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Impact of Sleep and Dialysis Mode on Quality of Life in a Mexican Population
Out of Center Sleep Testing in Ostensibly Healthy Middle Aged to Older 
Sleep Related Breathing Disorders and Neurally Mediated Syncope (SRBD 
   and NMS)
Sleep Board Review Question: Restless Legs
Impact of Sleep Duration and Weekend Oversleep on Body Weight 
   and Blood Pressure in Adolescents
Role of Spousal Involvement in Continuous Positive Airway Pressure 
   (CPAP) Adherence in Patients with Obstructive Sleep Apnea (OSA)
The Impact of an Online Prematriculation Sleep Course (Sleep 101) on
   Sleep Knowledge and Behaviors in College Freshmen: A Pilot Study
Obstructive Sleep Apnea and Quality of Life: Comparison of the SAQLI,
   FOSQ, and SF-36 Questionnaires
Gender Differences in Real-Home Sleep of Young and Older Couples
Brief Review: Sleep Health and Safety for Transportation Workers
Lack of Impact of Mild Obstructive Sleep Apnea on Sleepiness, Mood and
   Quality of Life
Alpha Intrusion on Overnight Polysomnogram
Sleep Board Review Question: Insomnia in Obstructive Sleep Apnea
Long-Term Neurophysiologic Impact of Childhood Sleep Disordered 
   Breathing on Neurocognitive Performance
Sleep Board Review Question: Hyperarousal in Insomnia
Sleep Board Review Question: Epilepsy or Parasomnia?
Sleep Board Review Question: Nocturnal Hypoxemia in COPD
Sleep Board Review Questions: Medications and Their 
   Adverse Effects
Sleep Board Review Questions: The Restless Sleeper
Obstructive Sleep Apnea and Cardiovascular Disease:
   Back and Forward in Time Over the Last 25 Years
Sleep Board Review Questions: The Late Riser
Sleep Board Review Questions: CPAP Adherence in OSA
Sleep Board Review Questions: Sleep Disordered Breathing 
   That Improves in REM
The Impact Of Sleep-Disordered Breathing On Body
Mass Index (BMI): The Sleep Heart Health Study (SHHS)
Incidence and Remission of Parasomnias among Adolescent Children in the 
   Tucson Children’s Assessment of Sleep Apnea (TuCASA) Study 
A 45-Year Old Man with Excessive Daytime Somnolence, 
  and Witnessed Apnea at Altitude


The Southwest Journal of Pulmonary and Critical Care publishes articles related to those who treat sleep disorders in sleep medicine from a variety of primary backgrounds, including pulmonology, neurology, psychiatry, psychology, otolaryngology, and dentistry. Manuscripts may be either basic or clinical original investigations or review articles. Potential authors of review articles are encouraged to contact the editors before submission, however, unsolicited review articles will be considered.



Impact of Sleep and Dialysis Mode on Quality of Life in a Mexican Population

Luxana Reynaga-Ornelas, Ph.D., R.N.1

Carol M. Baldwin, Ph.D., R.N., AHN-BC, F.A.A.N.2

Kimberly Arcoleo, Ph.D., M.P.H.3

Stuart F. Quan, M.D.2,4,5

1 División de Ciencias de la Salud. Departamento de Enfermería y Obstetricia Sede León

Universidad de Guanajuato

Sede San Carlos; Blvd. Puente Milenio #1001; Fracción del Predio San Carlos; C.P. 37670; León, Gto, Mexico

2 Arizona State University, Edson College of Nursing and Health Innovation

PAHO/WHO Collaborating Centre to Advance the Policy on Research for Health

500 N. 3rd Street, Phoenix, AZ USA 85004

3 University of Rochester School of Nursing

Box SON, Helen Wood Hall

601 Elmwood Avenue, Rochester, NY USA 14642

4 Division of Sleep and Circadian Disorders Brigham and Women’s Hospital and Harvard Medical School

221 Longwood Ave. Boston, MA USA 02115

5 Asthma and Airway Disease Research Center, University of Arizona College of Medicine

1501 N. Campbell Ave., Tucson, AZ USA 85725



Background: Health-related quality of life (HR-QOL) is reduced with end-stage renal disease (ESRD) but little is known about the impact of sleep disorders, dialysis modality and demographic factors on HR-QOL of Mexican patients with ESRD.

Methods: 121 adults with ESRD were enrolled from 4 dialysis units in the state of Guanajuato, Mexico, stratified by unit and dialysis modality (hemodialysis [HD], continuous ambulatory peritoneal dialysis [CAPD] and automated peritoneal dialysis [APD]). Analysis included clinical information and data from the Sleep Heart Health Study Sleep Habits Questionnaire, the Medical Outcomes Study (MOS) short form (SF-36) HR-QOL measure and Epworth Sleepiness Scale.

Results: Overall, sleep symptoms and disorders were common (e.g., 37.2% insomnia). SF-36 scores were worse versus US and Mexican norms. HD patients reported better, while CAPD patients poorer HR-QOL for Vitality. With multivariate modelling dialysis modality, sleep disorders as a group and lower income were significantly associated with poorer overall SF-36 and mental health HR-QOL. Overall and Mental Composite Summary models showed HR-QOL was significantly better for both APD and HD with small to moderate effect sizes. Cost-effectiveness analysis demonstrated an advantage for APD.

Conclusions: Mexican ESRD patients have reduced HR-QOL, and sleep disorders may be an important driver of this finding. APD should be the preferred mode of dialysis in Mexico.


The prevalence of end stage renal disease is increasing worldwide with an estimated prevalence in 2010 of 4.9 million persons. Unfortunately, only half receive dialysis; this need is projected to more than double by 2030 (1). End stage renal disease (ESRD) is associated with cardiovascular morbidity and mortality, type 2 diabetes, cognitive decline, and bone and mineral disorders. In Mexico, it is a significant health problem with annual prevalence and incidence rates of 1,564 and 412 per million persons respectively with over 65,000 individuals receiving dialysis (2). In addition, between 2000 and 2013, the incidence rate of ESRD has increased 122% (2). It has an annual mortality rate of 12.3 deaths per 100,000 inhabitants and is the second leading cause of years lost due to premature death (2). The most common treatment for ESRD in Mexico is hemodialysis (HD) performed at dialysis centers in over 50% of patients. The remainder receive peritoneal dialysis (PD) at home of which 70% are on continuous ambulatory peritoneal dialysis (CAPD) and 30% are on automated peritoneal dialysis (APD) (2). With CAPD, dialysis fluid is infused manually into the peritoneal cavity and then drained over a few hours usually four times per day. With APD, the process is automated with a device with alarms and safety features and is done at night. Kidney transplantation remains uncommon.

Treatment for ESRD has significant physiological, psychological and socio-economic implications for the individual, family, and community. Not surprisingly, persons with ESRD report poorer health-related quality of life (HR-QOL) compared with the general population (3, 4). Several studies have examined dialysis modality type on HR-QOL. Better HR-QOL scores have been noted for PD compared with HD treatment for ESRD (5, 6), but not always (7-9). A meta-analysis found better utility-based quality of life for APD compared to CAPD (10) and a recent study found APD associated with better physical health and milder dialysis-related symptoms than CAPD (11). Most of the studies used in the meta-analysis were from North America, Europe or Asia. There is little data available comparing HR-QOL among dialysis modalities for persons with ESRD in Latin American countries including Mexico.

Sleep disorders in persons with ESRD are common with prevalence estimates between 50 to more than 80%, and negatively influence HR-QOL (12-14). Among patients with ESRD, they include nightmares, excessive daytime sleepiness (EDS), restless leg syndrome (RLS), sleep apnea syndrome (OSA), insomnia and poor sleep quality (13). Whether the prevalence and severity of sleep disorders are similar among dialysis modalities is unclear; previous studies have been discordant with equivalent (15-17) and dissimilar rates and severity both reported (18-20). Only one study performed comparisons among HD, APD and CAPD (20). It found similar rates of insomnia, but less OSA with HD and more RLS with APD.

The purpose of this study was to determine the associations among HR-QOL and sleep disorders as a function of dialysis modality in a Mexican population with ESRD. A differential association may be an important factor in choice of dialysis modalities. We hypothesized that in this population, sleep disorders would be an important determinant of HR-QOL in ESRD, that APD would be associated with better QOL and be more cost-effective than HD or CAPD.


Design. Participants were a convenience sample of 125 patients with ESRD selected among persons insured by the Insurance and Social Service Institute for State Workers (ISSSTE) who were living in the state of Guanajuato, Mexico. Participants were proportionately selected by clusters. The sample included 30 patients from each geographic location of dialysis treatment units in the cities of Celaya, Irapuato, Guanajuato and Leon; ten patients were selected per dialysis modality (CAPD, APD, and HD). Patients were included if they were 18 years of age or older, Spanish-speaking, receiving dialysis and had not been hospitalized for the immediate 3 months prior to recruitment. Patients with cognitive or other mental health deficits that would preclude them from completing survey questionnaires were excluded from the study. They were recruited for participation during their monthly meetings, or in the waiting room for their specialist appointment. At the time of initial contact or a later appointment, the patient was asked to provide written informed consent, and to complete an individual interview and surveys that included information about their health, sleep and HR-QOL. They were also asked to give consent for chart review. The study was approved by the University of Guanajuato Ethics Committee and the Arizona State University Institutional Review Board.

Data Collection. Trained interviewers obtained information regarding age, sex, marital status, socioeconomic status (SES), educational level, number of hospitalizations, and time since first treatment. Participants also completed the Spanish translated and validated Sleep Heart Health Study Sleep Habits Questionnaire, and the Spanish version of the 36-item Medical Outcomes Study (MOS) short form (SF-36) HR-QOL measure. Height and weight were obtained to determine body mass index (BMI). Recent glucose, albumin, creatinine, urea, and hematocrit/hemoglobin blood levels were extracted from the patient’s medical record within the past three months. Additional clinical data collected to calculate the financial cost were ESRD etiology, hospitalizations within the past year, type of catheter, dialysis dose, number of anti-hypertensive drugs, use of erythropoietin, number of HD sessions per week and last home visit by the dialysis team.

Measurement Tools

Sleep Heart Health Sleep Study (SHHS), Sleep Habits Questionnaire (SHQ). The SHQ instrument has typically been used with patients with unidentified sleep disorders. The questionnaire addresses nine aspects of sleep disorders: 1) Snoring; 2) Breathing pauses (apnea); 3) Witnessed apneas; 4) Daytime sleepiness; 5) Insufficient sleep; 6) Insomnia symptoms including unrefreshing or nonrestorative sleep; 7) Nightmares, 8) Restless legs syndrome; and 9) Self-reported weekday and weekend sleep duration. Sleep symptoms questions were rated on a 5-point Likert-type scale from ‘Never’ to Almost Always.’ The SHQ, developed for the SHHS, has been used in a variety of investigations and is accepted as an appropriate means of characterizing sleep health. The Spanish version of the SHQ was cross-language validated by Baldwin and colleagues and shows excellent agreement with the English version (21).

Epworth Sleepiness Scale. The Epworth Sleepiness Scale (ESS) is a validated self-completion tool that asks subjects to rate the likelihood of falling asleep in eight common situations using four ordinal categories ranging from 0 (no chance) to 3 (high chance) (22). Scores range from 0 to 24 with a score >10 suggesting EDS (22). The Spanish version of the ESS was incorporated into the SHQ and has demonstrated equivalent reliability and validity as the English version (23).

Medical Outcomes Survey (MOS) Short Form SF-36 (Spanish version). The MOS SF-36 is a widely-used measure of health status and HR-QOL (24). It measures variations in health care practices and outcomes in a self-administered survey that assesses eight health dimensions. Scores for each subscale range from 0–100, with higher scores representing better QOL (24). Subscales measure the following eight general health concepts: physical functioning (PF), role physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), mental health (MH) and role emotional (RE). The Spanish version was validated in a Mexican population (25).

SF-6 D scores. The short-form-6D is a preference-based health state classification developed from the SF-36. All participants who complete the SF-36 can be assigned an SF-6D score (26). The SF-6D is a continuous measure, scored on a 0.29-1.0 scale, with 1.00 indicating optimal health. It has been used in economic evaluations of interventions for ESRD (27).

Data Analysis

Continuous variables are reported as means and standard deviations and categorical variables by percentages. A chi-square test was used to assess the association of demographic characteristics with dialysis modality. Comparisons between HR-QOL scores and the treatment groups were performed by analysis of variance (ANOVA). Effect sizes were estimated using Cohen’s d. Multiple linear regression analysis was performed controlling for socio-demographic factors, income (SES) and sleep disorders. SAS (V9.1) and IBM SPSS (V25) were used for data analysis. P <0.05 was considered statistically significant unless otherwise stated.

A cost effectiveness analysis utilizing the quality-adjusted life year (QALY) method examined the cost-effectiveness of each dialysis modality group. Cost data was obtained from data available online from Mexican governmental sources. The QALY was computed as the number of years on dialysis/hemodialysis x SF-6D score. A ratio of the difference in cost to the difference in effectiveness (QALY) was computed for each of the three therapies which yielded the incremental cost-effectiveness ratio (ICER).


Of 125 patients approached for recruitment, 121 fulfilled the inclusion criteria, and all agreed to voluntarily participate and provide written informed consent. Socio-demographic and clinical characteristics of the consenting patients are shown in Table 1.

Table 1. Socio-demographic and Clinical Characteristics of Study Participants by Dialysis Modality.

Note: ‡p<0.01; *p < 0.05; †p<0.10. APD (Automated Peritoneal Dialysis); CAPD (Continuous Ambulatory Peritoneal Dialysis); HD (Hemodialysis).

There was a slightly greater percentage of males (55.4%) and 39.7% were 65 years of age or older. Clinical characteristics were not available on all patients. However, patients dialyzed with APD were younger, more highly educated, had higher incomes, consumed less alcohol and were more likely to be working. There was a trend for APD patients to have a higher creatinine. Otherwise, there were no differences among the 3 groups.

The prevalence of self-reported sleep disorders or symptoms overall, as well as stratified by dialysis modality are presented in Table 2.

Table 2. Prevalence of Self-reported Sleep Disorders and Symptoms by Dialysis Type

Note: *p < 0.05, †p <0.10. EDS (Excessive Daytime Sleepiness); APD (Automated Peritoneal Dialysis); CAPD (Continuous Ambulatory Peritoneal Dialysis); HD (Hemodialysis).

Notably, all patients reported at least one sleep symptom in the past year (data not shown). Insomnia was the most frequently reported disorder and was particularly prevalent for patients receiving HD although not statistically significant. There also was a trend for HD (42.5%) and CAPD (41.0%) patients to report higher rates of non-restorative (unrefreshing) sleep compared to APD patients (19%). In contrast, APD patients reported higher rates of witnessed apnea and snoring (14.3% and 25.6%, respectively) compared to CAPD (10.3%, 19.4%) and HD (5.1%, 17.5%) patients. Patients receiving APD were less likely to report EDS (11.9%) on the ESS but this was not statistically significant compared to CAPD (25.6%) and HD (25.0%). The prevalence of sleep disorders was the same for those younger than 65 years of age in comparison to those older than 65 years (data not shown) except for problems with waking up too early and not being able to fall back asleep (younger: 32.9% vs. older 51.2%, p=0.05)

Table 3 presents the comparison of the eight SF-36 domains and the Physical and Mental Component Summary (PCS and MCS) scores for the three dialysis modality groups with effect sizes for pairwise comparisons.

Table 3. Mean Scores and Standard Deviations for SF-36 Domains, Physical and Mental Composite Scores and SF-6D Scores by Dialysis Modality

Note: ‡p<0.01; *p < 0.05; †p <0.10. PCS (Physical Composite Score); MCS (Mental Composite Score); SD (Standard Deviation); APD (Automated Peritoneal Dialysis); CAPD (Continuous Ambulatory Peritoneal Dialysis); HD (Hemodialysis). Cohen’s d effect sizes were calculated examining the differences between dialysis type groups (small effect size ~0.2, medium effect size ~0.5, large effect size ~0.8).

The patients on HD reported significantly better HR-QOL for Vitality and a trend towards higher Social Functioning compared to persons on CAPD and APD; the patients on CAPD experienced the poorest quality of life on these two scales. There was a trend for patients on APD and HD to indicate better Physical Functioning and Role Physical HR-QOL compared to the CAPD patients. There was a tendency for better mental health on the MCS for patients receiving HD and APD compared to patients on CAPD. Importantly, effect sizes for the various domains and subdomains showed that they were generally small to moderate for contrasts between CAPD and either APD or HD. However, they were trivial to small between APD and HD. No other notable differences were observed among groups on the SF-36.

Determinants of HR-QOL was further investigated using multivariate modelling with socio-demographic factors, co-morbidities and self-reported sleep disorders and symptoms as potential explanatory variables. Dialysis modality (CAPD associated with worse HR-QOL in comparison to HD and APD, F=4.87, p<.02), sleep disorders and symptoms as a group (i.e., any of symptoms consistent with obstructive sleep apnea, insomnia, insufficient sleep and restless legs syndrome, F=17.79, p<.0001) and lower income (F=4.48, p<.04) were significantly associated with worse HR-QOL on the Mental Composite Summary of the SF-36, accounting for 34% of the variance (F=4.02, p=.0004). In contrast, the model for the Physical Composite Summary was not statistically significant. HR-QOL was significantly better for both APD (Least Square Mean=52.0 + 2.3) and HD (51.4 + 2.6) in comparison to CAPD (43.0 + 2.5, p<.025 vs. APD/HD) in the Mental Composite Summary, but not the Physical Composite Summary models (Least Square Means: CAPD: 31.4 + 2.5, APD: 33.7 + 2.3, HD: 34.8 + 2.5; p>.05 for all comparisons).

Cost effectiveness analyses for each dialysis modality are in Table 4.

Table 4. Dialysis Modalities Cost Analysis

Note: APD (Automated Peritoneal Dialysis); CAPD (Continuous Ambulatory Peritoneal Dialysis); HD (Hemodialysis). QALY (quality-adjusted life year), ICER (Incremental Cost-Effectiveness Ratio); IE (Incremental effectiveness); IC (Incremental Cost).

Although CAPD was the least costly, it was the least effective (QALY=0.71); APD was less costly than HD, but was more effective (APD QALY: 2.05 vs. HD QALY 1.44) and HD was the most costly with moderate effectiveness. Comparing the incremental cost effectiveness ratios among APD, CAPD and HD, APD was superior to both CAPD and HD, and HD was better than CAPD.


In this study, we found that there is a high prevalence of sleep disorders and symptoms among Mexican patients with ESRD with differences in prevalence among dialysis modalities. Like other chronic medical conditions, HR-QOL, particularly mental health aspects, was poor in these patients and notably, the presence of sleep disorders was an important determinant of poorer HR-QOL.

Consistent with previous reports (12, 13, 28), we observed that sleep disorders and symptoms of sleep disorders were common among Mexican patients on dialysis. The explanation for the high rate of sleep disorders and symptoms in ESRD is likely multifactorial including metabolic issues, medications, poor sleep hygiene and dysfunction in ventilatory control (13). In addition, we found that there were differences in prevalence rates for some sleep disorders and symptoms among dialysis modalities. Previous investigations comparing the prevalence of sleep disorders among dialysis modalities have not been consistent. Some studies comparing only APD to CAPD have found no differences (15-17). In others, sleep problems as a generic symptom tended to be more common among APD compared to CAPD (18), and more frequent among HD in comparison with PD (19). To our knowledge, there is one other study that compared the rates of sleep disorders and symptoms among all 3 dialysis modalities (20). In that study, the rates of insomnia were high (>80%), but not different among dialysis modalities. Obstructive sleep apnea was the least common in HD patients (36% vs 60% [APD] and 65% [CAPD]). Furthermore, they observed less RLS in HD patients (23%) in comparison to APD (50%) and CAPD (33%). In contrast, we observed that unrefreshing sleep, a symptom of insomnia, was more common in HD and CAPD, snoring and witnessed apneas to be more frequent in APD, and no differences in the prevalence rates of RLS. The explanation for the large amount of discrepancy among various studies is unclear. However, possibilities include differences in the socio-demographic characteristics of the study populations and the questions used to elicit information. Further studies are required, particularly ones that use overnight polysomnography and standardized questionnaires.

We found there were few differences in the prevalence of sleep disorders or their symptoms between older and younger patients with ESRD. The only exception was early morning awakenings which are a common complaint among the elderly and may reflect a phase advance in sleep timing (29). Otherwise, in contrast to our findings, older persons in general population cohorts report more problems with their sleep (30, 31). We propose that the negative impact of ESRD on sleep quality had greater impact on younger patients thus negating any age differences in prevalence rates.

Despite the availability of dialysis to treat ESRD, HRQOL remains low compared to the general population (3, 4). Our findings in a cohort of Mexican patients with ESRD being treated with 3 different dialysis modalities is no different and are generally consistent with data from a large study of US patients with ESRD (32). Compared to the previous study in Mexican patients with ESRD, all of whom were receiving HD (28), however, we found lower scores on the Physical Function and higher scores on the Role Emotional scales. One-third of the current study was comprised of patients on CAPD, and thus our finding of worse Physical Function can be attributed to lower scores among this subgroup. The discrepancy in the Role Emotional scale, however, remains unexplained. International comparisons of HRQOL in patients with ESRD exhibit considerable heterogeneity (32). This may be related to cultural diversity, social determinants of health, health inequality or differences in health delivery systems across countries. In Mexico, availability and adequacy of dialysis varies considerably according to the insurance status of the patient (2). Irrespective of potential cross-cultural and international differences, it is important for clinicians and health care workers to realize that HR-QOL is reduced in ESRD and comparable to other chronic medical conditions despite the use of dialysis. Our findings support the recommendation by Jha et al. that national programs for chronic diseases include strategies to reduce burden and costs relevant to kidney disease (33).

Importantly, we found that in multivariate analyses, the presence of sleep disorders was a major factor in adversely affecting HR-QOL with the primary impact on the mental health component of HR-QOL. Other studies also have found negative associations between various sleep disorders and HR-QOL in patients with ESRD (12, 14). Our findings, however, extend these previous observations to a Latin American population. They further highlight the importance of sleep as a determinant of HR-QOL in ESRD and suggest that screening for poor sleep and sleep disorders should be an essential part of the care of patients undergoing chronic dialysis. As well, sleep health promotion strategies should be developed and implemented relevant to this patient population and examined germane to improving HR-QOL, further reducing health care cost, sequelae from ESRD, and dialysis type.

In addition to sleep disorders, we observed that mode of dialysis was an important determinant of HR-QOL. Several extant studies also have examined dialysis modality type on HR-QOL and most report better HR-QOL for PD compared to HD treatment for ESRD (5, 6). One study in elderly patients, however, observed no difference between PD and HD (7). It is suggested that travel and dietary restrictions are fewer, and recreation opportunities and dialysis access are improved with PD resulting in better HR-QOL (34). In addition, indices of depression may be higher in comparisons of HD to PD (5). Comparisons of APD to CAPD are fewer (3, 16, 18, 35), with most showing that APD is associated with better HR-QOL (3, 18, 35). Our study extends these previous studies by being one of the few to examine quality of life among all three dialysis modalities simultaneously (36). Our results suggest that in comparison to HD and APD, CAPD is associated with worse HR-QOL with small to moderate effect sizes; there was little difference between HD and APD with trivial to small effect sizes. The burdensome requirement for continuous dialysate exchanges in CAPD compared to only nightly automated exchanges with APD or scheduled visits to a dialysis center for HD likely explains this finding. Furthermore, our cost-effectiveness analysis indicates that for the socio-economic landscape in Mexico, APD should be the preferred dialysis modality.

Our study has some important limitations. First, the study population was not prospectively selected or randomized with respect to dialysis modality. Unfortunately, choice of dialysis modality in Mexico and elsewhere is dictated frequently by health insurance, patient income and availability of resources. Thus, it is possible that our findings related to HR-QOL and sleep disorders may have been impacted by an assignment bias. For example, CAPD may have been differentially provided to patients with lower income, thus accounting for worse HR-QOL. We attempted to mitigated this by controlling for some of these potential biases with our multivariate analysis. Nevertheless, residual confounding may have been present. Second, our analyses are cross-sectional and causality cannot be confirmed. Third, the presence of sleep disorders and symptoms was self-reported; there may have been some misclassification. Any misclassifications, however, were likely non-differential. Last, our study sample is relatively small; some non-statistically significant differences may represent type II error. Conversely, use of multiple comparisons may have resulted in type I error in some cases.

In summary, HR-QOL is reduced in Mexican patients with ESRD and the presence of sleep disorders may be an important driver of this finding. Interventions targeted at improving sleep quality and treating sleep disorders may improve HR-QOL in this population. Differences in HR-QOL among dialysis modalities suggest that in Mexico, APD should be the preferred mode of dialysis.


Financial support was provided to Dr. Reynaga-Ornelas by the Bardewick Scholarship from Arizona State University and the PROMEP Scholarship from the University of Guanajuato. Dr. Quan was partially supported by AG009975 from the National Institute of Aging.


  1. Liyanage T, Ninomiya T, Jha V, et al. Worldwide access to treatment for end-stage kidney disease: a systematic review. Lancet. 2015;385(9981):1975-82. [CrossRef] [PubMed]
  2. García-García G, García-Bejarano H, Breien-Coronado H, et al. Chapter 9 - End-Stage Renal Disease in Mexico. In: Chronic Kidney Disease in Disadvantaged Populations. García-García G, Agodoa LY and Norris K, eds. Cambridge, MA: Academic Press, 2017; 77-83. [CrossRef] [PubMed]
  3. Reina Neyra M, Cirera Segura F, Martín Espejo J. Salud Percibida por los Pacientes en DPCA y DPA. Rev Soc Esp Enferm Nefrol. 2008;11(2):26-33. [CrossRef]
  4. Guerini Rocco D, Mercieri A, Yavuzer G. Multidimensional health-status assessment of chronic hemodialysis patients: the impact on quality of life. Eura Medicophys. 2006;42(2):113-9. [PubMed]
  5. Ginieri-Coccossis M, Theofilou P, Synodinou C, Tomaras V, Soldatos C. Quality of life, mental health and health beliefs in haemodialysis and peritoneal dialysis patients: investigating differences in early and later years of current treatment. BMC Nephrol. 2008;914-2369-9-14. [CrossRef] [PubMed]
  6. Chen JY, Wan EYF, Choi EPH, et al. The health-related quality of life of chinese patients on hemodialysis and peritoneal dialysis. Patient. 2017;10(6):799-808. [CrossRef] [PubMed]
  7. Harris SA, Lamping DL, Brown EA, Constantinovici N, North Thames Dialysis Study (NTDS) Group. Clinical outcomes and quality of life in elderly patients on peritoneal dialysis versus hemodialysis. Perit Dial Int. 2002;22(4):463-70. [PubMed]
  8. Queeley GL, Campbell ES. Comparing treatment modalities for end-stage renal disease: A meta-analysis. Am Health Drug Benefits. 2018;11(3):118-27. [PubMed]
  9. Manavalan M, Majumdar A, Harichandra Kumar KT, Priyamvada PS. Assessment of health-related quality of life and its determinants in patients with chronic kidney disease. Indian J Nephrol. 2017;27(1):37-43. [CrossRef] [PubMed]
  10. Wyld M, Morton RL, Hayen A, Howard K, Webster AC. A systematic review and meta-analysis of utility-based quality of life in chronic kidney disease treatments. PLoS Med. 2012;9(9):e1001307. [CrossRef] [PubMed]
  11. Yang F, Luo N, Lau T, Yu ZL, Foo MWY, Griva K. Health-related quality of life in patients treated with continuous ambulatory peritoneal dialysis and automated peritoneal dialysis in Singapore. Pharmacoecon Open. 2018;2(2):203-8. [CrossRef] [PubMed]
  12. Brekke FB, Amro A, Hortemo Osthus TB, Dammen T, Waldum B, Os I. Sleep complaints, depression and quality of life in Norwegian dialysis patients. Clin Nephrol. 2013;80(2):88-97. [CrossRef] [PubMed]
  13. Hanly P. Sleep disorders and end-stage renal disease. Curr Opin Pulm Med. 2008;14(6):543-50. [CrossRef] [PubMed]
  14. Edalat-Nejad M, Qlich-Khani M. Quality of life and sleep in hemodialysis patients. Saudi J Kidney Dis Transpl. 2013;24(3):514-8. [CrossRef] [PubMed]
  15. Turkmen K, Yazici R, Solak Y, et al. Health-related quality of life, sleep quality, and depression in peritoneal dialysis and hemodialysis patients. Hemodial Int. 2012;16(2):198-206. [CrossRef] [PubMed]
  16. Guney I, Solak Y, Atalay H, et al. Comparison of effects of automated peritoneal dialysis and continuous ambulatory peritoneal dialysis on health-related quality of life, sleep quality, and depression. Hemodial Int. 2010;14(4):515-22. [CrossRef] [PubMed]
  17. Eryavuz N, Yuksel S, Acarturk G, et al. Comparison of sleep quality between hemodialysis and peritoneal dialysis patients. Int Urol Nephrol. 2008;40(3):785-91. [CrossRef] [PubMed]
  18. Bro S, Bjorner JB, Tofte-Jensen P, et al. A prospective, randomized multicenter study comparing APD and CAPD treatment. Perit Dial Int. 1999;19(6):526-33. [PubMed]
  19. Eghbali M, Shahqolian N, Nazari F, Babaee S. Comparing problems of patients with chronic renal failure undergoing hemodialysis and peritoneal dialysis referring to medical university's hospitals. Iran J Nurs Midwifery Res. 2009;14(1):1-5.
  20. Losso RL, Minhoto GR, Riella MC. Sleep disorders in patients with end-stage renal disease undergoing dialysis: comparison between hemodialysis, continuous ambulatory peritoneal dialysis and automated peritoneal dialysis. Int Urol Nephrol. 2015;47(2):369-75. [CrossRef] [PubMed]
  21. Baldwin CM, Choi M, McClain DB, Celaya A, Quan SF. Spanish translation and cross-language validation of a sleep habits questionnaire for use in clinical and research settings. J Clin Sleep Med. 2012;8(2):137-46. [CrossRef] [PubMed]
  22. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14(6):540-5. [CrossRef] [PubMed]
  23. Ferrer M, Vilagut G, Monasterio C, Montserrat JM, Mayos M, Alonso J. Measurement of the perceived impact of sleep problems: the Spanish version of the functional outcomes sleep questionnaire and the Epworth sleepiness scale. Med Clin (Barc). 1999;113(7):250-5. [PubMed]
  24. Ware JE,Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473-83. [CrossRef] [PubMed]
  25. Zúniga AM, Carrillo-Jiménez TG, Fos JP, Gandek B, Medina-Moreno M. Evaluación del estado de salud con la Encuesta SF-36: resultados preliminares en México. Salud Pública de México. 1999;41(2):110-8. [CrossRef] [PubMed]
  26. Brazier J, Roberts J, Deverill M. The estimation of a preference-based measure of health from the SF-36. J Health Econ. 2002;21(2):271-92. [CrossRef]
  27. Davison SN, Jhangri GS, Feeny DH. Comparing the health utilities index mark 3 (HUI3) with the short form-36 preference-based SF-6D in chronic kidney disease. Value Health. 2009;12(2):340-5. [CrossRef] [PubMed]
  28. Dehesa-Lopez E, Correa-Rotter R, Olvera-Castillo D, Gonzalez-Parra C, Baizabal-Olarte R. Clinical, dialytic, and laboratory factors associated with poor health-related quality of life in Mexican patients on hemodialysis. Rev Invest Clin. 2016;68(4):192-200. [PubMed]
  29. Kim JH, Duffy JF. Circadian rhythm sleep-wake disorders in older adults. Sleep Med Clin. 2018;13(1):39-50. [CrossRef] [PubMed]
  30. Klink M, Quan SF. Prevalence of reported sleep disturbances in a general adult population and their relationship to obstructive airways diseases. Chest. 1987;91(4):540-6. [CrossRef] [PubMed]
  31. Ohayon MM, Zulley J, Guilleminault C, Smirne S, Priest RG. How age and daytime activities are related to insomnia in the general population: consequences for older people. J Am Geriatr Soc. 2001;49(4):360-6. [CrossRef] [PubMed]
  32. Fukuhara S, Lopes AA, Bragg-Gresham JL, et al. Health-related quality of life among dialysis patients on three continents: the Dialysis Outcomes and Practice Patterns Study. Kidney Int. 2003;64(5):1903-10. [CrossRef] [PubMed]
  33. Jha V, Garcia-Garcia G, Iseki K, et al. Chronic kidney disease: global dimension and perspectives. Lancet. 2013;382(9888):260-72. [CrossRef] [PubMed]
  34. Wu AW, Fink NE, Marsh-Manzi JV, et al. Changes in quality of life during hemodialysis and peritoneal dialysis treatment: generic and disease specific measures. J Am Soc Nephrol. 2004;15(3):743-53. [CrossRef] [PubMed]
  35. de Wit GA, Merkus MP, Krediet RT, de Charro FT. A comparison of quality of life of patients on automated and continuous ambulatory peritoneal dialysis. Perit Dial Int . 2001;21(3):306-12. [PubMed]
  36. Caballero-Morales S, Trujillo-Garcia JU, Welsh-Orozco U, Hernandez-Cruz ST, Martinez-Torres J. Calidad de vida en pacientes con hemodiálisis, diálisis peritoneal continua ambulatoria y automatizada. Arch Med Fam. 2006;8(3):163-8.

Cite as: Reynaga-Ornelas L, Baldwin CM, Arcoleo K, Quan SF. Impact of sleep and dialysis mode on quality of life in a Mexican population. Southwest J Pulm Crit Care. 2019;18(5):122-34. doi: PDF 


Out of Center Sleep Testing in Ostensibly Healthy Middle Aged to Older Adults

Stuart F. Quan, M.D.1,2

Brandon J. Lockyer1

Salma Batool-Anwar, M.D., M.P.H.1

Daniel Aeschbach, Ph.D.1,3

1Division of Sleep and Circadian Disorders, Department of Medicine and Department of Neurology; Brigham and Women's Hospital and Division of Sleep Medicine, Harvard Medical School, Boston, MA

2Asthma and Airways Research Center, University of Arizona College of Medicine, Tucson, AZ

3Department of Sleep and Human Factors Research; Institute of Aerospace Medicine; German Aerospace Center; Cologne, 51147; Germany


Background: Out of Center Sleep Testing (OCST) is used increasingly to diagnose obstructive sleep apnea (OSA). However, there are few data using OCST that quantify the amount of intrinsic apneic and hypopneic events among asymptomatic healthy persons, especially those who are elderly. This analysis reports the results of OCST in a small group of ostensibly healthy asymptomatic individuals.

Methods: The study population was comprised of ostensibly healthy middle-aged to elderly volunteers for studies of circadian physiology. Before undergoing an OCST, they were found to be free of any chronic medical or psychiatry condition by history, physical and psychologic examination and by a variety of questionnaires and laboratory tests.

Results: There were 24 subjects ranging in age from 55-70 years who had an OCST performed. Repeat studies were required in only 3 subjects. Over half the study population was over the age of 60 years (54.2% vs 45.8%); the majority were men (70.8%). The mean apnea hypopnea index (AHI) was 9.2 /hour with no difference between younger and older subjects. However, 11 had an AHI > 5 /hour. Five had an AHI >15 /hour and 2 had an AHI >40 /hour. Those with an AHI <15 /hour had a mean AHI of 4.4 /hour (95% CI:2.8-6.0 /hour).

Conclusions: Although OCST has a low failure rate, there is a high prevalence of intrinsic obstructive apnea and hypopnea in ostensibly healthy asymptomatic persons.


Out of center sleep testing (OCST) is increasingly used instead of laboratory polysomnography (PSG) for the identification of persons with obstructive sleep apnea (OSA) (1). There have been a number of studies validating the use of OCST for this purpose (1). Consequently, large research studies now are using OCST to identify subjects with OSA for clinical trials or observational studies (2-4). Out of center sleep testing also may have a role in identifying the presence of unrecognized OSA in studies of asymptomatic normal individuals. Studies reporting on the frequency of apneic and hypopneic events in healthy individuals using current PSG monitoring techniques (5, 6) found surprisingly high prevalence rates of OSA. Similar reports using OCST also noted that OSA was common in asymptomatic volunteers, but many of these subjects still had chronic medical conditions (7, 8). Thus, there is little information on the prevalence of OSA using OCST, especially in those who are older without any co-morbidities.

In this report, we describe the results of OCST in a small group of middle-aged to older adults who were screened intensively to exclude the presence of chronic sleep and medical conditions. We hypothesized that in this group of ostensibly healthy adults the prevalence of OSA would be less than previously observed.


Potential subjects between 55 and 70 years of age were identified through public advertisements for volunteers to participate in a circadian physiology research study. The study was approved by the Partners Health Care Human Research Committee, and subjects gave written informed consent prior to their participation. Initially, 5,225 individuals were screened by telephone for medical and psychiatric exclusion criteria. Those who passed (n=90) were invited for an interview and more intensive screening which included a medical history, the Pittsburgh Sleep Quality Index (PSQI) (9), Epworth Sleepiness Scale (ESS) (10) the Berlin Questionnaire (11), blood and urine tests, an electrocardiogram, and a complete physical examination by a physician. In addition, a structured psychologic examination was conducted by a clinical psychologist along with completion of several psychological screening tests including the Geriatric Depression Scale (12), Mattis Dementia Rating Scale (13) and the Mini Mental Status Examination (14). Potential subjects also could not have worked at night for the previous 3 years or recently traveled across time zones. Those who were determined to be free from any acute or chronic medical or psychiatric condition including but not limited to obesity (body mass index, BMI < 30 kg/m2), medication use, hypertension, cardiovascular or pulmonary disease, neoplasia, and disorders of the gastrointestinal, renal, endocrine, metabolic or neurologic systems were asked to undergo an OCST.

The OCST was performed using the Embletta Gold (Embla Systems, Broomfield, CO), a Type III OCST device. The testing montage included nasal pressure, pulse oximetry, bilateral leg electromyography, and chest and abdominal inductance plethysmography. Subjects were instructed to sleep at their habitual hours during OCST. Procedure for determining lights out and lights on, sleep onset and sleep offset, and wake periods during OCST in the sleep, aging and circadian rhythm disorders is given in Appendix 1. Estimated total sleep time was ascertained by the scoring technologist on the basis of changes in the recorded signals indicative of sleep onset or offset and a questionnaire administered to the subject on the morning after the study (see online supplement for the protocol). Studies were scored for apneas, hypopneas and periodic limb movements according to the following criteria. An apnea was defined as > 90% amplitude decrease from baseline of the nasal pressure signal lasting ≥ 10 s. Hypopneas were scored if an event was at least 10 s in duration and if there was a clear amplitude reduction of the nasal pressure signal that was associated with an oxygen desaturation > 4%. Obstructive or central apneas were identified by the presence or absence of respiratory effort, respectively. The apnea hypopnea index (AHI) was calculated as the sum of all apneas and hypopneas divided by the estimated total sleep time. Periodic limb movements were identified using American Academy of Sleep Medicine criteria (15). The periodic limb movement index (PLMI) was computed as the sum of all periodic limb movements divided by the estimated total sleep time. All OCST recordings were scored by a registered polysomnographic technologist and reviewed by a board-certified sleep physician.

Six subjects who had successfully completed the circadian physiology protocol were invited again to enroll in a related protocol approximately 1-3 years later. They repeated the aforementioned screening procedures including a second OCST.

Paired and unpaired Student’s t-tests were used to compare means. Comparisons between proportions were performed using c2. Data are expressed as means ± SD or number and % of cases. Data were analyzed using IBM SPSS Statistics V24 (Armonk, NY).


As shown in Table 1, there were 24 subjects who successfully underwent a screening OCST.

Their ages ranged from 55 to 70 years. Over half the study population was over the age of 60 years [13/24 (54.2 %) vs 11/24 (45.8%)], and the majority were men (70.8%). In 3 subjects, the initial OCST provided insufficient data and a repeat study was required. The mean AHI was 9.2 /hour overall and there were no differences between younger and older subjects. Notably, 11 subjects (46%) had an AHI greater than 5 /hour. Five (21%) had an AHI greater than 15 /hour and 2 subjects had an AHI greater than 40 /hour. Excluding subjects with an AHI ≥15 /hour yielded a mean AHI of 4.4 (95% CI: 2.8-6.0) /hour. Younger subjects had a higher BMI (27.1 ± 2.7 vs. 24.2 ± 3.5 kg/m2, p=0.036), tended to have a longer estimated total sleep time (9.2 ± 0.6 vs. 7.9 ± 2.1 hours, p=0.059), and a slightly lower average nocturnal oxygen saturation (94.9 ± 1.4 vs. 96.1 ± 1.4%, p=.061). No other differences were observed between young and older subjects.

In Table 2 are shown the sleep and anthropometric findings for the 6 subjects who had repeat testing.

The interval between tests ranged from 382 to 930 days (mean: 672 ± 227 days). Although there was a slight increase in BMI over this interval, no changes were noted in their sleep quality, AHI or PLMI.


In this study, we found that it was feasible to screen an ostensibly healthy asymptomatic group of middle to older aged adults for the presence of OSA using a Level III OCST device. The results of the OCST were replicable over an interval of several years and there were few technical failures. Furthermore, evidence of OSA was observed in a substantial proportion of these individuals underscoring that the diagnosis of OSA remains unrecognized in many elderly persons.

Over the past 20 years, there have been numerous clinical trials and cohort studies that have recorded data related to the presence of OSA (2-4, 8, 16, 17). Most have used PSG recorded in the laboratory or at home (16-18). However, the use of PSG is logistically complex and expensive. Additionally, the equipment required for data acquisition may artifactually disrupt the subject’s sleep. In contrast, OCST is less intrusive and expensive, but actual sleep is not recorded. However, to our knowledge there have not been previous studies that have determined the normative values for the AHI using OCST in a group of ostensibly healthy middle-aged to older adults. In this small cohort, the mean AHI was 9.2 /hour. According to the 3rd International Classification of Sleep Disorders (19), an AHI ≥15 /hour is diagnostic of OSA even in the absence of symptoms or associated medical conditions. Therefore, after excluding those who met criteria for at least moderate OSA (i.e., AHI ≥15 hour), our findings indicate an average value of 4.4 /hour in those individuals with a “normal” AHI using OCST. In contrast, a previous study of healthy volunteers for circadian physiology research using similar inclusion and exclusion criteria found the overall mean AHI of all subjects using PSG was substantially higher; hypopneas were identified if reductions in airflow were associated with a minimum 3% oxygen desaturation or a cortical arousal (6). However, a more recent study also using PSG found AHI values more similar to our observations (5). Although it would be expected that OCST may underreport the presence of hypopneas, the explanation for the differences between the two PSG studies is unclear given that the recording montages and respiratory scoring algorithms appeared to be similar.

A striking finding from this study is the high prevalence of OSA among these carefully screened, ostensibly healthy volunteers who had no evidence of a sleep disorder based on their Berlin Questionnaire, PSQI and ESS. The AHI of 2 subjects documented the presence of severe OSA which is usually an indication for treatment. The absence of hypersomnia in a substantial proportion of persons with PSG evidence of OSA has been clearly documented (20). Our data extend these observations by demonstrating the existence of severe OSA in ostensibly healthy middle-aged to older adults. Although some data suggest that such individuals are not at risk for cardiovascular disease or other sequelae of OSA (8), whether this prognosis is correct is still not settled.

Some, but not all epidemiologic data suggest that OSA slowly worsens with age. In contrast, we observed no progression of OSA over an interval of approximately 1-2.5 years (8, 21). However, it is likely that our follow up interval was insufficient to detect a change given the small number of subjects.

In conclusion, use of OCST to screen for OSA is feasible in research studies of normal individuals. Importantly, a relatively high proportion of even ostensibly healthy individuals can be expected to show evidence of OSA.


This study was supported by P01 AG009975 from the National Institute of Aging. We would like to express our gratitude to Alec Rader and Jacob Medina for their help with subject recruitment and Stephanie Marvin for scoring support.


  1. Kapur VK, Auckley DH, Chowdhuri S, et al. Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline. J Clin Sleep Med. 2017;13(3):479-504. [CrossRef] [PubMed]
  2. Gottlieb DJ, Punjabi NM, Mehra R, et al. CPAP versus oxygen in obstructive sleep apnea. N Engl J Med. 2014;370(24):2276-85. [CrossRef] [PubMed]
  3. Zhao YY, Wang R, Gleason KJ, et al. Effect of Continuous Positive Airway Pressure Treatment on Health-Related Quality of Life and Sleepiness in High Cardiovascular Risk Individuals with Sleep Apnea: Best Apnea Interventions for Research (BestAIR) Trial. Sleep. 2017;40(4):10.1093/sleep/zsx040. [CrossRef] [PubMed]
  4. Redline S, Sotres-Alvarez D, Loredo J, et al. Sleep-disordered breathing in Hispanic/Latino individuals of diverse backgrounds. The Hispanic Community Health Study/Study of Latinos. Am J Respir Crit Care Med. 2014;189(3):335-44. [CrossRef] [PubMed]
  5. Mitterling T, Hogl B, Schonwald SV, et al. Sleep and Respiration in 100 Healthy Caucasian Sleepers--A Polysomnographic Study According to American Academy of Sleep Medicine Standards. Sleep. 2015;38(6):867-75. [CrossRef] [PubMed]
  6. Pavlova MK, Duffy JF, Shea SA. Polysomnographic respiratory abnormalities in asymptomatic individuals. Sleep. 2008;31(2):241-8. [CrossRef] [PubMed]
  7. Sforza E, Pichot V, Martin MS, Barthelemy JC, Roche F. Prevalence and determinants of subjective sleepiness in healthy elderly with unrecognized obstructive sleep apnea. Sleep Med. 2015;16(8):981-6.[CrossRef] [PubMed]
  8. Sforza E, Hupin D, Pichot V, Barthelemy JC, Roche F. A 7-year follow-up study of obstructive sleep apnoea in healthy elderly: The PROOF cohort study. Respirology. 2017;22(5):1007-14. [CrossRef] [PubMed]
  9. Buysse DJ, Reynolds CF,3rd, 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. [CrossRef] [PubMed]
  10. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14(6):540-5. [CrossRef] [PubMed]
  11. Netzer NC, Stoohs RA, Netzer CM, Clark K, Strohl KP. Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med. 1999;131(7):485-91.[CrossRef] [PubMed]
  12. Yesavage JA, Brink TL, Rose TL, et al. Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res. 1982;17(1):37-49. [CrossRef] [PubMed]
  13. Mattis S. Mental status examination for organic mental syndrome in the elderly patient. In: Geriatric psychiatry. Bellak L and Karasu TE, eds. New York: Grune and Stratton, 1976; 77-121
  14. Pangman VC, Sloan J, Guse L. An examination of psychometric properties of the mini-mental state examination and the standardized mini-mental state examination: implications for clinical practice. Appl Nurs Res. 2000;13(4):209-213. [CrossRef] [PubMed]
  15. Iber C, Ancoli-Israel S, Chesson A, Quan SF. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications. 1st ed. Westchester, IL: American Academy of Sleep Medicine, 2007; 57.
  16. Quan SF, Howard BV, Iber C, et al. The Sleep Heart Health Study: design, rationale, and methods. Sleep. 1997;20(12):1077-85. [PubMed]
  17. Kushida CA, Nichols DA, Quan SF, et al. The Apnea Positive Pressure Long-term Efficacy Study (APPLES): rationale, design, methods, and procedures. J Clin Sleep Med. 2006;2(3):288-300. [PubMed]
  18. Chen X, Wang R, Zee P, et al. Racial/Ethnic Differences in Sleep Disturbances: The Multi-Ethnic Study of Atherosclerosis (MESA). Sleep. 2015;38(6):877-88. [CrossRef] [PubMed]
  19. Sateia MJ. International Classification of Sleep Disorders. 3rd ed. Darien, IL: American Academy of Sleep Medicine, 2014.
  20. He K, Kapur VK. Sleep-Disordered Breathing and Excessive Daytime Sleepiness. Sleep Med Clin. 2017;12(3):369-82.[CrossRef] [PubMed]
  21. Redline S, Schluchter MD, Larkin EK, Tishler PV. Predictors of longitudinal change in sleep-disordered breathing in a nonclinic population. Sleep. 2003;26(6):703-9. [CrossRef] [PubMed]

Cite as: Quan SF, Lockyer BJ, Batool-Anwar S, Aeschbach D. Out of center sleep testing in ostensibly healthy middle aged to older adults. Southwest J Pulm Crit Care. 2019;18:87-93. doi: PDF 


Sleep Related Breathing Disorders and Neurally Mediated Syncope (SRBD and NMS)

Damian Valencia, MD1 

Stella Pak, MD1

Juan Linares, MD1

Victor Valencia, BS2

Christopher Lee, MD1

John-Philip Markovic, MD1

Hemant Shah, MD1 


1Department of Medicine, Kettering Medical Center, Kettering, Ohio USA

2Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois USA



Introduction: Individuals with severe sleep related breathing disorders (SRBD) tend to experience intermittent hypoxia, sleep fragmentation and highly fluctuating intrathoracic pressures. Chronic exposure to these stressors sensitizes the parasympathetic system while suppressing the sympathetic system. Parasympathetic over-reactivity among patients with severe sleep related breathing disorders has been proposed as a predisposing factor for neurally mediated syncope.

Goal: We sought to determine the relative risk for neurally mediated syncope in patients with severe SRBD compared to the general population.

Methods: This is a retrospective cohort study of 228 cases selected from 2,598 patients who were referred for polysomnography on discharge from hospitalization. Incidence of neurally mediated syncope (NMS) was compared between patients with apnea-hypopnea-index (AHI) scores of 30 or greater and those with an AHI score below 5.

Results: Approximately 32% of patients with severe SRBD had a history of neurally mediated syncope compared to only 14% in patients with normal sleep breathing patterns (OR = 3.09, 95% CI: 1.25 - 7.62, p = 0.015).

Conclusion: Our multi-center retrospective study supports an association between SRBD and NMS.

Brief Summary

Current Knowledge/Study Rational. There are multiple reports that highlight a possible connection between sleep related breathing disorders and neurally mediated syncope. Deleterious effects on the autonomic and peripheral nervous system by severe sleep related breathing disorders have also been demonstrated. We sought to determine the association and relative risk of neurally mediated syncope in patients with severe sleep related breathing disorders.

Study Impact. Patients with severe sleep related breathing disorders are at increased risk for neurally mediated syncope. Early identification and appropriate treatment in this patient population may reduce rates of syncope, improve quality of life and clinical outcomes.


Sleep related breathing disorders (SRBD), comprise a spectrum of disorders characterized by chronic intermittent apnea and hypopnea, which includes obstructive sleep apnea (OSA), central sleep apnea, sleep-related hypoventilation, and nocturnal hypoxemia (1). Neurally mediated syncope (NMS), also known as reflex syncope, is defined as a transient loss of consciousness secondary to decreased cerebral blood supply, typically as a result of reflexive cardiac inhibition and decreased vascular tone. NMS includes vasovagal syncope, situational syncope and carotid sinus syncope (2). Autonomic dysfunction may also play a role in cases of NMS (3). Researchers have previously documented the deleterious effects of SRBD on the autonomic and peripheral nervous system (4-7). A connection between SRBD and NMS has been proposed by some, detailing cases of patients suffering from incapacitating recurrent syncope which demonstrates dramatic improvement or resolution after diagnosis and treatment of OSA (8-10). In this study, we sought to determine the association and relative risk of neurally mediated syncope in patients with severe sleep related breathing disorders.


This retrospective cohort analysis was performed using electronic medical record data collection from hospitals within the Kettering Health Network, including Fort Hamilton Hospital (Hamilton, Ohio), Grandview Medical Center (Dayton, Ohio), Greene Memorial Hospital (Xenia, Ohio), Kettering Medical Center (Kettering, Ohio), Soin Medical Center (Beavercreek, Ohio), Southview Medical Center (Centerville, Ohio) and Sycamore Medical Center (Miamisburg, Ohio). Individuals who underwent and completed in-facility polysomnography were selected for study review. Patients under the age of 18 years old and those with a pacemaker or implantable cardiac defibrillator were excluded from the study. Patients were divided into two groups; those with severe SRBD, defined as having an Apnea-Hypopnea Index (AHI) score of/ or greater than 30, and a control group, defined as patients having an AHI score of/ or less than 5. This study was approved by the institutional review board (IRB) at Kettering Health Network.

Statistical Methods: The Kolmogorov-Smirnov and Shapiro-Wilk tests were utilized to compare baseline patient demographics between each group; control and severe SRBD group. These tests were selected to better represent the data, with median interquartile range (IQR), as outliers were included in the analysis. Categorical variables were compared using Pearson’s Chi-squared test. Continuous variables were compared using the Student’s t-test or Wilcoxon rank sum test (Mann-Whitney U test). All estimates were reported as 95% confidence intervals with p-values. Two-sided p-values less than 0.05 were considered statistically significant. Multivariate logistic regression modeling was used to determine the effects of each variable while controlling for confounding variables. Odds ratios (OR) were calculated for each type of syncope in both the severe SRBD group and control group. All statistical analyses were performed using IBM SPSS Statistics for Windows version 20.0 (IBM Corp., Armonk, NY, USA).


A total of 2,598 patients were identified from the electronic medical record database, of which, only 228 patients fulfilled our inclusion criteria for severe SRBD (AHI score of/ or greater than 30), with 80 patients meeting criteria for the control group (AHI score of/ or less than 5). Among the 228 patients with severe SRBD, the most common subtype was obstructive sleep apnea (204 of 228 patients, 89.5%), followed by central sleep apnea (13 of 228 patients, 4.2%) and mixed type (11 of 228 patients, 3.6%). 

Initial comparison of demographic characteristics (Table 1) was done using univariate analysis.

Table 1: Baseline Characteristics of the Individuals with and without SRBD.

SRBD: sleep-related breathing disorder, IQR: interquartile range; BMI: body-mass index; AHI: apnea-hypopnea index; LEVF: left ventricular ejection fraction; COPD: chronic obstructive pulmonary disease; N: number; N/A: not applicable.

The SRBD group and control did not statistically significance differ in age (p = 0.79). Although gender differences were noted, 62.3% male in the SRBD group compared to 47.5% in the control group (p = 0.042), there were no statistically significant differences on multivariate logistic regression (p = 0.854). Differences in body mass index (BMI) between groups were noted on univariate (p = 0.042) and multivariate models (p = 0.041), with 36.5 (IQR 31.3 – 43.8) mean BMI of the SRBD group compared to 34.4 (IQR 27.3 – 40.4) in the control group.

The incidence of pre-existing comorbidities between groups was also compared. (Table 1) There were no statistically significant differences between the groups in terms of pulmonary artery pressure (p = 0.226), diabetes (p = 0.902) and coronary artery disease (p = 0.065). Univariate analysis did reveal differences amongst left ventricular ejection fraction (LVEF), 31.1% of patients with SRBD had LVEF <55% compared to only 17.5% in the control group (p = 0.19), hypertension (HTN), 75.4% of patients with SRBD had HTN compared to only 53.8% in the control group (p < 0.001), and chronic obstructive pulmonary disease (COPD), 29.8% of patients with SRBD compared to 43.8% in the control group (p = 0.023). These findings were not statistically significant on multivariate logistic regression; LVEF<55% (p = 0.326), HTN (p = 0.585), COPD (p = 0.576). 

The mean apnea hypopnea index (AHI) for the severe SRBD group was 53.2 (38.7-80.2), compared to 1.6 (0-2.6) in the control group (p < 0.001). The prevalence of NMS was higher in the SRBD group compared to the control group, 32% (73 of 228 patients) and 14% (11 of 80 patients), respectively; χ2 (2, N=308) = 9.96, p = 0.001. Prevalence of non-neurally mediated syncope did not differ significantly between the SRBD group and control group, 1% (2 of 228 patients) and 0% (no patients), respectively; Pearson’s Chi-squared test p = 0.571. Approximately 32% of patients with severe SRBD had a history of neurally mediated syncope compared to only 14% in patients with normal sleep breathing patterns (OR = 3.09, 95% CI: 1.25 - 7.62, p = 0.015). (Table 2).

Table 2: Multivariate Logistic Regression Modeling, Odds Ratio (OR) for Neurally Mediated Syncope.

CI: confidence interval; BMI: body mass index; AHI: apnea-hypopnea index; LEVF: left ventricular ejection fraction; COPD: chronic obstructive pulmonary disease.

Situational syncope has not been consistently recorded, OR and CI were not calculated.


This study suggests that individuals with severe sleep related breathing disorders are at increased risk for developing neurally mediated syncope. Chrysostomakis et al. (11) showed that parasympathetic activity is increased during the night in patients with obstructive sleep apnea and that continuous positive airway pressure (CPAP) treatment may restore autonomic balance. Puel et al. (8) suggested that intermittent hypoxia, sleep fragmentation and variations of intra-thoracic pressures may result in chronic adaptations to the autonomic nervous system, which may predispose patients to vasovagal syncope. Cintra et al. (12) noted that patients with vasovagal syncope exhibited sympathetic suppression during rapid eye movement (REM) sleep. Previous studies indicate that chronic intermittent hypoxia can also increase activation of free-radical oxidation, which in turn can elicit rapid and sustained expression of pro-inflammatory cytokines (12). This oxidative stress and inflammatory response can induce tissue damage and intermittent academia, eventually leading to up-regulation of pH sensitive ion channels on chemo-afferent neurons at the carotid bodies. Overexpression of these channels potentiates the carotid body response to changes in arterial oxygen saturation (12). It is possible that this mechanism also contributes to the higher prevalence of carotid sinus hypersensitivity and syncope among patients with severe SRBD. In accordance with our findings, there have been reported cases of recurrent syncope, which have resolved with correction of underlying SRBD (8-10). Appropriate management of SRBD in this patient population may reduce rates of NMS. Given the high prevalence of SRBD and neurally mediated syncope in the United States, further investigation is warranted to delineate the association between the two disease processes and the mechanisms which are involved.

Study Limitations

Our retrospective study design has limited control over consistency and accuracy. This study did not use any matching algorithm to match the control group to the individuals with severe SRBD for baseline characteristics. We did not utilize a caliper matching process to identify controls, and as a result, the control cohort was smaller than the study cohort. The diagnosis of vasovagal syncope was made based on clinical presentation. All patients who were diagnosed with vasovagal syncope did not have confirmatory tilt-table testing, limiting diagnostic accuracy and consistency.


Our study suggests that individuals with severe sleep-related breathing disorders (SRBD) are approximately 3 times (OR = 3.09, 95% CI: 1.25 - 7.62, p = 0.015) more likely to have experienced neurally mediated syncope (NMS) compared to case matched controls.


Rosaria Jordan (table/figure formatting)


  1. Tsara V, Amfilochiou A, Papagrigorakis M, Georgopoulos D, Liolios E. Guidelines for diagnosis and treatment of sleep-related breathing disorders in adults and children. Definition and classification of sleep related breathing disorders in adults: Different types and indications for sleep studies (part 1). Hippokratia. 2009;13:187-91. [PubMed]
  2. Alboni P, Brignole M, Menozzi C, et al. Diagnostic value of history in patients with syncope with or without heart disease. J Am Coll Cardiol. 2001;37(7):1921-8. [CrossRef] [PubMed]
  3. Mosqueda-Garcia R, Furlan R, Tank J, Fernandez-Violante R. The elusive pathophysiology of neurally mediated syncope. Circulation. 2000;102(23):2898-2906. [CrossRef] [PubMed]
  4. Li Y, Veasey SC. Neurobiology and neuropathophysiology of obstructive sleep apnea. NeuroMolecular Med. 2012;14(3):168-179. doi:10.1007/s12017-011-8165-7. [CrossRef] [PubMed]
  5. Gozal D, Daniel JM, Dohanich GP. Behavioral and anatomical correlates of chronic episodic hypoxia during sleep in the rat. J Neurosci. 2001;21(7):2442-50. [PubMed]
  6. Mayer P, Dematteis M, Pépin JL, et al. Peripheral neuropathy in sleep apnea: A tissue marker of the severity of nocturnal desaturation. Am J Respir Crit Care Med. 1999;159(1):213-9. [CrossRef] [PubMed]
  7. Dziewas R, Schilling M, Engel P, et al. Treatment for obstructive sleep apnoea: effect on peripheral nerve function. J Neurol Neurosurg Psychiatry. 2007;78(3):295-7. [CrossRef] [PubMed]
  8. Puel V, Pepin JL, Gosse P. Sleep related breathing disorders and vasovagal syncope, a possible causal link? Int J Cardiol. 2013;168(2):1666-7. [CrossRef] [PubMed]
  9. Barone D, Fine L, Bhandari N, Ana C. Syncope in hypoxemic respiratory arrest. J Sleep Med Disord. 2015;2(2):2-4. [CrossRef].
  10. Willis FB, Isley AL, Geda YE, Shaygan A, Quarles L, Fredrickson P a. Resolution of syncope with treatment of sleep apnea. J Am Board Fam Med. 2008;21(5):466-8. [CrossRef] [PubMed]
  11. Chrysostomakis SI, Simantirakis EN, Schiza SE, et al. Continuous positive airway pressure therapy lowers vagal tone in patients with obstructive sleep apnoea-hypopnoea syndrome. Hell J Cardiol. 2006;47(1):13-20. [PubMed]
  12. Cintra F, Poyares D, DO Amaral A, et al. Heart rate variability during sleep in patients with vasovagal syncope. Pacing Clin Electrophysiol. 2005;28(12):1310-6. [CrossRef] [PubMed]

Cite as: Valencia D, Pak S, Linares J, Valencia V, Lee C, Markovic J-P, Shah H. Sleep related breathing disorders and neurally mediated syncope (SRBD and NMS). Southwest J Pulm Crit Care. 2019;18(4):76-81. doi: PDF 


Sleep Board Review Question: Restless Legs

Olabimpe Omobomi, MD MPH

Rohit Budhiraja, MD

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Impact of Sleep Duration and Weekend Oversleep on Body Weight and Blood Pressure in Adolescents

*Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA

Asthma and Airways Research Center, University of Arizona College of Medicine, Tucson, AZ USA

Department of Pediatrics, University of Arizona College of Medicine, Tucson, AZ USA

§Department of Medicine, University of Arizona College of Medicine, Tucson, AZ USA

Center for Sleep and Circadian Sciences, University of Arizona Health Sciences Center, Tucson, AZ USA

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