigue | 451 | 3.1 | 5571 | 54.0 | 1569 | 15.2 |
| Loss of Smell | 28 | 0.2 | 4623 | 44.8 | 1291 | 12.5 |
| Loss of Taste | 21 | 0.1 | 4502 | 43.6 | 1177 | 11.4 |
| Nasal Congestion | 386 | 2.7 | 4693 | 45.5 | 1006 | 9.7 |
| Sore Throat | 151 | 1.0 | 4472 | 43.3 | 866 | 8.4 |
| Tinnitus | 222 | 1.5 | 3619 | 35.1 | 936 | 9.1 |
| Dyspnea | 116 | 0.8 | 3989 | 38.6 | 1089 | 10.5 |
| Cough/Sputum Production | 183 | 1.3 | 4233 | 41.0 | 957 | 9.3 |
| Nausea | 133 | 0.9 | 3658 | 35.4 | 813 | 7.9 |
| Uneasieness/Discomfort | 89 | 0.6 | 3756 | 36.4 | 980 | 9.5 |
| Diarrhea/Constipation | 182 | 1.3 | 3467 | 33.6 | 782 | 7.6 |
| Chest Pain | 63 | 0.4 | 3296 | 31.9 | 796 | 7.7 |
| Palpitations | 47 | 0.3 | 3074 | 29.8 | 776 | 7.5 |
| Peripheral Edema | 56 | 0.4 | 2855 | 27.7 | 675 | 6.5 |
| Headache | 410 | 2.8 | 4084 | 39.6 | 993 | 9.6 |
| Sleepiness | 311 | 2.1 | 3632 | 35.2 | 675 | 6.5 |
| Sleep Problems | 315 | 2.2 | 3436 | 33.3 | 1034 | 10.0 |
| Limited Physical Activity | 189 | 1.3 | 3707 | 35.9 | 1073 | 10.4 |
| Limited Social Activity | 182 | 1.3 | 3669 | 35.5 | 969 | 9.4 |
| Other Aches or Pains | 258 | 1.8 | 3418 | 33.1 | 973 | 9.4 |
| COGNITIVE SYMPTOMS * | ||||||
| Forgetful | 360 | 2.5 | 4205 | 40.7 | 1185 | 11.5 |
| Difficulty Thinking | 199 | 1.4 | 3989 | 38.6 | 1224 | 11.9 |
| Difficulty Focusing | 274 | 1.9 | 3911 | 37.9 | 1165 | 11.3 |
| Cloudy | 155 | 1.1 | 3749 | 36.3 | 1075 | 10.4 |
| Difficulty Finding Words | 245 | 1.7 | 3526 | 34.2 | 1028 | 10.0 |
| Mental Fatigue | 322 | 2.2 | 3783 | 36.6 | 1153 | 11.2 |
| Slow | 139 | 1.0 | 3481 | 33.7 | 1012 | 9.8 |
| Mind Went Blank | 269 | 1.9 | 3388 | 32.8 | 1078 | 10.4 |
| MENTAL HEALTH SYMPTOMS * | ||||||
| Feeling Nervous/Anxious | 735 | 5.1 | 3536 | 34.3 | 2021 | 19.6 |
| Feeling Agitated | 477 | 3.3 | 2431 | 23.5 | 1904 | 18.4 |
| Being Harmed by People | 88 | 0.6 | 2287 | 22.2 | 1265 | 12.3 |
| Inability to Control Worrying | 334 | 2.3 | 2148 | 20.8 | 1716 | 16.6 |
| Little Pleasure | 403 | 2.8 | 2472 | 23.9 | 1750 | 17.0 |
| Depressed | 601 | 4.2 | 2459 | 23.8 | 1915 | 18.5 |
| Irritability | 401 | 2.8 | 2230 | 21.6 | 1701 | 16.5 |
| Avoiding People/Places | 185 | 1.3 | 2021 | 19.6 | 1605 | 15.5 |
All symptoms higher in COVID-19 Positive and COVID-19 Symptoms >3 months Groups
Similarly, participants who endorsed having had a positive COVID-19 test or infection were asked if they experienced any of the cognitive and mental health symptoms listed in Table 1 more than 2 weeks after their infection. The duration of each symptom with a positive response was also solicited utilizing response options identical to those used for general health symptoms.
In parallel to participants presumed to have had COVID-19, those who never had a positive test for COVID-19, who affirmed never having had a COVID-19 infection, and who reported no had a loss of taste or smell since January 2020 were asked whether they experienced any of the same general health, cognitive or mental health symptoms in the two weeks preceding the survey. However, they were not queried regarding duration of any positive symptoms.
Statistical Analyses (eMethods in Supplement)
As in our previous analyses, we defined a positive history of COVID-19 infection as an affirmative response to having tested positive for COVID-19, a clinical diagnosis of COVID-19, or loss of taste or smell.12,16 Participants were considered to have obstructive sleep apnea if they endorsed currently having the condition whether treated or not, or if they had two or more symptoms of obstructive sleep apnea.12 Vaccination status was dichotomized as Boosted (>2 vaccinations) or Not Boosted (≤2 vaccinations).12 Comorbid medical conditions were defined as currently having the condition whether treated or untreated and were evaluated by summing the number of conditions reported by the participant (maximum value=9).12 Body mass index (BMI) was calculated using self-reported height and weight. Socioeconomic covariates were dichotomized as follows: employment status (retired vs. not retired), educational attainment (high school or less vs. some college) and annual household income in U.S. Dollars (<$50,000 vs ≥$50,000). Participants were considered to have a general health, cognitive or mental health symptom potentially associated with PASC if they endorsed having the symptom for at least 3 months after their COVID-19 infection.
Summary data for continuous or ordinal variables are reported as their respective means and standard deviations (SD) and for categorical variables as their percentages. Comparisons of co-morbid medical, demographic, and social characteristic variables stratified by COVID-19 infection status were performed using Student’s unpaired t-test for continuous or ordinal variables and χ2 for categorical variables. For individual symptoms potentially associated with PASC, a z test for proportions was used to assess differences among COVID-19 infection groups.
Multivariable modelling using logistic regression was utilized to determine whether obstructive sleep apnea was associated with each individual symptom potentially associated with PASC among COVID-19 positive participants. For each symptom, a baseline model was constructed using only obstructive sleep apnea. We then developed increasingly complex models by sequentially including demographic factors, comorbidities, boosted vaccination status, and socioeconomic factors.
To assess whether obstructive sleep apnea was associated with PASC overall rather than individual symptoms, we developed several different models of PASC based on symptom frequency. Initially, using positive COVID-19 status as a binary outcome, we performed an elastic net regression using 10-fold cross-validation to select the most relevant symptoms that would contribute to an overall model of PASC. Next, a PASC score was calculated using a multiple linear regression using the symptom variables selected (N=13) weighted by the elastic net coefficients. For two models, overall PASC (symptoms present > 3 months) was defined as a score exceeding the 95th and 99th percentiles respectively of the calculated scores of participants who had no evidence for COVID-19 infection. For two additional models, the symptom variables were summed; overall PASC was defined as a score of ≥2 and ≥3 which represent the 97.5th and 99th percentiles respectively of scores of participants who had no evidence of COVID-19 infection. Finally, a multivariate logistic regression was performed in the group of participants with evidence of COVID-19 infection for each of the 4 PASC models to determine the association between obstructive sleep apnea and overall PASC. Sensitivity analyses were performed using stricter and broader definitions of COVID-19 as well as an obstructive sleep apnea definition that omitted participants with obstructive sleep apnea symptoms but did not self-report a diagnosis of obstructive sleep apnea.
Analyses were conducted using IBM SPSS version 28 (Armonk, NY). A p<0.05 was considered statistically significant.
Results
Table 2 shows the associations between COVID-19 infection status and various co-morbid medical conditions, demographic, and social characteristics of the 24,803 participants in the cohort. Those who had experienced COVID-19 infection (N=10,324, 41.6%) were younger, less likely to be retired and had greater income; Hispanics had a higher prevalence than other racial or ethnic groups. They also had a greater number of comorbidities and had a higher prevalence of obstructive sleep apnea.
Table 2:
Associations Between COVID-19 Infection Status and Obstructive Sleep Apnea, Co-morbid Medical, Demographic and Social Characteristics*
| COVID-19 Negative (N=14479) | COVID-19 Positive (N=10324) | COVID-19 Overall (N=24803) | ||||
|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | |
| Age (y) * | 50.6 | 18.0 | 39.3 | 15.3 | 46.6 | 17.8 |
| Body Mass Index (kg/m2) | 27.5 | 5.9 | 27.6 | 6.3 | 28.4 | 8.9 |
| No. Comorbidities * | 1.1 | 1.5 | 2.1 | 2.9 | 1.1 | 1.8 |
| N | % | N | % | N | % | |
| Sex | ||||||
| Male | 7027 | 48.8 | 5007 | 49.1 | 12034 | 48.9 |
| Female | 7385 | 51.2 | 5198 | 50.9 | 12583 | 51.1 |
| Race/Ethnicity * | ||||||
| White | 9206 | 63.6 | 6032 | 58.4 | 15238 | 61.4 |
| Black | 1581 | 10.9 | 1056 | 10.2 | 2637 | 10.6 |
| Asian | 1024 | 7.1 | 513 | 5.0 | 1537 | 6.2 |
| Hispanic | 1926 | 13.3 | 2264 | 21.9 | 4190 | 16.9 |
| Other | 742 | 5.1 | 459 | 4.4 | 1201 | 4.8 |
| Employment * | ||||||
| Retired | 4471 | 30.9 | 1382 | 13.4 | 5853 | 23.6 |
| Not Retired | 10008 | 69.1 | 8942 | 86.6 | 18950 | 76.4 |
| Education | ||||||
| High School or Less | 3864 | 26.7 | 2670 | 25.9 | 6534 | 26.3 |
| Some College | 10615 | 73.3 | 7654 | 74.1 | 18269 | 73.7 |
| Income (Y early) * | ||||||
| < $50,000 | 6621 | 48.1 | 4136 | 41.3 | 10757 | 45.2 |
| ≥ $50,000 | 7156 | 51.9 | 5873 | 58.7 | 13029 | 54.8 |
| Vaccination Boosted | ||||||
| No (≤2 Vaccinations) | 7726 | 55.5 | 7207 | 71.9 | 14933 | 62.3 |
| Yes (>2 Vaccinations) | 6198 | 44.5 | 2823 | 28.1 | 9021 | 37.7 |
| Obstructive Sleep Apnea* | ||||||
| Yes | 1756 | 12.1 | 2828 | 27.4 | 4584 | 18.5 |
| No | 12723 | 87.9 | 7496 | 72.6 | 20219 | 81.5 |
Minor discrepancies in case counts and totals reflect small amounts of missing data and rounding Significant differences in means or proportions: *p≤0.001
The prevalence rates of symptoms putatively associated with PASC are presented in Table 2. Participants without evidence of previous COVID-19 infection had very low prevalence rates of all symptoms in comparison to participants with previous COVID-19 infection (all p values <0.0001). Prevalence rates of these participants also were lower than those who had COVID-19 with symptoms persisting ≥3 months (all p values <0.0001). Among COVID-19 participants with persistent symptoms, fatigue (15.2%) and loss of smell (12.5%) and taste (11.4%) had the highest prevalence rates among general health symptoms. More common was the occurrence of mental health symptoms with the prevalence of nervousness or anxiety approaching 1 in 5 COVID-19 infected participants.
Logistic regression models of the association between obstructive sleep apnea and individual symptoms putatively associated with PASC are displayed in Table 3. Obstructive sleep apnea was associated with a greater likelihood of all symptoms in all models. The highest aORs for general health, cognitive and mental health symptoms were fever (2.053), mind went blank (1.669) and feeling nervous/anxious (1.939) respectively.
Table 3:
Logistic Regression Models of the Association Between Obstructive Sleep Apnea and Individual Candidate Symptoms of PASC
| Unadjusted | Model 1 | Model 2 | Model 3 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | aOR | 95% CI | aOR | 95% CI | aOR | 95% CI | |||||
| Lower | Upper | Lower | Upper | Lower | Upper | Lower | Upper | |||||
| GENERAL HEALTH SYMPTOMS * | ||||||||||||
| Fever | 4.429 | 3.895 | 5.037 | 4.083 | 3.579 | 4.659 | 2.087 | 1.714 | 2.541 | 2.053 | 1.682 | 2.505 |
| Fatigue | 2.509 | 2.245 | 2.803 | 2.544 | 2.271 | 2.850 | 1.504 | 1.269 | 1.783 | 1.494 | 1.259 | 1.774 |
| Loss of Smell | 3.203 | 2.843 | 3.609 | 3.052 | 2.701 | 3.449 | 1.778 | 1.484 | 2.131 | 1.780 | 1.483 | 2.138 |
| Loss of Taste | 2.928 | 2.634 | 3.374 | 2.932 | 2.582 | 3.329 | 1.921 | 1.594 | 2.315 | 1.928 | 1.598 | 2.328 |
| Nasal Congestion | 3.512 | 3.076 | 4.010 | 3.303 | 2.892 | 3.794 | 1.640 | 1.337 | 2.012 | 1.607 | 1.308 | 1.975 |
| Sore Throat | 4.206 | 3.647 | 4.852 | 3.831 | 3.309 | 4.434 | 1.674 | 1.338 | 2.094 | 1.642 | 1.311 | 2.057 |
| Tinnitus | 3.394 | 2.961 | 3.891 | 3.177 | 2.862 | 3.654 | 1.552 | 1.258 | 1.916 | 1.559 | 1.260 | 1.929 |
| Dyspnea† | 2.862 | 2.519 | 3.252 | 2.802 | 2.458 | 3.195 | 1.371 | 1.122 | 1.676 | 1.363 | 1.114 | 1.668 |
| Cough/Sputum Production† | 3.308 | 2.890 | 3.787 | 3.130 | 2.724 | 3.597 | 1.382 | 1.120 | 1.706 | 1.383 | 1.119 | 1.709 |
| Nausea | 3.698 | 3.196 | 4.278 | 3.462 | 2.979 | 4.024 | 1.906 | 1.520 | 2.389 | 1.913 | 1.523 | 2.403 |
| Uneasiness/Discomfort | 2.808 | 2.456 | 3.209 | 2.711 | 2.363 | 3.110 | 1.440 | 1.171 | 1.772 | 1.442 | 1.170 | 1.776 |
| Diarrhea/Constipation | 3.921 | 3.379 | 4.551 | 3.703 | 3.178 | 4.314 | 1.778 | 1.415 | 2.234 | 1.775 | 1.410 | 2.235 |
| Chest Pain | 3.474 | 2.999 | 4.023 | 3.260 | 2.804 | 3.791 | 1.582 | 1.265 | 1.978 | 1.586 | 1.266 | 1.986 |
| Palpitations | 3.926 | 3.382 | 4.559 | 3.727 | 3.198 | 4.344 | 1.664 | 1.320 | 2.096 | 1.651 | 1.307 | 2.084 |
| Peripheral Edema | 4.184 | 3.566 | 4.909 | 3.906 | 3.315 | 4.603 | 1.623 | 1.265 | 2.083 | 1.621 | 1.260 | 2.085 |
| Headache | 2.503 | 2.191 | 2.859 | 2.463 | 2.148 | 2.824 | 1.514 | 1.234 | 1.858 | 1.517 | 1.235 | 1.865 |
| Sleepiness | 2.583 | 2.206 | 3.025 | 2.479 | 2.108 | 2.916 | 1.490 | 1.169 | 1.898 | 1.520 | 1.191 | 1.940 |
| Sleep Problems | 2.461 | 2.159 | 2.805 | 2.446 | 2.138 | 2.797 | 1.345 | 1.100 | 1.646 | 1.367 | 1.116 | 1.675 |
| Limited Physical Activity | 2.464 | 2.166 | 2.803 | 2.481 | 2.173 | 2.831 | 1.421 | 1.164 | 1.735 | 1.449 | 1.185 | 1.772 |
| Limited Social Activity‡ | 2.415 | 2.111 | 2.764 | 2.397 | 2.087 | 2.752 | 1.273 | 1.033 | 1.571 | 1.289 | 1.043 | 1.591 |
| Other Aches or Pains | 2.523 | 2.206 | 2.886 | 2.529 | 2.020 | 2.904 | 1.586 | 1.291 | 1.949 | 1.605 | 1.304 | 1.974 |
| COGNITIVE SYMPTOMS * | ||||||||||||
| Forgetful | 2.448 | 2.163 | 2.770 | 2.594 | 2.284 | 2.946 | 1.596 | 1.321 | 1.928 | 1.625 | 1.343 | 1.965 |
| Difficulty Thinking | 2.641 | 2.338 | 2.983 | 2.728 | 2.407 | 3.092 | 1.527 | 1.266 | 1.842 | 1.534 | 1.269 | 1.853 |
| Difficulty Focusing | 2.206 | 1.947 | 2.500 | 2.324 | 2.043 | 2.644 | 1.380 | 1.137 | 1.675 | 1.375 | 1.131 | 1.673 |
| Cloudy | 2.465 | 2.167 | 2.804 | 2.544 | 2.230 | 2.902 | 1.560 | 1.283 | 1.898 | 1.588 | 1.303 | 1.936 |
| Difficulty Finding Words | 2.126 | 1.863 | 2.426 | 2.239 | 1.955 | 2.565 | 1.425 | 1.165 | 1.742 | 1.439 | 1.175 | 1.763 |
| Mental Fatigue | 2.081 | 1.835 | 2.361 | 2.253 | 1.978 | 2.565 | 1.401 | 1.154 | 1.700 | 1.426 | 1.173 | 1.733 |
| Slow | 2.557 | 2.241 | 2.918 | 2.618 | 2.287 | 2.998 | 1.553 | 1.267 | 1.903 | 1.574 | 1.282 | 1.932 |
| Mind Went Blank | 2.431 | 2.137 | 2.765 | 2.525 | 2.213 | 2.883 | 1.666 | 1.370 | 2.026 | 1.669 | 1.370 | 2.033 |
| MENTAL HEALTH SYMPTOMS * | ||||||||||||
| Feeling Nervous/Anxious | 2.952 | 2.661 | 3.274 | 2.960 | 2.659 | 3.296 | 1.962 | 1.678 | 2.294 | 1.939 | 1.655 | 2.271 |
| Feeling Agitated | 3.247 | 2.920 | 3.611 | 3.220 | 2.886 | 3.593 | 1.838 | 1.563 | 2.160 | 1.800 | 1.528 | 2.120 |
| Being Harmed by People | 4.192 | 3.701 | 4.748 | 3.839 | 3.377 | 4.363 | 1.899 | 1.570 | 2.298 | 1.873 | 1.545 | 2.271 |
| Inability to Control Worrying | 2.858 | 2.560 | 3.189 | 2.829 | 2.527 | 3.168 | 1.680 | 1.421 | 1.986 | 1.668 | 1.409 | 1.975 |
| Little Pleasure | 2.740 | 2.457 | 3.056 | 2.756 | 2.463 | 3.083 | 1.516 | 1.282 | 1.793 | 1.520 | 1.284 | 1.800 |
| Depressed | 2.427 | 2.182 | 2.700 | 2.473 | 2.215 | 2.761 | 1.440 | 1.223 | 1.695 | 1.449 | 1.229 | 1.708 |
| Irritability | 2.453 | 2.196 | 2.740 | 2.484 | 2.216 | 2.784 | 1.429 | 1.207 | 1.692 | 1.440 | 1.215 | 1.708 |
| Avoiding People/Places | 2.715 | 2.426 | 3.038 | 2.712 | 2.415 | 3.046 | 1.557 | 1.309 | 1.852 | 1.560 | 1.309 | 1.858 |
Model 1: adjusted for age, sex and race
Model 2: Model 1 + bmi, comorbidities, boosted COVID-19 vaccination status, and boosted COVID-19 vaccination status/obstructive sleep apnea interaction
Model 3: Model 2 + income, employment and education
p <0.001 for association of each symptom and obstructive sleep apnea except for dyspnea, cough, sleep problems and limited social activity
p <0.01 for association of dyspnea, cough and sleep problems and obstructive sleep apnea for Models 2 and 3
p <0.05 for association of limited social activity and obstructive sleep apnea for Models 2 and 3
In Table 4 shows the standardized elastic net regression coefficients for symptoms possibly associated with PASC. Of the initial 37 symptoms entered into the elastic net regression, only 13 had non-zero coefficients. Fever, fatigue, and loss of smell or taste had the highest coefficients. Except for forgetfulness, cognitive and mental health symptoms had relatively small contributions to the overall regression.
Table 4:
Elastic Net Regression Standardized Coefficients for Symptoms Associated with PASC
| Standardized Coefficient | |
|---|---|
| Fever | 0.048 |
| Fatigue | 0.031 |
| Loss of Smell | 0.026 |
| Loss of Taste | 0.018 |
| Sore Throat | 0.001 |
| Sleepiness | 0.001 |
| Forgetful | 0.013 |
| Difficulty Thinking | 0.011 |
| Difficulty Focusing | 0.006 |
| Cloudy | 0.004 |
| Slow | 0.003 |
| Feeling Nervous/Anxious | 0.003 |
| Avoiding People/Places | 0.003 |
| Intercept | 0.416 |
| L1 Ratio | 0.1 |
| Alpha | 0.1 |
| Dependent Variable | Previous COVID-19 Infection |
Table 5 presents the PASC prevalence rates and logistic regression models of the association between obstructive sleep apnea and four models of PASC as constructed from the results of the elastic net regression. Prevalence rates ranged from 21.8% (at least 2 symptoms present) to 38.5% (95th percentile of PASC scores). For all four models, fully adjusted aORs demonstrated that obstructive sleep apnea was associated with a higher likelihood of having PASC. The aOR for the best fitting model (≥3 symptoms present) was 2.059 (95% CI: 1.769–2.395). The remaining models were similar. Boosted vaccination status was protective against development of PASC (aOR for ≥3 symptoms present: 0.776, 95% CI: 0.656–0.918).
Table 5:
Logistic Regression Models of the Association of Obstructive Sleep Apnea with Overall PASC Models
| PASC Prevalence | Unadjusted | Model 1 | Model 2 | Model 3 | Model 3 Goodness of Fit and Variance | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | aOR | 95% CI | aOR | 95% CI | aOR | 95% CI | −2 Log likelihood | Nagelk erke R2 | ||||||
| PASC Model* | N/% | L | U | L | U | L | U | L | U | ||||||
| PASC: 97.5th Percentile | 2260/21.8 | 3.451 | 3.128 | 3.807 | 3.388 | 3.063 | 3.747 | 1.940 | 1.671 | 2.253 | 1.934 | 1.663 | 2.249 | 8078.772 | 0.140 |
| PASC: 95th Percentile | 3976/38.5 | 3.770 | 3.444 | 4.127 | 3.740 | 3.406 | 4.106 | 2.059 | 1.795 | 2.361 | 2.024 | 1.762 | 2.325 | 10067.928 | 0.185 |
| PASC: At Least 2 Positive | 2985/28.9 | 3.771 | 3.439 | 4.136 | 3.757 | 3.415 | 4.132 | 2.204 | 1.938 | 2.506 | 2.071 | 1.797 | 2.386 | 9074.241 | 0.174 |
| PASC: At Least 3 Positive | 2257/21.9 | 3.770 | 3.417 | 4.160 | 3.757 | 3.395 | 4.157 | 2.040 | 1.756 | 2.370 | 2.059 | 1.769 | 2.395 | 7940.332 | 0.158 |
Model 1: adjusted for age, sex and race
Model 2: Model 1 + bmi, comorbidities, boosted COVID-19 vaccination status, and boosted COVID19 vaccination status/obstructive sleep apnea interaction
Model 3: Model 2 + income, employment and education
See text for definition of PASC Models
In sensitivity analyses (eTable S1 in supplement) both a definition of COVID-19 that was stricter (positive test, loss of taste or smell) and more liberal (positive test, loss of taste or smell, clinical diagnosis but no positive test) demonstrated a strong association of obstructive sleep apnea with all four models of PASC. Current or past treatment of obstructive sleep apnea also showed a strong relationship with PASC. However, current treatment of obstructive sleep apnea alone was not associated with PASC in all four models.
Discussion
A large number of symptoms are reported by individuals who incompletely recover many weeks after a COVID-19 infection and who are thus diagnosed as having PASC.1,3,17 For many of these commonly reported physical and mental health symptoms, we now document that they are highly prevalent more than 3 months afterwards among individuals who previously experienced a COVID-19 infection in comparison to those who have never been infected. Consistent with recent reviews, we found that fatigue and dysgeusia or dysosmia were among the most frequently reported symptoms.1,3 In contrast, persistent fever was a common occurrence among our participants whereas it was less prominent in other studies.3 Our findings also highlight the variety of persistent mental health symptoms after a COVID-19 infection. The high rates of depression, anxiety and generalized dysphoria are likely factors that contribute to poor quality of life experienced by individuals with PASC.18
We observed that obstructive sleep apnea was associated with all of the symptoms linked with PASC in our study after controlling for demographic factors, medical comorbidities, and variation in socioeconomic considerations. We and others have documented that obstructive sleep apnea appears to be a risk factor for COVID-19 infection.7,8,10–12 In a recent study using an amalgam of three different definitions of PASC identified from electronic medical records, an association with obstructive sleep apnea was found with an adjusted odds ratio of 1.75.14 Our findings extend this observation by documenting the association of obstructive sleep apnea with individual symptoms of PASC.
Our elastic net regression results identified 13 symptoms that were strongly related to a diagnosis of COVID-19. In a recent study from the RECOVER cohort in which a lasso regression was used for selection of the most important PASC related symptoms, abnormal smell or taste was the strongest predictor.19 Our results are consistent with this observation, but differ in finding that fatigue and fever also had a high predictive value. The differences may relate to the composition of the cohorts; the COPE cohort was recruited from the general population regardless of COVID-19 infection history, whereas RECOVER primarily targeted individuals who had been infected with COVID-19.
Although there is general consensus that PASC consists of a constellation of symptoms, there is no widely accepted definition of the syndrome or diagnostic biomarker.13 Recently, a definition of PASC was proposed using data from the RECOVER cohort in which between 1 and 8 points were assigned to each of 12 symptoms derived after applying a lasso regression to 37 candidate symptoms.19 The prevalence of PASC defined as a score of ≥12 was 23%. Using a different methodology, we found a similar prevalence rate in our two models that employed a 97.5th percentile population cutpoint (21.8%) or at least 3 positive symptoms (21.9%) (Table 5). The latter definition may be easier to implement than the more complex algorithm derived from the RECOVER cohort.19
Obstructive sleep apnea was found to be associated with PASC in all 4 of the models that we developed. Thus, our results replicate the observations from the RECOVER cohort in which they also noted a strong association between PASC and obstructive sleep apnea using an approach based on medical record documentation.14 We extend this finding by demonstrating no association between obstructive sleep apnea and PASC in participants who had been treated for their obstructive sleep apnea. This is consistent with our previous observation that risk of COVID-19 infection was reduced in those with treated obstructive sleep apnea.12 Finally, preexisting health conditions such as obesity and diabetes are linked to development of PASC, but do not explain our observations inasmuch as adjustments for them were made in our models.
We observed that boosted vaccination status was protective against the development of PASC in our models. This finding is consistent with the conclusion from a recent systematic review of the protective effects of COVID-19 vaccination.20 It supports public health messaging concerning the importance of COVID-19 vaccination.
The mechanism underlying the association between obstructive sleep apnea and PASC remains to be determined. However, there are several possibilities. Substantial evidence supports that obstructive sleep apnea is an pro-inflammatory condition.21 Intermittent hypoxemia resulting from obstructive sleep apnea promotes the release of inflammatory cytokines.22 Introduction of the SARS-CoV-2 virus into a pre-existing inflammatory milieu could increase the likelihood of PASC.4 Intermittent hypoxemia also may promote a hypercoagulable state in obstructive sleep apnea.23,24 Microthrombi have been observed in PASC and may contribute to neurologic and cardiovascular symptoms.25 Intermittent hypoxemia also produces oxidative stress with release of reactive oxygen species.26 A hypercoagulable state, inflammation and oxidative stress are all factors that can lead to disruption of the blood brain barrier resulting in the cognitive and neurologic symptoms of PASC.13,24 Abnormalities in cellular immunity have been documented in PASC;13 obstructive sleep apnea also has been associated with cellular immune dysfunction and may contribute to the abnormal immune function observed in PASC.27
Our results are subject to some limitations. Identification of COVID-19 and subsequent symptoms as well as obstructive sleep apnea were self-reported which may have resulted in misclassification of the exposure and/or outcome. However, in our sensitivity analyses, changes in the definition of COVID-19 resulted in similar findings. Without an established PASC definition, those utilized in our modeling of PASC were to some extent arbitrary. However, use of percentiles ranging from the 95th to 99th is a common practice to define normality in anthropometry and health conditions.28 In contrast to these limitations, our study has two major strengths, the size of cohort (N=24,803) and that it was generally representative of the U.S. adult population.
In conclusion, there is a strong association between obstructive sleep apnea, and physical and mental health symptoms experienced by individuals more than 3 months after a COVID-19 infection. In several overall models, obstructive sleep apnea was strongly associated with PASC; this relationship was mitigated with obstructive sleep apnea treatment indicating that untreated obstructive sleep apnea should be considered an important risk factor for the development of PASC. Furthermore, the presence of 3 or more PASC related symptoms is a practical definition of PASC, but additional validation is required.
Supplementary Material
Clinical Significance.
Obstructive sleep apnea is associated with the development of Post-Acute Sequelae of SARS-CoV-2 Infection (PASC)-related symptoms as well as with a global definition of PASC.
The association between obstructive sleep apnea and PASC is mitigated among those with treated obstructive sleep apnea.
The presence of 3 or more PASC-related symptoms provides a useful definition of PASC.
Acknowledgments:
Concept and Design: SFQ
Data collection: MDW, MÉC, MEH
Data analysis and interpretation: SFQ, MDW, MÉC, LAB, MEH
Drafting of the manuscript: SFQ
Critical feedback and revision of manuscript: SFQ, MDW, MÉC, LKB, LAB, MEH, MLJ, RL, CFM, AR, RR, PV, SMWR, CAC
Funding Information:
This work was supported by the Centers for Disease Control and Prevention. Dr. M. Czeisler was supported by an Australian-American Fulbright Fellowship, with funding from The Kinghorn Foundation. The salary of Drs. Barger, Czeisler, Robbins and Weaver were supported, in part, by NIOSH R01 OH011773 and NHLBI R56 HL151637. Dr. Robbins also was supported in part by NHLBI K01 HL150339.
Conflicts of Interest:
MDW reports institutional support from the US Centers for Disease Control and Prevention, National Institutes of Occupational Safety and Health, Delta Airlines, and the Puget Sound Pilots; as well as consulting fees from the Fred Hutchinson Cancer Center and the University of Pittsburgh. LKB reports institutional support from the US Centers for Disease Control and Prevention, National Institutes of Occupational Safety and Health, Delta Airlines, and the Puget Sound Pilots; as well as honorariums from the National Institutes of Occupational Safety and Health, University of Arizona and University of British Columbia. MÉC reported personal fees from Vanda Pharmaceuticals Inc., research grants or gifts to Monash University from WHOOP, Inc., Hopelab, Inc., CDC Foundation, and the Centers for Disease Control and Prevention. SMWR reported receiving grants and personal fees from Cooperative Research Centre for Alertness, Safety, and Productivity, receiving grants and institutional consultancy fees from Teva Pharma Australia and institutional consultancy fees from Vanda Pharmaceuticals, Circadian Therapeutics, BHP Billiton, and Herbert Smith Freehills. SFQ has served as a consultant for Best Doctors, Bryte Foundation, Jazz Pharmaceuticals, Apnimed, and Whispersom. RR reports personal fees from SleepCycle AB; Rituals Cosmetics BV; Sonesta Hotels International, LLC; Ouraring Ltd; AdventHealth; and With Deep, LLC. CAC serves as the incumbent of an endowed professorship provided to Harvard Medical School by Cephalon, Inc. and reports institutional support for a Quality Improvement Initiative from Delta Airlines and Puget Sound Pilots; education support to Harvard Medical School Division of Sleep Medicine and support to Brigham and Women’s Hospital from: Jazz Pharmaceuticals PLC, Inc, Philips Respironics, Inc., Optum, and ResMed, Inc.; research support to Brigham and Women’s Hospital from Axome Therapeutics, Inc., Dayzz Ltd., Peter Brown and Margaret Hamburg, Regeneron Pharmaceuticals, Sanofi SA, Casey Feldman Foundation, Summus, Inc., Takeda Pharmaceutical Co., LTD, Abbaszadeh Foundation, CDC Foundation; educational funding to the Sleep and Health Education Program of the Harvard Medical School Division of Sleep Medicine from ResMed, Inc., Teva Pharmaceuticals Industries, Ltd., and Vanda Pharmaceuticals; personal royalty payments on sales of the Actiwatch-2 and Actiwatch-Spectrum devices from Philips Respironics, Inc; personal consulting fees from Axome, Inc., Bryte Foundation, With Deep, Inc. and Vanda Pharmaceuticals; honoraria from the Associated Professional Sleep Societies, LLC for the Thomas Roth Lecture of Excellence at SLEEP 2022, from the Massachusetts Medical Society for a New England Journal of Medicine Perspective article, from the National Council for Mental Wellbeing, from the National Sleep Foundation for serving as chair of the Sleep Timing and Variability Consensus Panel, for lecture fees from Teva Pharma Australia PTY Ltd. and Emory University, and for serving as an advisory board member for the Institute of Digital Media and Child Development, the Klarman Family Foundation, and the UK Biotechnology and Biological Sciences Research Council. CAC has received personal fees for serving as an expert witness on a number of civil matters, criminal matters, and arbitration cases, including those involving the following commercial and government entities: Amtrak; Bombardier, Inc.; C&J Energy Services; Dallas Police Association; Delta Airlines/Comair; Enterprise Rent-A-Car; FedEx; Greyhound Lines, Inc./Motor Coach Industries/FirstGroup America; PAR Electrical Contractors, Inc.; Puget Sound Pilots; and the San Francisco Sheriff’s Department; Schlumberger Technology Corp.; Union Pacific Railroad; United Parcel Service; Vanda Pharmaceuticals. CAC has received travel support from the Stanley Ho Medical Development Foundation for travel to Macao and Hong Kong; equity interest in Vanda Pharmaceuticals, With Deep, Inc, and Signos, Inc.; and institutional educational gifts to Brigham and Women’s Hospital from Johnson & Johnson, Mary Ann and Stanley Snider via Combined Jewish Philanthropies, Alexandra Drane, DR Capital, Harmony Biosciences, LLC, San Francisco Bar Pilots, Whoop, Inc., Harmony Biosciences LLC, Eisai Co., LTD, Idorsia Pharmaceuticals LTD, Sleep Number Corp., Apnimed, Inc., Avadel Pharmaceuticals, Bryte Foundation, f.lux Software, LLC, Stuart F. and Diana L. Quan Charitable Fund. Dr Czeisler’s interests were reviewed and are managed by the Brigham and Women’s Hospital and Mass General Brigham in accordance with their conflict-of interest policies. No other disclosures were reported.
Footnotes
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References
- 1.Healey Q, Sheikh A, Daines L, Vasileiou E. Symptoms and signs of long COVID: A rapid review and meta-analysis. J Glob Health. 2022;12:05014. doi: 10.7189/jogh.12.05014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Marshall M The lasting misery of coronavirus long-haulers. Nature. 2020;585(7825):339–341. doi: 10.1038/d41586-020-02598-6 [DOI] [PubMed] [Google Scholar]
- 3.Nasserie T, Hittle M, Goodman SN. Assessment of the Frequency and Variety of Persistent Symptoms Among Patients With COVID-19: A Systematic Review. JAMA Netw Open. 2021;4(5):e2111417. doi: 10.1001/jamanetworkopen.2021.11417 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Yong SJ. Long COVID or post-COVID-19 syndrome: putative pathophysiology, risk factors, and treatments. Infect Dis (Lond). 2021;53(10):737–754. doi: 10.1080/23744235.2021.1924397 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Nittas V, Gao M, West EA, et al. Long COVID Through a Public Health Lens: An Umbrella Review. Public Health Rev. 2022;43:1604501. doi: 10.3389/phrs.2022.1604501 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Tsampasian V, Elghazaly H, Chattopadhyay R, et al. Risk Factors Associated With Post−COVID-19 Condition: A Systematic Review and Meta-analysis. JAMA Internal Medicine. 2023;183(6):566–580. doi: 10.1001/jamainternmed.2023.0750 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Cade BE, Dashti HS, Hassan SM, Redline S, Karlson EW. Sleep Apnea and COVID-19 Mortality and Hospitalization. Am J Respir Crit Care Med. 2020;202(10):1462–1464. doi: 10.1164/rccm.202006-2252LE [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Chung F, Waseem R, Pham C, et al. The association between high risk of sleep apnea, comorbidities, and risk of COVID-19: a population-based international harmonized study. Sleep Breath. 2021;25(2):849–860. doi: 10.1007/s11325-021-02373-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Hariyanto TI, Kurniawan A. Obstructive sleep apnea (OSA) and outcomes from coronavirus disease 2019 (COVID-19) pneumonia: a systematic review and meta-analysis. Sleep Med. 2021;82:47–53. doi: 10.1016/j.sleep.2021.03.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Maas MB, Kim M, Malkani RG, Abbott SM, Zee PC. Obstructive Sleep Apnea and Risk of COVID-19 Infection, Hospitalization and Respiratory Failure. Sleep Breath. 2021;25(2):1155–1157. doi: 10.1007/s11325-020-02203-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Mashaqi S, Lee-Iannotti J, Rangan P, et al. Obstructive sleep apnea and COVID-19 clinical outcomes during hospitalization: a cohort study. J Clin Sleep Med. 2021;17(11):2197–2204. doi: 10.5664/jcsm.9424 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Quan SF, Weaver MD, Czeisler MÉ, et al. Associations between obstructive sleep apnea and COVID-19 infection and hospitalization among US adults. J Clin Sleep Med. 2023;19(7):1303–1311. doi: 10.5664/jcsm.10588 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Davis HE, McCorkell L, Vogel JM, Topol EJ. Long COVID: major findings, mechanisms and recommendations. Nat Rev Microbiol. 2023;21(3):133–146. doi: 10.1038/s41579-022-00846-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Mandel HL, Colleen G, Abedian S, et al. Risk of post-acute sequelae of SARS-CoV-2 infection associated with pre-coronavirus disease obstructive sleep apnea diagnoses: an electronic health record-based analysis from the RECOVER initiative. Sleep. 2023;46(9):zsad126. doi: 10.1093/sleep/zsad126 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213. doi: 10.1016/0165-1781(89)90047-4 [DOI] [PubMed] [Google Scholar]
- 16.Quan SF, Weaver MD, Czeisler MÉ, et al. Insomnia, Poor Sleep Quality and Sleep Duration, and Risk for COVID-19 Infection and Hospitalization. Am J Med. 2023;136(8):780–788.e5. doi: 10.1016/j.amjmed.2023.04.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Mizrahi B, Sudry T, Flaks-Manov N, et al. Long covid outcomes at one year after mild SARS-CoV-2 infection: nationwide cohort study. BMJ. 2023;380:e072529. doi: 10.1136/bmj-2022-072529 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Malesevic S, Sievi NA, Baumgartner P, et al. Impaired health-related quality of life in long-COVID syndrome after mild to moderate COVID-19. Sci Rep. 2023;13(1):7717. doi: 10.1038/s41598-023-34678-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Thaweethai T, Jolley SE, Karlson EW, et al. Development of a Definition of Postacute Sequelae of SARS-CoV-2 Infection. JAMA. 2023;329(22):1934–1946. doi: 10.1001/jama.2023.8823 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Watanabe A, Iwagami M, Yasuhara J, Takagi H, Kuno T. Protective effect of COVID-19 vaccination against long COVID syndrome: A systematic review and meta-analysis. Vaccine. 2023;41(11):1783–1790. doi: 10.1016/j.vaccine.2023.02.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Kheirandish-Gozal L, Gozal D. Obstructive Sleep Apnea and Inflammation: Proof of Concept Based on Two Illustrative Cytokines. Int J Mol Sci. 2019;20(3):459. doi: 10.3390/ijms20030459 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Ren H, Hu K. Inflammatory and oxidative stress-associated factors in chronic intermittent hypoxia in Chinese patients, rats, lymphocytes and endotheliocytes. Mol Med Rep. 2017;16(6):8092–8102. doi: 10.3892/mmr.2017.7632 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Bikov A, Meszaros M, Schwarz EI. Coagulation and Fibrinolysis in Obstructive Sleep Apnoea. Int J Mol Sci. 2021;22(6):2834. doi: 10.3390/ijms22062834 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Zolotoff C, Bertoletti L, Gozal D, et al. Obstructive Sleep Apnea, Hypercoagulability, and the Blood-Brain Barrier. J Clin Med. 2021;10(14):3099. doi: 10.3390/jcm10143099 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Turner S, Khan MA, Putrino D, Woodcock A, Kell DB, Pretorius E. Long COVID: pathophysiological factors and abnormalities of coagulation. Trends Endocrinol Metab. 2023;34(6):321–344. doi: 10.1016/j.tem.2023.03.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Stanek A, Brożyna-Tkaczyk K, Myśliński W. Oxidative Stress Markers among Obstructive Sleep Apnea Patients. Oxid Med Cell Longev. 2021;2021:9681595. doi: 10.1155/2021/9681595 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Ludwig K, Huppertz T, Radsak M, Gouveris H. Cellular Immune Dysfunction in Obstructive Sleep Apnea. Front Surg. 2022;9:890377. doi: 10.3389/fsurg.2022.890377 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Wang Y, Chen HJ. Use of Percentiles and Z-Scores in Anthropometry. In: Handbook of Anthropometry: Physical Measures of Human Form in Health and Disease. 1st ed. Springer; 2012:3107. Accessed December 3, 2023. 10.1007/978-1-4419-1788-1 [DOI] [Google Scholar]
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