Diagnosis and Treatment of Sleep Apnea in Shelter Residents
Phase: NA
Conditions: Sleep Apnea, Sleep Disorder, Sleep Deprivation, Sleep Disturbance
Sponsor: University Health Network, Toronto

 
 
 
CLINICAL PROTOCOL 
 
 
Diagnosis and treatment of sleep apnea in shelter residents 
 
Azadeh Yadollahi, PhD 
 
 
 University Health Network 
 Toronto Rehabilitation Centre 
 
 
 
 
Protocol Version 11 (Amendment)  
Date (Day/ Month/Year): 
10/06/2024 
 
 

 
 
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Contents 
Protocol Summary ........................................................................................................................................ 4 
Title ........................................................................................................................................................... 4 
Sample Size ............................................................................................................................................... 4 
Study Population ....................................................................................................................................... 4 
Accrual period ........................................................................................................................................... 4 
Study Design ............................................................................................................................................. 4 
Study Duration .......................................................................................................................................... 5 
Primary Objectives .................................................................................................................................... 5 
General Information ...................................................................................................................................... 5 
Introduction and Background ....................................................................................................................... 6 
Rationale ....................................................................................................................................................... 6 
Study Objectives and Hypothesis ................................................................................................................. 7 
Primary Objectives .................................................................................................................................... 7 
Hypotheses ................................................................................................................................................ 7 
Study Design ................................................................................................................................................. 8 
Measurements ........................................................................................................................................... 8 
Questionnaires ....................................................................................................................................... 8 
Sleep Apnea Screening ......................................................................................................................... 8 
Sleep Apnea Diagnosis ......................................................................................................................... 8 
Sleep Apnea Treatment ......................................................................................................................... 9 
Data Collection Protocol ........................................................................................................................... 9 
Patient recruitment ................................................................................................................................ 9 
Sleep Apnea Screening (Figure 2) ........................................................................................................ 9 
Sleep Apnea Diagnosis (Figure 2) ...................................................................................................... 10 
Sleep Apnea Treatment (Figure 3) ...................................................................................................... 11 
Data Analysis and Expected Results ........................................................................................................... 12 
Sleep Apnea Diagnosis (Primary Outcome 1) ........................................................................................ 12 
Sleep Apnea Treatment (Primary Outcome 2) ........................................................................................ 13 
Selection of Participants ............................................................................................................................. 14 
Privacy of Participants ................................................................................................................................ 14 

 
 
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Management of Adverse Events ................................................................................................................. 14 
Infection Control Measures ......................................................................................................................... 15 
Direct Access to Source Data/Documents .................................................................................................. 15 
Quality Control and Quality Assurance Procedures ................................................................................... 15 
Ethics .......................................................................................................................................................... 15 
Consent Process ...................................................................................................................................... 15 
Data Handling and Record Keeping ........................................................................................................... 16 
Publication Policy ................................................................................................................................... 16 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
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List of Abbreviations/ Terminology 
 
Apnea-Hypopnea Index (AHI) 
 
Asthma Control Test (ACT)  
 
Auto-titrating 
Positive 
Airway 
Pressure (APAP) 
 
Beck Depression Inventory (BDI)  
 
Epworth Sleepiness Score (ESS)  
 
Functional 
Outcome 
of 
Sleep 
Questionnaire (FOSQ) 
 
Chalder Fatigue Scale (CFQ)  
 
Canadian Agency for Drugs and 
Technologies in Health (CADTH) 
 
Continuous 
Positive 
Airway 
Pressure (CPAP) 
 
Central Sleep Apnea (CSA) 
 
Health 
Information 
Technology 
Usability Evaluation Scale (Health-
ITUES) 
 
 
Health Information Technology 
Usability 
Evaluation 
Scale 
(Health-ITUES) Questionnaire 
 
Health Insurance Portability and 
Protection ACT (HIPPA).  
 
Infection 
Prevention 
and 
Control (IPAC) 
 
Inner 
City 
Health 
Associate 
(ICHA) 
 
Mandibular Advancement Device 
(MAD) 
 
Oral Health Impact Profile - 14 
(OHIP-14)  
 
Oxygen Desaturation Index (ODI) 
 
Obstructive Sleep Apnea (OSA) 
 
Personal Information Protection 
and Electronic Documents Act 
(PIPEDA) 
 
 
Rapid Eye Movement (REM) 
 
Research Ethics Board  (REB) 
 
Socio Economic status (SES) 
 
University Health Network (UHN) 
 
Protocol Summary 
Title 
Diagnosis and treatment of sleep apnea in shelter residents 
 Sample Size 
        n = 400 
 Study Population 
Adults experiencing homelessness and living in shelters (shelter residents) 
Accrual period 
5 year 
Study Design 
This longitudinal study will collect data to assess the prevalence of sleep apnea in people living in 
shelters (shelter residents) and to investigate the effects of sleep apnea treatment on their quality of life. 
We will also collect information about the major complications of sleep apnea including cardiovascular 
disorders, respiratory diseases, and dental diseases. Several short questionnaires will be provided to the 
shelter residents, to assess sleep apnea-related quality of life, daytime sleepiness, and oral health, which 
is important for our proposed sleep apnea treatment based on oral appliances. A general survey will be 

 
 
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provided to shelter employees, shelter residents and healthcare providers to assess the barriers of the 
use of portable polysomnography and sleep apnea treatment options in people experiencing 
homelessness. 
Eligible participants who screen positive for sleep apnea will be referred to the University Health 
Network (UHN) Centre for Sleep Health and Research for clinical diagnosis of sleep apnea and 
treatment. Definitive diagnosis would involve a complete medical history and examination, combined 
with an overnight polysomnography test. Treatment will be provided based on physician’s 
recommendation and patient’s preference, including continuous positive airway pressure (CPAP) or an 
oral appliance made specifically for the participant.  
 Study Duration 
5 year 
Primary Objectives 
1. Assess the prevalence of sleep apnea in shelter residents  
2. Evaluate the effects of preferred sleep apnea treatment on quality of life of the people experiencing 
homelessness 
General Information 
 
Protocol title 
Diagnosis and treatment of sleep apnea in shelter 
residents 
Principal Investigator: 
Azadeh Yadollahi, PhD 
Co-Investigator: 
Tina Meisami, BSc., DDS, FRCD(C), DIP OMFS 
Valeria Rac, MD, PhD 
Owen Lyons, MB BCH BAO, MRCPI 
Mandeep Singh, MMBS, MD, MSc, FRCPC 
Andrew Boozary, MD, PhD 
 
Fellows/Residents: 
Research fellows of Azadeh Yadollahi, and Co-
Investigators 
Michalina Seidl, Registered social worker 
Study site(s) 
1. Dixon Hall Housing Services department 
Add: 58 Sumach Street, Toronto, ON 
M5A 3J7 Tel: 416-863-0499 
2. Fred Victor 
Add: 800 Bay Street, Suite 402, Toronto, 
ON M5S 3A9 Tel: 416-482-4103 

 
 
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Introduction and Background 
People experiencing homelessness are at higher risk of getting infected, transmitting disease, and having 
poor health outcomes [1]. Access to medical care, even within a system of universal health insurance like 
the one in Canada, is decreased among people experiencing homelessness [2]. Even prior to the COVID-
19 pandemic, the care-pathways of this populations were often characterized by a state of disconnected 
emergency room visits and hospitalization, rather than longer-term disease management [3]. While shelters 
offer basic necessities of living to this population, these community residences are not equipped to monitor 
the health status of their residents. 
Compared to the general population, people experiencing homelessness sleep less, have excessive daytime 
fatigue, and greater use of substance to fall asleep at night or stay awake during the day. A common sleep 
problem is sleep apnea, which is characterized by repeated episodes of breathing cessation during sleep [4]. 
Sleep apnea is associated with the conditions that account for the leading causes of mortality in adults: 
hypertension [5], obstructive lung disease [6, 7], cardiovascular [8],[9] and cerebrovascular [10] diseases. 
What is known is that the prevalence of chronic diseases among the people experiencing homelessness is 
significantly greater than the general population, and likely, sleep apnea is no expectation [11-13]. 
However, there is no study on the prevalence of sleep apnea in people experiencing homelessness and 
observations suggest very low rates of treatment.  
Also, individual, systemic, and environmental barriers in people experiencing homelessness lead to a higher 
rate of underdiagnosed and untreated sleep apnea. For example: i) care providers may consider sleep apnea 
less crucial than other challenges e.g. unstable housing or poverty. In contrary, high prevalence of chronic 
disorders and socioeconomic disadvantages should emphasize the importance of treating sleep apnea as a 
modifiable barrier to engage in daily activities e.g. work. ii) To be covered by health insurance (e.g. in 
Ontario), sleep apnea diagnosis should be done in a sleep laboratory which is challenging for people 
experiencing homelessness with family/childcare responsibilities. iii) Even if diagnosed, sleep apnea is hard 
to be treated in the people experiencing homelessness, because treatments such as CPAP devices are bulky, 
hard to store or transport, may be stolen, and need electricity which add to barriers. Alternative treatments 
such as mandibular advancement devices are not covered by health insurance and present a financial barrier. 
Unfortunately, all-cause mortality is 5-10 times higher in people experiencing homelessness than the 
general population, and sleep apnea remains a potential silent cause of morbidity and mortality, emergency 
department visits, poor mental health, and low quality of life in people experiencing homelessness. 
Our goal is to diagnose and treat sleep apnea in marginalized people living in shelters and to examine 
the effect of patient-centered sleep apnea treatment on their quality of life. 
Rationale 
Previous studies have focused on chronic health conditions of people experiencing homelessness related to 
asthma, cardiology, and respiratory diseases, as well as the morbidity of overdose- and cardiology-related 
diseases [11-17]. But there is no literature on the prevalence of sleep apnea in the people experiencing 
homelessness. From past studies, chronic diseases have been shown to be more prevalent in the people 
experiencing homelessness versus the general population, with a particular emphasis on a high prevalence 

 
 
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of asthma and hypertension in the people experiencing homelessness. There was an average of 21.4% 
(range, 17.1%-24%) prevalence of asthma in the people experiencing homelessness from three North 
American studies and an average of 16.35% (range, 15.6%-17.1%) prevalence of hypertension in the people 
experiencing homelessness from two North American studies [11-13]. In comparison with the prevalence 
of asthma and hypertension in the general U.S. population, 11.5% and 7.4% respectfully, there is a 
significantly higher prevalence of both asthma and hypertension in the people experiencing homelessness 
[12].  
There is already a well-established connection between the prevalence of sleep apnea in patients who have 
asthma and/or hypertension [18-21]. Previous studies have shown that 22%-55% of their sample population, 
having a previous diagnosis of hypertension, also had undiagnosed obstructive sleep apnea [9, 22, 23]. The 
number of patients with undiagnosed obstructive sleep apnea is even higher for resistant hypertension, with 
71%-81% of patients having undiagnosed obstructive sleep apnea [9, 22-24]. Similar results are true for 
patients with pre-existing asthma. One study found the prevalence of obstructive sleep apnea to be 88%, 
58%, and 31% in patients with severe asthma, moderate asthma, and no asthma, respectfully [25]. 
Meanwhile, another study found a 57.3% prevalence of obstructive sleep apnea in patients with a diagnosis 
of asthma and suspected obstructive sleep apnea [7]. 
Furthermore, there is an emerging link in the health sciences literature between socioeconomic status (SES) 
and health [26]. A systematic review of the literature, encompassing 17 studies from 1995-2016, found a 
significant association between SES status indices and obstructive sleep apnea in data gathered from around 
the world [27]. The authors noted that a definite health gradient could be observed from the few studies that 
analyzed the association between obstructive sleep apnea and individual SES indices [27]. Also, there are 
some literature shows the SES indices can be associated with the central sleep apnea (CSA) [28, 29].  
Sleep apnea is already a highly undiagnosed condition in the general population [30, 31] and contributes to 
many other chronic health conditions [32-35]. Given the strong association of chronic cardio-respiratory 
disorders with sleep apnea, and the above average prevalence of these disorders in this population, it is 
reasonable to infer that there might also be a high prevalence of undiagnosed sleep apnea among the people 
experiencing homelessness. 
Study Objectives and Hypothesis 
Primary Objectives 
1. To assess the prevalence of sleep apnea in shelter residents. 
2. To evaluate the effects of preferred sleep apnea treatment on quality of life of the people 
experiencing homelessness 
Hypotheses 
1. The prevalence of sleep apnea in the people experiencing homelessness is more than 30%.  
2. Treating sleep apnea in shelter residents will improve their quality of life.  

 
 
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 Study Design 
 
Measurements 
Questionnaires 
The following questionnaires will be provided to the participants to assess their sleep related 
quality of life and health. 
● Participant Demographics questionnaire 
● STOP-Bang [36-40],  
● Insomnia severity index [41],  
● Epworth sleepiness score (ESS) [42],  
● Functional outcome of Sleep Questionnaire (FOSQ-10) [43, 44],  
● Beck Depression Inventory (BDI) [45] 
● Chalder Fatigue Scale (CFQ) [46] 
● Health Information Technology Usability Evaluation Scale (Health-ITUES) 
Questionnaire [47]  
● Oral Health Impact Profile - 14 (OHIP-14) [48]  
● Asthma Control Test (ACT) [49]  
● Primary care post-traumatic stress disorder (PTSD) screen (PC-PTSD-5) [50] 
● A survey to help identify barriers to treatment in the people experiencing homelessness 
(General Survey)  
Sleep Apnea Screening  
For another initial risk assessment, individuals are asked to complete a video-based task on a 
smartphone application developed by the Dr. Azadeh Yadollahi’s research fellows. The task 
includes recording a video which asks the users to say the vowels loudly and clearly. After 
finishing the task, the application will process the facial landmarks from each frame of the video 
and analyze the speech of the individuals in parallel and mix them to feed a pre-trained neural 
network in order to assess the risk of sleep apnea. Also, the participants are asked to complete the 
list of previous questionnaires with the help of research assistant. The result of the application 
will be combined with the questionnaires for the final risk assessment.  
Sleep Apnea Diagnosis 
The Prodigy 2 (Figure 1): is a portable polysomnography device to assess sleep 
apnea in individuals at risk of sleep apnea. The Prodigy 2 has Health Canada 
Approval for home sleep study. The system is small, easy to use, and can be setup 
by a research technician at the shelter. Prodigy 2 measures thoraco-abdominal 
motion, nasal airflow, oxyhemoglobin saturation (SpO2), cardiac function with 
electrocardiogram and leg movement. The main advantage of Prodigy 2 to other 
portable devices is that it has a simple headband to record forehead 
electroencephalogram to detect rapid eye movement (REM) and non-REM sleep 
stages. After processing Prodigy 2 signals, an apnea-hypopnea index (AHI) will be 
Figure 1: The Prodigy   

 
 
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calculated for each participant based on the number of respiratory events (apneas or hypopneas) 
per hour of sleep [51]. We will measure AHI, REM AHI, non-REM AHI, AHI in different body 
postures, snoring duration, arousal index, sleep time with SpO2<90%, oxygen desaturation index 
(ODI), and the sleep efficiency.  
Sleep Apnea Treatment 
Individuals who are diagnosed with sleep apnea, and are deemed eligible for treatment, will 
receive a treatment option based on Canadian Agency for Drugs and Technologies in Health 
(CADTH), physician recommendations, and the participant’s preferences. In this study, auto-
titrating positive airway pressure (Auto-CPAP) and Mandibular advancement device (MAD) will 
be the main modalities of treatment.  
Auto-titrating positive airway pressure (Auto-CPAP or APAP): is a common variation of CPAP 
for sleep apnea treatment. Instead of delivering a fixed pressure, Auto-CPAP automatically 
delivers various pressures depending on the severity of pharyngeal airway collapse. Compared to 
CPAP, Auto-CPAP can be used without the need for an in-laboratory titration to determine the 
optimum air pressure. Therefore, it saves time and costs.  
Mandibular advancement device (MAD): is an alternative treatment for sleep apnea. Patients who 
refuse to or are intolerant of APAP or patients who prefer to have MAD will be referred to Dr. 
Tina Meisami (Co-PI, Oral & Maxillofacial Surgeon). Custom made titratable oral appliances are 
the most effective and comfortable appliances available. MAD reduces sleep apnea symptoms by 
advancing the mandible and the tongue forward, decreasing upper airway collapsibility, and 
increasing oropharyngeal space to alleviate the airway obstructions. The degree to which the 
mandible must be advanced is specific to each patient. Dr. Meisami will prescribe, fit and titrate a 
custom made MAD for every patient. All patients would start MAD treatment at 50% of the 
maximum protrusion of the mandible. Then, their sleep apnea will be retested with the Prodigy 
and MAD will be further advanced if needed.  
 
Data Collection Protocol 
Patient recruitment 
Two research assistant with strong knowledge of anti-oppressive, trauma-informed, and patient-
centered care framework, will be the designated persons to contact shelters to establish a trusting 
and relatable relationship between the research team and the research participants. The research 
assistants will also conduct surveys. A poster specifying the nature of the study will also be 
designed and provided to shelters in and around the Greater Toronto Area.  
Sleep Apnea Screening (Figure 3) 
A trained research assistant with expertise in sleep assessment and a registered social worker with 
experience in shelter residents will go to the shelter to perform the screening phase of study. For 
individuals that agree to participate in the study, research personnel will obtain a signed copy of 
the study consent form (Consent Form A which relates to screening and diagnosis of sleep 
apnea). Participants will complete eleven questionnaires: Stop-Bang, Insomnia severity index, 

 
 
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Epworth sleepiness score (ESS), quality of life (FOSQ-10), Beck Depression Inventory (BDI), 
Chalder Fatigue Scale (CFQ), primary care post-traumatic stress disorder (PTSD) scale (PC-
PTSD-5), Asthma control questionnaire (ACQ), OHIP-14, and Participant demographics. The RA 
will help the participants complete the questionnaires (~one and a half hours in total). At the end, 
the research assistant help the participant use the screening mobile application. 
If the participant consents to complete the in-shelter sleep apnea diagnosis with in-shelter PSG 
devices, research assistants will schedule the date of study. For the in-shelter diagnosis, the 
research assistants will go to the shelter around 8PM and measure the participant’s weight, height, 
neck, hip and waist circumferences, and blood pressure (Omron 3 inflatable cuff). Afterwards, 
research assistants set up the portable polysomnography (Prodigy 2, Figure 1), based on 
participant’s preference. The next day at 7AM, the research assistant will return to the shelter to 
measure blood pressure and collect the measurement devices. Participants will fill Health-ITUES 
questionnaire in the morning. 
In case of COVID that we cannot perform the study in person, the same protocol will be followed 
through Microsoft Teams (MS Teams). The research assistants will present the questionnaires to 
the participants through REDCap and help the participant to complete the questionnaire. The 
research assistants will guide the participants to use the sleep screening mobile application. The 
research assistants will guide the participants through MS Team to measure weight, height, neck, 
hip and waist circumferences, and blood pressure (Omron 3 inflatable cuff), and show the 
participants how to set up the portable polysomnography (Prodigy 2, Figure 1), based on 
participant’s preference. The next day at 7AM, the research assistant will guide the participants 
(through MS Team) to measure blood pressure, remove the measurement devices, complete 
Health-ITUES questionnaire and put the measurement devices in safe locker in shelter which is 
assigned for this purpose. 
 
Sleep Apnea Diagnosis (Figure 3) 
Individuals with moderate to severe sleep apnea score on the questionnaires will be asked to 
complete the second diagnosis phase. Based on the symptoms and clinical conditions, the 
physician will discuss the referral with individuals to the sleep physicians at UHN for definitive 
diagnosis based on overnight in-lab polysomnography (second diagnosis phase). If the participant 
has already been connected to a family physician, the research assistant will provide them with 
the printed referral form to ask their physician to complete and fax it to the sleep clinic. If the 
participant does not have a corresponding family physician, the physician at Inner City Health 
Associate (ICHA) clinic will complete the referral form and fax it to the sleep clinic. 
The participants will attend a clinical sleep apnea diagnosis at the UHN Centre for Sleep Health 
and Research, which involves getting medical history in combination with an overnight 

 
 
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polysomnography test. Patients who are diagnosed with obstructive sleep apnea will be offered 
treatment with APAP or MAD at the UHN Centre for Sleep Health and Research. 
Sleep Apnea Treatment (Figure 4) 
Patients who are diagnosed with sleep apnea will be recruited for six months of sleep apnea 
treatment. A sleep physician (Co-Investigators: Drs. M. Singh, O. Lyons), will analyze the 
polysomnography report and patient’s symptoms to diagnose individuals with sleep apnea. The 
physicians will use a decision aid [54] to better match sleep apnea treatment with patient 
preference, which results in greater adherence and greater health outcomes [55]. Based on the 
decision aid, patient preference, and CADTH recommendations, the sleep physicians will 
recommend the participant to use Auto-CPAP or MAD for six months. For Auto-CPAP, a trained 
sleep technician will select the optimum mask size for the patients, train them on how to use the 
Auto-CPAP, and provide them with the Auto-CPAP. For MAD, the participant will be referred to 
an Oral and Maxillofacial Surgeon (Dr. T. Meisami, Co-PI) to treat and titrate with MAD for 
optimal disease control. The patient will later receive a customized MAD for treatment. Patients 
will use their Auto-CPAP or MAD for 6 months. Before treatment, and at 3 months and 6 months 
after treatment, participant’s weight and blood pressure will be measured and they will fill 
insomnia severity index, ESS, FOSQ, BDI, CFQ, PC-PTSD-5, Health-ITUES questionnaires, and 
the general survey. Also, at these intervals (3, 6 months after starting the treatment) the 
participants are asked to complete the video task on the smartphone which was used at the sleep 
apnea screening stage. After 3 and 6 months of starting the treatment, the participants will also be 
asked about hospitalization and emergency department visits. 
Figure 3: Schematic of diagnosis phase (Protocol A) 
 
Assessment of Eligibility
Full Polysomnography
8PM
9PM
7 AM
Experiment night 2: Sleep apnea diagnosis (at Clinical sleep lab)
Set up for polysomnography
Technology 
questionnaire
Assessment by Inner City Health Associates family 
physician
OR 
Participant’s family physician
Protocol A
Polysomnography 
Experiment night 1: Sleep apnea diagnosis (at shelter)
Anthropometric measurement, 
Blood Pressure
Blood pressure
8PM
9PM
7 AM
Sleep apnea screening (at shelter)
Consent
Questionnaire
Smartphone application
1.5 hr
(Prodigy 2)
Stage 1
Stage 2
Stage 3

 
 
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To increase adherence to treatment, once a week, a research assistant will contact the individuals 
by phone to solve the potential technical challenges with the APAP or MAD.  
Diagnostic tests using the Prodigy 2 will be repeated after 3 and 6 months to assess sleep apnea 
severity. The treatment information will be stored on the study database on a secure driver within 
the UHN server system. The protocol of treatment phase is shown in Figure 4. 
 
Data Analysis and Expected Results 
Sleep Apnea Diagnosis (Primary Outcome 1) 
The primary outcome of the study is to estimate the prevalence of sleep apnea in the people 
experiencing homelessness (primary objective 1). Polysomnography data will be scored by a 
qualified technician using standard techniques and criteria for scoring sleep stages, events, and 
arousals [14, 15]. Pulse oximetry data will also be analyzed to extract oxygen desaturation index 
(ODI). Oxygen desaturation index is defined as hourly average number of desaturation episodes, 
which is characterized by oxygen desaturation of 4% or more compared to the average oxygen 
saturation in the preceding 120 seconds which lasts more than 10 seconds [57]. Sleep apnea will 
be diagnosed and its severity will be assessed based on AHI and ODI. Individuals with AHI≥15 
or REM-AHI≥15 or ODI≥5 will be considered as sleep apnea. 
To assess the effectiveness of home-based technologies to diagnose sleep apnea in the people 
experiencing homelessness, we will follow signal processing techniques from previous studies to 
analyze the signals [52]. The Prodigy signals will be annotated automatically using Michele 
Scoring System. The system has the ability to preprocess the raw signals and extract 
distinguishable parameters which are conventionally extracted by human expert [58, 59]. Pulse 
oximetry data will also be analyzed to extract ODI. The AHI estimation of the Prodigy will be 
Figure 4: Schematic of treatment phase (Protocol B)  
Protocol B
Assessment by Sleep physician
Referral to Oral and maxillofacial surgeon
MAD
Auto-CPAP
Use of treatment
Treatment Phase
Questionnaires,
Smart phone application,
Weight measurement,
Blood Pressure
Day 1
Month 3
Month 6
Questionnaires, 
Smart phone application
Weight measurement, Blood Pressure, 
Polysomnography (Prodigy 2)
Use of treatment 
Weekly follow up
Consent
Weekly follow up
Questionnaires, 
Smart phone application
Weight measurement, Blood Pressure, 
Polysomnography (Prodigy 2)

 
 
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compared with those from polysomnography results to assess the effectiveness of the at-shelter 
sleep study. 
Statistical models: We will report the OSA prevalence rate within shelter residents, overall and 
by sex, type and severity. Using regression models, we will estimate the relationship between 
quality of life (FOSQ) measured on a continuous sale and severity of OSA among people with 
OSA, adjusted for sex, age, BMI, waist and neck circumference, ethnicity, sexual orientation, 
gender identity, menopausal status, comorbidities (hypertension, type 2 diabetes, BDI, PC-PTSD-
5), and sleepiness. We will also assess the relationship between fatigue and OSA severity, 
adjusting for the same confounders. We will report obstructive AHI, central AHI, REM-AHI, 
non-REM AHI, AHI in various body postures, sleep time with SpO2<90%, snoring duration, 
sleep efficiency, and alternative metrics[60] including apnea-hypopnea event duration, arousal 
intensity,[61] odds ratio product,[62] hypoxic burden,[63-66] and cardiopulmonary coupling, 
overall and by sex.[67] Using in-shelter polysomnography as the gold standard, we will report the 
sensitivity and specificity of the Stop-Bang questionnaire to identify participants with AHI≥5, 
AHI≥15, AHI≥30, REM-AHI≥15, or ODI≥5. 
Expected results: The prevalence of sleep apnea in shelter residents will be >35%. OSA severity 
is a strong predictor of functional quality of life and fatigue. OSA phenotypes, such as REM vs. 
non-REM AHI, event duration, and sleep fragmentation will differ based on sex. The specificity 
of Stop-Bang to detect residents with AHI≥15 will be lower than its specificity in the general 
population (~30%).[36, 38]  
Sleep Apnea Treatment (Primary Outcome 2) 
The primary outcomes will be change in quality of life (FOSQ score)[44] and systolic and 
diastolic blood pressure, and adherence to treatment at three and six months. Adherence to 
treatment is measured as the number of hours/night and nights/week that participants use 
treatment. Auto-CPAP devices keep track of the usage and this data can be automatically 
extracted.  
Statistical Analysis: We will use repeated measures ANOVA to assess the changes in the FOSQ-
10 score from baseline to 3 and 6 months after treatment using each person as their own control. 
Regression models for FOSQ at 3 and 6 months will adjust for factors known to contribute to 
changes in the FOSQ global score, including baseline FOSQ-10 score, anthropometrics, BMI, 
sexual orientation, gender identity, AHI, age, treatment adherence, baseline blood pressure, and 
comorbidities (type 2 diabetes, hypertension, depression and PTSD scores). We will assess 
changes in systolic and diastolic blood measure using similar models in those with hypertension. 
We will report adherence to treatment. The usability of sleep apnea treatment will be assessed by 
a Health Information Technology Usability Evaluation Scale (Health-ITUES)[47] which is 
modified for our study. 
Expected results: After treatment, FOSQ scores will increase (better quality of life) and systolic 
and diastolic blood pressure in patients with hypertension will decrease. Adherence to MAD and 
CPAP treatment will be ≥70%, which is similar to the adherence in the general population.[68-
76]    

 
 
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Selection of Participants 
Participants will be referred by a shelter manager, case worker, or another shelter employee from one of 
the shelters in and around the Greater Toronto Area. The eligibility criteria for participants will include 
residing in a shelter at the time of recruitment, and being >18 years old. Participants with allergies to 
medical tape will be excluded from the study. For treatment protocol, exclusion criteria for mandibular 
advancement treatment will be dental and oral health requiring extensive dental treatment or periodontal 
disease with tooth mobility.  
Shelter setting: The patients and their community are central parts of this research. We have established 
strong partnership with institutes that provide care for experiencing homelessness. 
Dixon Hall: serves more than 10,000 marginalized people in Toronto annually, including at-risk youth, 
women, seniors, adults with physical and health disabilities, people who need housing, individuals 
searching for employment, those with mental health issues, and newly immigrated individuals and their 
families. Dixon Hall’s Housing Services department has been providing shelter services for the homeless 
and vulnerably housed in the city of Toronto for more than two decades. They provide overnight 
accommodation throughout the year to 500 residents through two emergency shelters, two respites and 3 
hotels. Most residents in hotels use the housing service for a long period, average duration of six 
months/year, which provides a robust “living laboratory” for our proposed research.  
Fred Victor: is committed to ending homelessness. Serving communities for over 125 years, Fred Victor 
has grown from a single mission at Queen and Jarvis to a multi-service organization with over 20 
locations across Toronto. In addition to affordable housing, transitional housing, and emergency shelters, 
Fred Victor provides a constellation of supports to help people secure and maintain a safe place to live. 
Furthermore, Fred Victor has provided accommodation to more than 1000 residents through six different 
sites.  
Privacy of Participants 
Patient information will be held in the strictest confidence. All communications with participants will be 
done only by research staff, via phone or secure UHN email address. Participants will be informed of the 
data sharing protocols, as part of informed consent, and all email scripts as well as advertisements will 
include the email disclaimer for sharing personal data. All correspondence involving sharing personal and 
medical information will be handled with strict confidentiality and in accordance to the Personal 
Information Protection and Electronic Documents Act (PIPEDA) and Health Insurance Portability and 
Protection ACT (HIPPA). 
Management of Adverse Events 
To support the participants emotionally, the research assistant will stay affiliated with them throughout their 
involvement in the proposed research. The occurrence of any adverse event in this study is unlikely or 
minimal. However, in case of any adverse event associated with the study that is both serious and 
unexpected, the REB, and federal agency will be promptly reported.  

 
 
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Infection Control Measures 
All the items that will be used in this study will be subject to the regular infection control measures in the 
sleep lab in accordance with UHN Infection Prevention and Control (IPAC) protocols. The electrodes of 
Prodigy 2 will be cleaned and disinfected based on the manufacturer’s protocol.  
 Direct Access to Source Data/Documents 
Only designated research staff will have access to participant consent forms, surveys, and other study 
documents. The sharing of study data and documents will be done by fax where possible, or via secure 
UHN email addresses that are only used for research purposes. Physical copies of study data and documents 
will be stored under lock and key, accessible only by designated research staff. Electronic data and 
documents will be stored on a secure driver within the UHN server system. 
 Quality Control and Quality Assurance Procedures 
Conduct of the study and study data will be reviewed by the principal investigators and other research 
personnel during weekly research meetings. 
 Ethics 
Consent Process 
An important challenge will be to establish trust between participants and the research team. Due to the 
systemic barriers and traumatic healthcare experiences that these individuals may have had in the past, 
we will take a trauma-informed approach to our research. Potential participants will be informed that 
the information collected in the surveys will be for research purposes and that their participation is 
voluntary. For this study, two consent forms (A and B) are used in different stages of the study. Consent 
Form A, related to the sleep apnea screening and diagnosis in shelter residents, while the consent form 
B involves treatment stage of this study. A research assistant familiar with issues of trust and trauma-
informed approach will contact the potential participants. The individuals will receive a brief summary 
of the research project, including: the purpose, the duration, and the procedures involved. The 
individuals will be informed that their regular care will not be affected even if they do not participate, 
or that financial compensation should not coerce them into participating. Individuals will be presented 
with both the reasonable and expected benefits of participation, in addition to any reasonable and 
foreseeable risks or discomforts. During the course of their participation, and in the event of subsequent 
treatment, it will be made known that alternative procedures or treatment options will always be 
presented, should they become available.  
Participants will be assured that their identities will remain confidential and information accessible only 
by designated research personnel. Also, the participants will be informed that they can withdraw from 
the study at any time due to any reason. Participants will be asked to inform the research staff in case 
of withdrawal and the reason, if possible. 

 
 
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 Data Handling and Record Keeping 
Publication Policy 
The findings of this study will be submitted for publication in a peer-reviewed journal and used for 
grant proposals. Participants will not be identifiable in any publications. Study findings will be fed back 
to the shelter community so they can learn about their community. 
 
References 
1. 
Perri, M., N. Dosani, and S.W. Hwang, COVID-19 and people experiencing homelessness: 
challenges and mitigation strategies. CMAJ, 2020. 192(26): p. E716-E719. 
2. 
Hwang, S.W., et al., Universal health insurance and health care access for homeless persons. 
American journal of public health, 2010. 100(8): p. 1454-1461. 
3. 
Coffey, A., et al., Interventions to promote early discharge and avoid inappropriate hospital (re) 
admission: a systematic review. International journal of environmental research and public health, 
2019. 16(14): p. 2457. 
4. 
Peppard, P.E., et al., Increased prevalence of sleep-disordered breathing in adults. Am J 
Epidemiol, 2013. 177(9): p. 1006-14. 
5. 
Mohsenin, V., et al., The effect of gender on the prevalence of hypertension in obstructive sleep 
apnea. Sleep medicine, 2009. 10(7): p. 759-762. 
6. 
Julien, J.Y., et al., Prevalence of obstructive sleep apnea-hypopnea in severe versus moderate 
asthma. J Allergy Clin Immunol, 2009. 124(2): p. 371-6. 
7. 
Madama, D., A. Silva, and M.J. Matos, Overlap syndrome--Asthma and obstructive sleep apnea. 
Rev Port Pneumol (2006), 2016. 22(1): p. 6-10. 
8. 
Wang, X., et al., Obstructive sleep apnea and risk of cardiovascular disease and all-cause 
mortality: a meta-analysis of prospective cohort studies. International journal of cardiology, 
2013. 169(3): p. 207-214. 
9. 
WORSNOP, C.J., et al., The prevalence of obstructive sleep apnea in hypertensives. American 
journal of respiratory and critical care medicine, 1998. 157(1): p. 111-115. 
10. 
Saletu, M., et al., Structural and serum surrogate markers of cerebrovascular disease in 
obstructive sleep apnea (OSA). Journal of neurology, 2006. 253(6): p. 746-752. 
11. 
Nikoo, N., et al., Chronic physical health conditions among homeless. Journal of Health 
Disparities Research and Practice, 2014. 8(1): p. 5. 
12. 
Schanzer, B., et al., Homelessness, health status, and health care use. American Journal of Public 
Health, 2007. 97(3): p. 464-469. 
13. 
Snyder, L.D. and M.D. Eisner, Obstructive lung disease among the urban homeless. Chest, 2004. 
125(5): p. 1719-1725. 
14. 
Baggett, T.P., S.S. Liauw, and S.W. Hwang, Cardiovascular disease and homelessness. Journal 
of the American College of Cardiology, 2018. 71(22): p. 2585-2597. 
15. 
Baggett, T.P., et al., Mortality among homeless adults in Boston: shifts in causes of death over a 
15-year period. JAMA internal medicine, 2013. 173(3): p. 189-195. 
16. 
Kerr, T., et al., Predictors of non-fatal overdose among a cohort of polysubstance-using injection 
drug users. Drug and alcohol dependence, 2007. 87(1): p. 39-45. 
17. 
O'Driscoll, P.T., et al., Predictors of accidental fatal drug overdose among a cohort of injection 
drug users. American Journal of Public Health, 2001. 91(6): p. 984. 
18. 
Nieto, F.J., et al., Association of sleep-disordered breathing, sleep apnea, and hypertension in a 
large community-based study. Jama, 2000. 283(14): p. 1829-1836. 

 
 
Version 12 – June 10, 2024   
Page 17 of 19 
19. 
Wang, D., et al., Central sleep apnea in stable methadone maintenance treatment patients. Chest, 
2005. 128(3): p. 1348-1356. 
20. 
Dumitrascu, R., et al., Sleep apnea in precapillary pulmonary hypertension. Sleep medicine, 
2013. 14(3): p. 247-251. 
21. 
Bradley, T.D. and J.S. Floras, Sleep apnea and heart failure: Part II: central sleep apnea. 
Circulation, 2003. 107(13): p. 1822-1826. 
22. 
Broström, A., et al., Factors associated with undiagnosed obstructive sleep apnoea in 
hypertensive primary care patients. Scandinavian journal of primary health care, 2012. 30(2): p. 
107-113. 
23. 
Ruttanaumpawan, P., et al., Association between refractory hypertension and obstructive sleep 
apnea. Journal of hypertension, 2009. 27(7): p. 1439-1445. 
24. 
Gonçalves, S.C., et al., Obstructive sleep apnea and resistant hypertension: a case-control study. 
Chest, 2007. 132(6): p. 1858-1862. 
25. 
Julien, J.Y., et al., Prevalence of obstructive sleep apnea–hypopnea in severe versus moderate 
asthma. Journal of Allergy and Clinical Immunology, 2009. 124(2): p. 371-376. 
26. 
Hanson, M.D. and E. Chen, Socioeconomic status and health behaviors in adolescence: a review 
of the literature. Journal of behavioral medicine, 2007. 30(3): p. 263. 
27. 
Guglielmi, O., P. Lanteri, and S. Garbarino, Association between socioeconomic status, belonging 
to an ethnic minority and obstructive sleep apnea: a systematic review of the literature. Sleep 
medicine, 2019. 57: p. 100-106. 
28. 
Buckhalt, J.A., Insufficient sleep and the socioeconomic status achievement gap. Child 
Development Perspectives, 2011. 5(1): p. 59-65. 
29. 
Jehan, S., et al., Sleep health disparity: the putative role of race, ethnicity and socioeconomic 
status. Sleep medicine and disorders: international journal, 2018. 2(5): p. 127. 
30. 
Evans, J., et al., Sleep laboratory test referrals in Canada: sleep apnea rapid response survey. 
Can Respir J, 2014. 21(1): p. e4-10. 
31. 
Young, T., et al., Estimation of the clinically diagnosed proportion of sleep apnea syndrome in 
middle-aged men and women. Sleep, 1997. 20(9): p. 705-706. 
32. 
Valham, F., et al., Increased risk of stroke in patients with coronary artery disease and sleep 
apnea: a 10-year follow-up. Circulation, 2008. 118(9): p. 955-60. 
33. 
Yaggi, H.K., et al., Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med, 
2005. 353(19): p. 2034-41. 
34. 
Wang, X., et al., Obstructive sleep apnea and risk of cardiovascular disease and all-cause 
mortality: a meta-analysis of prospective cohort studies. Int J Cardiol, 2013. 169(3): p. 207-14. 
35. 
Sharafkhaneh, A., et al., Association of psychiatric disorders and sleep apnea in a large cohort. 
Sleep, 2005. 28(11): p. 1405-11. 
36. 
Chung, F., H.R. Abdullah, and P. Liao, STOP-Bang Questionnaire: A Practical Approach to 
Screen for Obstructive Sleep Apnea. Chest, 2016. 149(3): p. 631-8. 
37. 
Chung, F., et al., Alternative scoring models of STOP-bang questionnaire improve specificity to 
detect undiagnosed obstructive sleep apnea. J Clin Sleep Med, 2014. 10(9): p. 951-8. 
38. 
Nagappa, M., et al., Validation of the STOP-Bang Questionnaire as a Screening Tool for 
Obstructive Sleep Apnea among Different Populations: A Systematic Review and Meta-Analysis. 
PLoS One, 2015. 10(12): p. e0143697. 
39. 
Nagappa, M., et al., Association of STOP-Bang Questionnaire as a Screening Tool for Sleep 
Apnea and Postoperative Complications: A Systematic Review and Bayesian Meta-analysis of 
Prospective and Retrospective Cohort Studies. Anesth Analg, 2017. 125(4): p. 1301-1308. 
40. 
Nagappa, M., et al., An update on the various practical applications of the STOP-Bang 
questionnaire in anesthesia, surgery, and perioperative medicine. Curr Opin Anaesthesiol, 2017. 
30(1): p. 118-125. 
41. 
Bastien, C.H., A. Vallières, and C.M. Morin, Validation of the Insomnia Severity Index as an 
outcome measure for insomnia research. Sleep medicine, 2001. 2(4): p. 297-307. 

 
 
Version 12 – June 10, 2024   
Page 18 of 19 
42. 
Johns, M.W., A new method for measuring daytime sleepiness: the Epworth sleepiness scale. 
sleep, 1991. 14(6): p. 540-545. 
43. 
Weaver, T.E., et al., An instrument to measure functional status outcomes for disorders of 
excessive sleepiness. Sleep, 1997. 20(10): p. 835-843. 
44. 
Chasens, E.R., S.J. Ratcliffe, and T.E. Weaver, Development of the FOSQ-10: a short version of 
the Functional Outcomes of Sleep Questionnaire. Sleep, 2009. 32(7): p. 915-9. 
45. 
Beck, A.T., R.A. Steer, and G. Brown, Beck depression inventory–II. Psychological Assessment, 
1996. 
46. 
Chalder, T., et al., Development of a fatigue scale. Journal of psychosomatic research, 1993. 
37(2): p. 147-153. 
47. 
Schnall, R., H. Cho, and J. Liu, Health Information Technology Usability Evaluation Scale 
(Health-ITUES) for Usability Assessment of Mobile Health Technology: Validation Study. JMIR 
Mhealth Uhealth, 2018. 6(1): p. e4. 
48. 
Slade, G.D. and A.J. Spencer, Development and evaluation of the oral health impact profile. 
Community dental health, 1994. 11(1): p. 3-11. 
49. 
Juniper, E., et al., Development and validation of a questionnaire to measure asthma control. 
European respiratory journal, 1999. 14(4): p. 902-907. 
50. 
Prins, A., et al., The primary care PTSD screen for DSM-5 (PC-PTSD-5): development and 
evaluation within a veteran primary care sample. Journal of general internal medicine, 2016. 
31(10): p. 1206-1211. 
51. 
Kapur, V.K., 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): p. 479-504. 
52. 
Saha, S., et al., Apnea-hypopnea index (AHI) estimation using breathing Sounds, accelerometer 
and pulse oximeter. 2019, Eur Respiratory Soc. 
53. 
Saha, S., et al., Portable diagnosis of sleep apnea with the validation of individual event 
detection. Sleep medicine, 2020. 69: p. 51-57. 
54. 
Hamoda, M.M., et al. Obstructive Sleep Apnea Treatment Preference Using the Decision Aid 
Tool in Recently Diagnosed, Treatment-Naïve Patients. in Annual meeting of American Thoracic 
Society. 2018. San Diego, CA. 
55. 
Almeida, F.R., et al., Patient preferences and experiences of CPAP and oral appliances for the 
treatment of obstructive sleep apnea: a qualitative analysis. Sleep Breath, 2013. 17(2): p. 659-66. 
56. 
McCallum, J., J. Watson, and J. Globerman, Rapid Response Service. Rapid Response: Peer-
based programs to support antiretroviral adherence, S.B. Rourke and J. Bacon, Editors. 2014, 
Ontario HIV Treatment Network: Toronto, ON. 
57. 
Chung, F., L. Zhou, and P. Liao, Parameters from preoperative overnight oximetry predict 
postoperative adverse events. Minerva anestesiologica, 2014. 80(10): p. 1084. 
58. 
Younes, M., et al., Utility of technologist editing of polysomnography scoring performed by a 
validated automatic system. Annals of the American Thoracic Society, 2015. 12(8): p. 1206-
1218. 
59. 
Younes, M., M. Younes, and E. Giannouli, Accuracy of automatic polysomnography scoring 
using frontal electrodes. Journal of Clinical Sleep Medicine, 2016. 12(5): p. 735-746. 
60. 
Malhotra, A., et al., Metrics of Sleep Apnea Severity: Beyond the AHI. Sleep, 2021. 
61. 
Amatoury, J., et al., Arousal Intensity is a Distinct Pathophysiological Trait in Obstructive Sleep 
Apnea. Sleep, 2016. 39(12): p. 2091-2100. 
62. 
Younes, M., et al., Odds ratio product of sleep EEG as a continuous measure of sleep state. 
Sleep, 2015. 38(4): p. 641-54. 
63. 
Azarbarzin, A., et al., The hypoxic burden of sleep apnoea predicts cardiovascular disease-
related mortality: the Osteoporotic Fractures in Men Study and the Sleep Heart Health Study. 
Eur Heart J, 2019. 40(14): p. 1149-1157. 

 
 
Version 12 – June 10, 2024   
Page 19 of 19 
64. 
Azarbarzin, A., et al., Hypoxic burden captures sleep apnoea-specific nocturnal hypoxaemia. Eur 
Heart J, 2019. 40(35): p. 2989-2990. 
65. 
Azarbarzin, A., et al., The Sleep Apnea-Specific Hypoxic Burden Predicts Incident Heart Failure. 
Chest, 2020. 158(2): p. 739-750. 
66. 
Azarbarzin, A., et al., The hypoxic burden: a novel sleep apnoea severity metric and a predictor 
of cardiovascular mortality-Reply to 'The hypoxic burden: also known as the desaturation 
severity parameter'. Eur Heart J, 2019. 40(35): p. 2994-2995. 
67. 
Thomas, R.J., et al., Prevalent hypertension and stroke in the Sleep Heart Health Study: 
association with an ECG-derived spectrographic marker of cardiopulmonary coupling. Sleep, 
2009. 32(7): p. 897-904. 
68. 
Hwang, D., et al., Effect of telemedicine education and telemonitoring on continuous positive 
airway pressure adherence. The Tele-OSA randomized trial. American journal of respiratory and 
critical care medicine, 2018. 197(1): p. 117-126. 
69. 
Eriksson, E.W., et al., A prospective 10-year follow-up polygraphic study of patients treated with 
a mandibular protruding device. Sleep and Breathing, 2015. 19(1): p. 393-401. 
70. 
Hoffstein, V., Review of oral appliances for treatment of sleep-disordered breathing. Sleep and 
Breathing, 2007. 11(1): p. 1-22. 
71. 
Cistulli, P.A., et al., Short-term CPAP adherence in obstructive sleep apnea: a big data analysis 
using real world data. Sleep medicine, 2019. 59: p. 114. 
72. 
Vanderveken, O.M., et al., Objective measurement of compliance during oral appliance therapy 
for sleep-disordered breathing. Thorax, 2013. 68(1): p. 91-6. 
73. 
Bachour, P., et al., Oral appliance in sleep apnea treatment: respiratory and clinical effects and 
long-term adherence. Sleep Breath, 2016. 20(2): p. 805-12. 
74. 
de Almeida, F.R., et al., Long-term compliance and side effects of oral appliances used for the 
treatment of snoring and obstructive sleep apnea syndrome. J Clin Sleep Med, 2005. 1(2): p. 143-
52. 
75. 
Dissanayake, H.U., et al., Comparative effects of CPAP and mandibular advancement splint 
therapy on blood pressure variability in moderate to severe obstructive sleep apnoea. Sleep Med, 
2021. 80: p. 294-300. 
76. 
Sutherland, K., et al., From CPAP to tailored therapy for obstructive sleep Apnoea. Multidiscip 
Respir Med, 2018. 13: p. 44.