The Impact of Obstructive Sleep Apnoea in Women With Polycystic Ovary Syndrome: A Cross-sectional Study
Conditions: Polycystic Ovary Syndrome, Obstructive Sleep Apnea
Sponsor: University Hospitals Coventry and Warwickshire NHS Trust

 
 
 
 
 
 
 
 
 The impact of Obstructive Sleep Apnoea in women with Polycystic Ovary 
Syndrome: A Cross-Sectional Study 
 
PCOS OSA 
 
 Protocol version 4.0 (01/08/2017) 
 
 
Sponsor: University Hospitals Coventry and Warwickshire NHS Trust 
 
Funder: No funding has been received to conduct this study.  Dr. Hassan Kahal is an NIHR clinical 
lecturer in Diabetes and Endocrinology and 50% of his time is allocated to research and funded by 
NIHR. 
 
IRAS ID: 213996 
 
REC reference: 16/EE/0469 
 
 
Confidentiality statement 
All information contained within this document is regarded as, and must be kept, confidential. No 
part of this document may be disclosed to any Third Party without the written permission of the 
Chief Investigator and/or Sponsor. 
 

 
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1. Title 
1.1 Study Title 
- 
Full Title: The impact of Obstructive Sleep Apnoea in women with Polycystic Ovary 
Syndrome: A Cross-sectional study 
- 
Short title: PCOS OSA 
1.2 Names, roles and contact details 
Chief and Principal Investigator 
  Professor Martin O Weickert (MD, FRCP) 
Role: Oversight of the study. Contributing to study design, writing protocol, and data 
analysis. Ensuring that the study is run according to protocol. 
Warwickshire Institute for the Study of Diabetes, Endocrinology and Metabolism (WISDEM) 
University Hospitals Coventry and Warwickshire NHS Trust 
Clifford Bridge Road, Coventry, CV2 2DX 
Tel: 02476 965972 
Fax: 02476 965964 
Email: martin.weickert@uhcw.nhs.uk 
Co-Investigators 
 Professor Harpal  Randeva (MB ChB, FRCP, PhD) 
Role: Contributing to study design, writing protocol, and data analysis. 
WISDEM Centre 
Warwick Medical School 
University Hospitals Coventry and Warwickshire NHS Trust 
Clifford Bridge Road, Coventry, CV2 2DX 
Tel: 02476 965972 
Fax: 02476 965964 
Email: Harpal.Randeva@warwick.ac.uk 
- 
Dr. Hassan Kahal (MD, MRCP, PhD) 
NIHR Clinical Lecturer in Diabetes and Endocrinology 
Role: Study design, writing protocol, data collection and analysis, and reporting back to the 
Principle Investigator. 
WISDEM Centre 
Warwick Medical School 
University of Warwick 
Email: h.kahal@warwick.ac.uk 
 
 

 
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- 
Dr. Ioannis Kyrou (MD, PhD) 
Clinical Lecturer in Metabolic Medicine, Diabetes and Endocrinology  
Role: Contributing to study design, writing protocol and data analysis. 
WISDEM Centre 
University Hospitals Coventry and Warwickshire NHS Trust 
Email: Ioannis.kyrou@uhcw.nhs.uk 
- 
Dr. George Dimitriadis (MD) 
Clinical Research Fellow in Diabetes and Endocrinology 
Role: Contributing to study design, writing protocol, data collection and analysis. 
WISDEM Centre 
University Hospitals Coventry and Warwickshire NHS Trust 
Email: G.Dimitriadis@warwick.ac.uk 
- 
Dr. Eleni Magdalini Kyritsi (MD, PhD) 
Clinical Fellow in Endocrinology 
Role: Contributing to writing protocol, data collection and analysis. 
WISDEM Centre 
University Hospitals Coventry and Warwickshire NHS Trust 
Email: Elena.kyritsi@uhcw.nhs.uk;  madeleine.2007@homail.com  
- 
Dr. Thomas M Barber (MRCP, PhD) 
Associate Professor in Clinical Endocrinology and Honorary Consultant Endocrinologist 
Role: Providing portable sleep study machines. Contributing to writing protocol, and data 
analysis. 
University of Warwick  
University Hospitals Coventry and Warwickshire NHS Trust 
Email: T.Barber@warwick.ac.uk 
- 
Dr. Abd A Tahrani (MD, MRCP, MMedSci, PhD) 
Clinician Scientist 
Role: Research idea.  Contributing to study design, writing protocol, and data analysis. 
Institute of Metabolism and Systems Research, School of Clinical and Experimental Medicine 
University of Birmingham 
Email: a.a.tahrani@bham.ac.uk 
- 
Dr. Asad Ali (MRCP) 
Consultant Respiratory Physician  
Role: Analysis of sleep studies. Contributing to study design and writing protocol. 
University Hospital Coventry and Warwickshire NHS Trust 
Email: Asad.Ali@uhcw.nhs.uk 

 
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- 
Dr. Peter Kimani (PhD) 
Assistant Professor 
Role: Contributing to power calculation and statistical analysis. 
Statistics and Epidemiology 
Warwick Medical School 
University of Warwick 
Email: Peter.K-U.Kimani@warwick.ac.uk 
Sponsor 
Ceri Jones 
Head of Research, Development & Innovation 
Research, Development & Innovation 
4th Floor Rotunda, ADA40007 
University Hospitals Coventry & Warwickshire 
Clifford Bridge Road 
Walsgrave, Coventry 
CV2 2DX 
Email: Ceri.Jones@uhcw.nhs.uk 
Tel:  02476 965031     
 
 
 
Research site 
WISDEM Centre 
University Hospitals Coventry and Warwickshire NHS Trust 
Clifford Bridge Road 
Coventry  
CV2 2DX 
1.3 Protocol details 
Protocol version 4.0 
Date 01/08/2017 

 
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2. Signatures 
- Prof Martin O Weickert 
Signature: 
 
 
 
Date: 
 
- Prof Harpal Randeva   
Signature: 
 
 
  
Date: 
 
- Dr. Hassan Kahal  
 
Signature: 
 
 
 
Date: 
 
- Dr. Ioannis Kyrou  
 
Signature: 
 
 
  
Date: 
 
- Dr. George Dimitriadis  
Signature: 
 
 
  
Date: 
 
- Dr. Eleni Magdalini Kyritsi  
Signature: 
 
 
  
Date: 
 
- Dr. Thomas M Barber  
Signature: 
 
 
 
Date: 
 
- Dr. Abd A Tahrani  
 
Signature: 
 
 
  
Date: 
 
- Dr. Asad Ali  
 
 
Signature: 
 
 
  
Date: 
 
- Dr. Peter Kimani 
 
Signature: 
 
 
 
Date: 
 
- Ms. Ceri Jones  
 
Signature: 
 
 
 
Date:

 
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3. Contents 
1. Title page……………………………………………………………………………………………………………………………………….2 
2. Signatures page……………………………………………………………………………………………………………………………..5 
3. Contents………………………………………………………………………………………………………………………………………..6 
4. List of Abbreviations……………………………………………………………………………………………………………………..8 
5. Summary……………………………………………………………………………………………………………………………………..10 
6. Background………………………………………………………………………………………………………………………………….11 
 
6.1 Polycystic Ovary Syndrome (PCOS) 
 
6.2 Obstructive Sleep Apnoea (OSA) 
 
6.3 Proposed mechanisms linking OSA to PCOS 
 
6.4 Literature search and review 
 
6.5 Summary of the literature 
 
6.6 Justification for the trial 
7. Hypothesis……………………………………………………………………………………………………………………………………18 
8. Study aims……………………………………………………………………………………………………………………………………18 
9. Study design…………………………………………………………………………………………………………………………………18 
10. Study groups………………………………………………………………………………………………………………………………18 
 
10.1 Source of subjects 
 
10.2 Inclusion criteria 
 
10.3 Exclusion criteria 
 
10.4 Expected number of eligible subjects 
11. Recruitment and choosing participants……………………………………………………………………………………..19 
12. Overview of the study visit(s)…………………………………………………………………………………………………….20 
13. Data……………………………………………………………………………………………………………………………………………21 
 
13.1 Anthropometric measurements 
 
13.2 Urine sample 
 
13.3 Blood sampling 
 
13.4 Reproductive history 
 
13.5 Clinical history 
 
13.6 Quality of life 
 
13.7 Depression and anxiety 
 
13.8 Sleep studies 

 
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14. Statistical considerations……………………………………………………………………………………………………………23 
 
14.1 Sample size calculation 
 
14.2 Statistical analysis 
15. Ethical Considerations…………………………………………………………………………………………………………….…24 
16. Side effects…………………………………………………………………………………………………………………………….….25 
17. Insurance…………………………………………………………………………………………………………………………………..25 
18. Funding……………………………………………………………………………………………………………………………………..25 
19. Public and Patient Involvement…………………………………………………………………………………………………25 
20. Reporting and dissemination……………………………………………………………………………………………………..25 
21. Annual Progress Reports……………………………………………………………………………………………………………25 
22. Data handling and record keeping…………………………………………………………….……………………..………26 
23. Monitoring and Auditing……………………………………………………………………………………………………………26 
24. End of study………………………………….……………………………………………………………………………………………26 
25. References…………………………………………………………………………………………………………………………………27 
26. Appendix…………………………………………………………………………………………………………………………………...31 
 
 

 
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4. List of Abbreviations 
- AHI  
 
 
Apnoea/hypopnoea index 
- AASM  
 
American Academy of Sleep Medicine 
- BMI   
 
Body mass index 
- BP  
 
 
Blood pressure 
- CPAP   
 
Continuous positive airway pressure  
- CRF   
 
Case Report Form 
- DVLA  
 
Driving and Vehicle Licensing Agency 
- ESS  
 
 
Epworth Sleepiness Scale 
- FGS   
 
Ferriman-Gallwey score 
 - FPG   
 
Fasting plasma glucose 
- FSH   
 
Follicular stimulating hormone 
- GnRH   
 
Gonadotropin releasing hormone 
- hCRP   
 
High sensitivity C-reactive protein 
- HAD   
 
Hospital Anxiety and Depression scale 
- HbA1C  
 
Glycated haemoglobin 
- HOMA-IR  
 
Homeostatic model assessment of insulin resistance  
- HRA   
 
Health Related Authority 
- ICSD-3 
 
International Classification of Sleep Disorders 
- IGT  
 
 
Impaired glucose tolerance 
- IR  
 
 
Insulin resistance 
- LH  
 
 
Luteinising hormone 
- MS  
 
 
Metabolic syndrome 
- NAFLD  
 
Non-alcoholic fatty liver disease 
- NC-CAH  
 
Non-classic congenital adrenal hyperplasia 
- NHS   
 
National Health Service 
- OCP   
 
Oral contraceptive pill 
- OSA   
 
Obstructive Sleep Apnoea 
- PCO  
 
Polycystic ovaries 
- PCOS  
 
Polycystic Ovary Syndrome 
- PCOSQ  
 
PCOS health-related quality of life questionnaire 
- PI 
 
 
Principle Investigator 

 
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- PIS  
 
 
Patient information sheet 
- QoL   
 
Quality of life 
- RDI 
 
 
Respiratory Disturbance index 
- SD  
 
 
Standard deviation 
- SDB   
 
Sleep disordered breathing 
- SEM   
 
Standard error of the mean 
- TT  
 
 
Total testosterone 
- UHCW 
 
University Hospital Coventry and Warwickshire NHS Trust 
- WHOQOL-BREF  
World Health Organisation QoL-BREF questionnaire 
- WHR   
 
Waist-to-hip ratio 
- WISDEM  
Warwickshire Institute for the Study of Diabetes, Endocrinology and 
Metabolism 
 

 
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5. Summary 
Background: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of 
reproductive age. PCOS is associated with multiple co-morbidities including obesity, insulin 
resistance, subfertility, impaired quality of life (QoL) and increased risk of type 2 diabetes. 
Obstructive sleep apnoea (OSA) is a common medical condition that is often undiagnosed, 
particularly in women. Obesity is a common risk factor for OSA and PCOS and OSA is associated with 
comorbidities similar to those observed in patients with PCOS such as insulin resistance, increased 
risk of type 2 diabetes, and impaired QoL. Hence it is not surprising that OSA and PCOS might co-
exist.  
However, the impact of OSA in women with PCOS remains unclear and understudied. It is plausible 
that OSA may contribute to the subfertility and impaired QoL observed in women with PCOS by 
increasing insulin resistance, activation of the sympathetic nervous system, disturbing the 
hypothalamic/pituitary/ovarian axis, and contributing to excessive daytime sleepiness and reduced 
mood. 
Hypothesis: Women with PCOS and OSA, compared to women with PCOS only, have more severe 
clinical and biochemical features of PCOS and impaired QoL. 
Study design: Observational cross-sectional study. 
Setting: A secondary care PCOS clinic in the WISDEM Centre, University Hospital Coventry. 
Study outcomes: The primary aim of this study is to examine the relationship between OSA and 
impaired QoL in women with PCOS. Study secondary outcomes are to examine the relationship 
between OSA and the clinical and biochemical features in women with PCOS. 
Methods: 38 women with PCOS will be recruited from the PCOS clinic. Women with increased risk of 
OSA, based on the Berlin questionnaire and the Epworth Sleepiness Scale (ESS), will have home-
based sleep studies performed. They will also be referred to the Respiratory Physician, as part of 
routine NHS care.  
Study participants will be divided based on the results of the Berlin and ESS questionnaires and sleep 
studies into two groups: 1) PCOS low risk OSA: women with normal ESS and normal Berlin 
questionnaire (no sleep studies performed), or women with normal sleep studies; and 2) PCOS OSA: 
women with OSA proven by sleep studies.   
Clinical and biochemical features including reproductive history, depression and anxiety [using the 
Hospital Anxiety and Depression questionnaire (HAD)], and QoL [using the PCOS health-related 
quality of life questionnaire (PCOSQ) and the World Health Organisation QoL-BREF (WHOQOL-BREF) 
questionnaire] will be compared between the two groups. 

 
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6. Background 
Few studies have suggested that obstructive sleep apnoea (OSA) is more common in women with 
polycystic ovary syndrome (PCOS) independent of obesity (Fogel et al. 2001; Vgontzas et al. 2001). It 
has also been suggested that women with PCOS and OSA may show more severe phenotypical and 
metabolic features of PCOS compared to women with PCOS alone and subsequently represent a 
different ‘higher risk’ population (Tasali et al. 2008). However, how much OSA contributes to the 
clinical and metabolic features of PCOS is not yet clear though important, as OSA is treatable.  
6.1 Polycystic Ovary Syndrome 
PCOS is a common disorder with a prevalence of 6 – 15% of women of reproductive age (Azziz et al. 
2004; Knochenhauer et al. 1998; Diamanti-Kandarakis et al. 1999; Asuncion et al. 2000; Fauser et al. 
2012). The Rotterdam criteria (Rotterdam 2004) define PCOS by the presence of two of the following 
three components: hyperandrogenism, oligomenorrhoea /anovulation, and polycystic ovaries on 
ultrasound. Oligomenorrhoea is defined as a mean cycle length > 35 days (usually fewer than nine 
cycles per year), while amenorrhoea is defined as cessation of menses for > 6 months (Broekmans et 
al. 2006). Hirsutism, excess body hair, is a common feature in women with PCOS. Polycystic ovaries 
(PCO) on ultrasound are defined as either 12 or more follicles measuring 2–9 mm in diameter in one 
of the ovaries, or an ovarian volume of >10 cm3 (Rotterdam 2004). The diagnosis requires the 
exclusion of conditions with similar presentation including non-classic congenital adrenal hyperplasia 
(NC-CAH), androgen secreting tumours, Cushing’s syndrome; thyroid disorders and prolactinomas. 
PCOS is also associated with subfertility (West et al. 2014),  obesity (Glueck et al. 2005), insulin 
resistance (IR) (Dunaif et al. 1989), increased risk of developing type 2 diabetes (Moran et al. 2010), 
depression and impaired quality of life (QoL) (Barnard et al. 2007; Hahn et al. 2005; Cinar et al. 
2011). Although multiple cardiovascular risk markers are increased in in women with PCOS, the link 
between PCOS and increased cardiovascular morbidity and mortality remains controversial (Randeva 
et al. 2012). 
6.2 Obstructive Sleep Apnoea 
OSA is a common disorder affecting around 17–26% of men and 9–28% of women (Young et al. 
2002). OSA is characterised by recurrent episodes of partial (hypopnoea) or complete (apnoea) 
upper airway obstructions associated with recurrent oxygen desaturations and cyclical changes in 
heart rate, blood pressure, intra thoracic pressure and sympathetic activity (Tahrani and Ali 2014). In 
addition, it results in changes in sleep architecture such as the loss of deep sleep (stages 3 and 4) 
and/or loss of REM sleep (Tahrani and Ali 2014). Women with OSA seem to have a higher proportion 
of respiratory events in REM sleep compared to men (O'Connor et al. 2000). 
Male gender, obesity and age are major risk factors for OSA (Lee et al. 2008). Large population-based 
studies suggest that OSA prevalence is 1.5 – 3 times higher in men compared to women and this 
gender difference decreases after menopause (Lee et al. 2008). Although the exact mechanisms 
underlying the gender differences in the prevalence of OSA are not clear, it is possible that 
androgens play a role in the pathogenesis of OSA, while progesterone has a protective role. OSA risk 
is also influenced by body fat distribution (Ehrmann 2012); visceral fat appears to be more 
metabolically active and the quantity of visceral fat has been shown to highly correlate with OSA risk 
(Shinohara et al. 1997). Other predisposing factors to OSA include ethnicity, smoking, alcohol, upper 
airway anatomy and genetic factors (Lee et al. 2008).  

 
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Patients with OSA may present with nocturnal symptoms including snoring, witnessed apnoeas, 
choking or gasping, insomnia, nocturia, enuresis, frequent arousals, diaphoresis, and impotence 
(McNicholas 2008). While daytime symptoms may include excessive daytime sleepiness, fatigue, 
memory impairment, morning headaches, and depression (McNicholas 2008). Despite the high 
prevalence of OSA, the condition is frequently unrecognized and undiagnosed (McNicholas 2008) 
particularly in women who may not present with the ‘classic ‘ symptoms of OSA (Lee et al. 2008). 
OSA is associated with increased risk of hypertension (Peppard et al. 2000), cardiovascular disease 
(Arzt et al. 2005; Peker et al. 2002; Marin et al. 2005), mortality (Young et al. 2008; Punjabi et al. 
2009), IR and type 2 diabetes (Wang et al. 2013), road traffic accidents (Tregear et al. 2009), 
depression and impaired QoL (Finn et al. 1998; Akashiba et al. 2002; Engleman and Douglas 2004). 
Continuous positive airway pressure (CPAP) therapy is the treatment of choice for symptomatic OSA 
(Greenstone and Hack 2014). 
6.3 Proposed mechanisms linking OSA to PCOS 
Androgens are thought to play an important role in the pathogenesis of OSA (Kapsimalis and Kryger 
2002) through mechanisms including an increase in upper airway collapsibility (Cistulli et al. 1994), 
and a change in ventilatory chemoreceptors sensitivity and responsiveness (White et al. 1985; Zhou 
et al. 2003). In contrast, progesterone is believed to play a protective role against the development 
of OSA in women (Kapsimalis and Kryger 2002) by reducing upper airway resistance (Driver et al. 
2005), and improving ventilation and increasing ventilator chemoresponsiveness (Zwillich et al. 
1978; Regensteiner et al. 1989). As PCOS is characterised by hyperandrogensim and anovulatory 
cycles, with subsequent higher oestrogen and lower progesterone levels, it is plausible that PCOS 
may lead to the development or worsening of OSA symptoms.  
The pathophysiology of PCOS is complex and not fully understood but genetic susceptibility, 
hyperandrogenism, IR, abnormal gonadotropin releasing hormone (GnRH) secretion, and 
sympathetic overactivity are thought to play a role (Conway et al. 2014; Lansdown and Rees 2012). 
OSA is associated with IR and women with OSA seem to have a high proportion of respiratory events 
during the REM sleep (O'Connor et al. 2000). Sleep is thought to have a significant influence on 
female hormone production (Lee et al. 2014). Sleep deprivation, sleep interruption, and sleep 
disordered breathing have been suggested to influence GnRH, follicular stimulating hormone (FSH) 
and luteinising hormone (LH) pulsatility and may cause menstrual disturbances (Baumgartner et al. 
1993; Hall et al. 2005). OSA is also associated with sympathetic overactivity (Grassi et al. 2005). 
Sympathetic overactivity may contribute to IR, alter ovarian function and cause PCO morphology 
(Lansdown and Rees 2012). Subsequently, OSA may contribute to the development of PCOS or 
worsening of its symptoms. 
6.4 Literature search and review 
One of the first studies to suggest a relationship between PCOS and OSA (Fogel et al. 2001) included 
18 young [age ±standard error of mean (SEM) 31.1 ±1.3 years], overweight and obese [body mass 
index (BMI) 36.9 ±1.3 kg/m2], women with PCOS and 18 age- and BMI-matched controls (age 32.3 
±1.3 years, BMI 36.9 ±1.4 kg/m2). PCOS was defined by chronic oligomenorrhoea (≤6 periods/year) 
along with elevated serum total or biologically available testosterone levels. Control women had 
regular cycles and no evidence of clinical hirsutism or biochemical hyperandrogensim. OSA [defined 
as apnoea/hypopnoea index (AHI) >10 events/hour] was more prevalent in women with PCOS 

 
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(66.67% vs. 16.67%, P<0.05) and AHI strongly correlated with waist-to-hip ratio (WHR), total serum 
testosterone, and unbound testosterone levels. Insulin levels were not reported. Study limitations 
include that the PCOS group had higher WHR compared to controls (0.88 ±0.02 vs. 0.82 ±0.01, 
P<0.01), and this was not adjusted for in the analysis; no information was provided on participants’ 
ethnicities; and small sample size. Although the authors concluded that the high prevalence of OSA 
in PCOS is likely to be secondary to hyperandrogenism (women with PCOS had significantly higher 
testosterone levels than controls), they did not consider the role of other risk factors for OSA 
including WHR, progesterone levels and IR. 
Vgontzas at al. (Vgontzas et al. 2001) compared 53 premenopausal women with PCOS, age 30.4 year 
(range 16 – 45), to 452 controls, age 32.1 year (range 20 – 42). The PCOS group was more 
overweight than controls, BMI 38.7 kg/m2 (range 24.3– 67.7) vs. 26.4 kg/m2 (range 16.1–59.9), 
P<0.01. PCOS was diagnosed if both oligomenorrhoea (˂6 periods/year), and raised total or free 
testosterone were present. All women with PCOS had PCO on ultrasound examination. Control 
subjects were selected through random telephone interviews, and those with symptoms suggestive 
of OSA were oversampled. OSA (defined as AHI ≥10 events/hour plus symptoms) was more common 
in women with PCOS (11.3% vs. 0.4%; P<0.001) even after adjustment for BMI. Differences between 
women with PCOS and sleep disordered breathing (SDB) (n=9), defined as either OSA or upper 
airway resistance syndrome, compared to those with PCOS without SDB (n=44), are summarised in 
Table 1. In a logistic regression analysis, insulin levels and glucose-to-insulin ratio had a stronger 
association with SDB than age, BMI, or testosterone levels. Study limitations include that abdominal 
adiposity was not measured and not adjusted for in the analysis; no information was provided on 
how women with PCOS were selected to take part in the study; women in the control group were 
not screened for PCOS; and no information was provided on ethnicities in either group. In addition, 
the difference in BMI between the PCOS and control groups was very high (12.3 kg/m2) that 
statistical adjustment is unlikely to exclude an effect for obesity on the difference in OSA prevalence 
between the two groups.  
Tasali et al. (Tasali et al. 2008) compared 52 premenopausal women with PCOS [age (±SEM) 29.7 
±0.7 year] to 21 controls (age 30.7 ±1.1 year). Women with PCOS were recruited consecutively from 
the endocrine clinic over a 3.5 year period, while controls were selected through advertisement in 
the community. Sleep complaints or symptoms of OSA were not used as selection criteria for the 
study. PCOS was diagnosed based on the presence of oligo/amenorrhoea and elevated free 
testosterone levels and either infertility, or the presence of clinical hyperandrogensim. The control 
group had a higher proportion of women of African-American or Hispanic descent (86 vs. 62%; P = 
0.054), while the PCOS group was heavier [BMI 39.2 kg/m2 (range 23.2 – 58.8) vs. 36.0 kg/m2 (range 
27.7 – 48.8)]. OSA (defined as AHI ≥5 events/hour) was more prevalent in women with PCOS (56% 
vs. 19%) even after adjustment for BMI and ethnicity (P=0.01).  The authors concluded that OSA is 
highly prevalent in women with PCOS independent of age and BMI. Differences between women 
with PCOS and OSA to those with PCOS without OSA are summarised in Table 1. AHI strongly 
correlated with IR, and impaired glucose tolerance. Study limitations include small study sample; and 
that abdominal adiposity was not measured and not adjusted for in the analysis. In addition, the high 
BMI of study participants, particularly the PCOS group and using two different methods to recruit 
participants (clinic vs. advertisement) raise suspicion of selection bias. The authors concluded that 
women with PCOS and OSA represent a metabolically different population ‘higher risk’ compared to 

 
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those with PCOS without OSA. However, this conclusion is limited by the small study sample and the 
lack of clinical outcomes measured.  
In a retrospective study (Nandalike et al. 2012), 28 adolescent girls with PCOS, [age ±standard 
deviation (SD) 16.7 ±1.9 year and BMI 44.8 ±8.8 kg/m2] were compared to 28 girls without PCOS (age 
17.1 ±1.8 year and BMI 40.2 ±4.7 kg/m2) and 28 boys (age 16.6 ±1.6 year and BMI 38.9 ±6.6 kg/m2). 
BMI Z-scores were similar in the three groups. All study participants had polysomnography 
performed as they had sleep related complaints such as snoring, trouble breathing at night or 
excessive daytime sleepiness. All the girls with PCOS had oligo/amenorrhoea plus clinical or 
biochemical evidence of hyperandrogenism. The female control group had a higher proportion of 
African Americans (46.4%) compared to the male (21.4%) and PCOS (17.9%) groups. A higher 
proportion of girls in the PCOS group (32%) and male control group (25%) had a history of 
adenotonsillectomy, treatment of choice for OSA in children, prior to polysomnography compared to 
the female control group (10.7%). OSA (defined as AHI was > 5 events/hour or apnoea index > 1 
event/hour) was diagnosed in 57% of girls with PCOS, in 14.3% girls without PCOS, and in 75% boys. 
Differences between girls with PCOS and OSA to those with PCOS without OSA are summarised in 
Table 1. Study limitations include small sample size; retrospective design; PCOS was not formally 
excluded in the control group; only adolescents with symptoms suggestive of OSA had 
polysomnography performed; and abdominal adiposity was not measured and adjusted for in the 
analysis. Although there was no statistical difference in BMI Z-scores between the study groups, the 
PCOS group had significantly higher BMI compared to the male and female control groups. In 
addition, while the authors reported that girls with PCOS and OSA had a trend to be more obese 
compared to girls with PCOS without OSA, the exact BMIs for those two subgroups (PCOS +/- OSA) 
were not provided. Subsequently, it is difficult to rule out an effect for BMI, abdominal adiposity or 
ethnicity on OSA prevalence in this study. In addition, the high BMI of study participants, in 
particular the PCOS group; and the fact that more girls in the PCOS group had previous 
adenotonsillectomy performed raise suspicion of selection bias. 
Interestingly, De Sousa et al. (de Sousa et al. 2010) compared 22 adolescent girls with PCOS [age 
(±SD) 15.2 ±1.3 year, BMI 31.7 ±6.2 kg/m2] to 18 normal-weight girls without PCOS (age 15.0 ±0.9 
year, BMI 20.6 ±2.3 kg/m2) and 11 obese girls without PCOS (age 15.0 ±1.0 year, BMI 34.8 ±8.7 
kg/m2).  None of the girls in the PCOS group were found to have OSA. PCOS was diagnosed based on 
the presence of hyperandrogensim and oligomenorrhoea/anovulation. Girls with PCOS were 
recruited from the obesity and endocrine outpatient clinics. Study limitations include small study 
sample, and girls in the control groups were only included if they had a polysomnography that ruled 
out OSA. The authors concluded that PCOS precedes the development of OSA. 
Yang et al. (Yang et al. 2009) compared 18 premenopausal slim [age (±SEM) 29.1 ±1.43 year, BMI 
21.7 ±0.57 kg/m2] women with PCOS to 10 BMI- and age-matched controls (age 31.6 ±3.9 year, BMI 
20.9 ±0.58 kg/m2). None of the participants in either group had an AHI ≥ 5 suggestive of OSA. 
Women with PCOS were recruited from the Obstetrics and Gynaecology clinic. PCOS was diagnosed 
based on the presence of oligomenorrhoea, biochemical hyperandrogensim and PCO on ultrasound. 
The PCOS group had significantly higher testosterone levels, larger waist circumference and WHR 
but there was no difference in homeostatic model assessment of insulin resistance (HOMA-IR). Study 
limitations include small number of participants. 

 
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In another study (Gopal et al. 2002), 23 premenopausal women with PCOS (BMI 42.7 kg/m2, range 
31.4 – 67.0), had polysomnography performed, regardless of symptoms, and sixteen women (69%) 
were found to have OSA. OSA was defined as respiratory distress index (RDI) ≥5 events/hour plus 
symptoms. Women with PCOS were consecutively selected from the Reproductive Endocrinology 
and Gynaecology clinics. There was no correlation between obesity and the severity of OSA. Study 
limitations include small study sample; and no information was provided on study participants’ age, 
ethnicity, abdominal adiposity, testosterone levels, or insulin resistance levels. In addition, the high 
BMI of study participants; and recruiting participants from outpatient clinics raise suspicion of 
selection bias. The authors concluded that obesity is not the only cause of the increased prevalence 
of OSA in women with PCOS. 
Tock et al. (Tock et al. 2014) screened 38 premenopausal women with PCOS [age (±SD) 28.3 ±6.8 
year and BMI 32.9 ±7.7 kg/m2] for OSA (defined as AHI ≥5 events/hour, regardless of symptoms), 
and 12 (32%) were found to have the condition. PCOS was diagnosed based on the Rotterdam 
criteria. Study participants were recruited from the Endocrinology clinic. Women with PCOS and OSA 
compared to those without OSA had higher prevalence of non-alcoholic fatty liver disease (NAFLD) 
(83.3% vs. 26.9%); other differences are summarised in Table 1. After adjusting for obesity in 
multivariate logistic regression, raised free testosterone levels ≥1.07 ng/dL increased the risk of OSA 
in women with PCOS by 8.2 fold. In a subsequent multiple logistic regression analysis, OSA was a 
stronger predictor than BMI and IR for the presence of NAFLD. Study limitations include small study 
sample; and that testosterone was measured by immunoassay rather than tandem mass 
spectrometry. The authors concluded that hyperandrogenism may be a predisposing factor for OSA 
in PCOS. 
In another study (Chatterjee et al. 2014), 50 women with PCOS (BMI 27.1 kg/m2) were screened for 
OSA and 33 (66%) were found to have sleep disordered breathing (SDB). Women with PCOS were 
randomly selected from the gynaecology and reproductive endocrinology clinics. PCOS was 
diagnosed based on the Rotterdam criteria. SDB was defined as an RDI of ≥5 events/hour along with 
symptoms or an RDI of >15 events/hour with or without associated symptoms. Differences between 
women with PCOS and OSA to women with PCOS without OSA are summarised in Table 1. On logistic 
regression analysis which adjusted for BMI, only the associations between fasting plasma glucose 
and diastolic blood pressure with SDB remained significant. Study limitations include that the age of 
study participants was not provided and small study sample. 
Finally, in an interventional study (Tasali et al. 2011) 19 obese women with PCOS and OSA [age 
(±SEM) 31.2 ±1.2 year, BMI 46.4 ±2.4 kg/m2] were treated with CPAP for 8 weeks with subsequent 
improvement in insulin sensitivity (relative increase of nearly 7%), and reduction  in diastolic blood 
pressure (around 2.3mmHg). Day-time and night-time norepinephrine levels also reduced after 
therapy. Study limitations include that the authors only performed ‘per protocol’ analysis including 
only 9 women, and data from 10 participants were excluded from the analysis as their average use 
of CPAP was less than 4 hours per night. In addition, the study did not include a control group. It is 
also not clear if the changes in insulin sensitivity and blood pressured observed in the study will 
translate into meaningful clinical outcomes.  

 
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Study 
Notes 
n 
OSA 
Women with PCOS and OSA compared to women with PCOS without OSA 
 
 
 
Diagnosis 
% 
Weight 
or BMI 
Waist or 
WHR 
IR 
Hyperandrog
enism 
BP 
FPG 
IGT 
MS 
FSH / 
LH 
Clinical 
features 
QoL/ 
Depression 
(Vgontzas 
et al. 2001) 
USA 
53 
AHI ≥10 +  
symptoms 
11–17% 
↑ 
NA 
Insulin ↑* 
Free and TT 
↔ 
NA 
↔ 
NA 
NA 
NA 
NA 
NA 
(Fogel et al. 
2001) 
USA 
18 
AHI >10 
66.8% 
NA 
↑ 
NA 
NA 
NA 
NA 
NA 
NA 
NA 
NA 
NA 
(Gopal et 
al. 2002) 
USA 
23 
RDI ≥5 + 
symptoms 
69.6% 
↔ 
NA 
NA 
NA 
NA 
NA 
NA 
NA 
NA 
NA 
NA 
(Tasali et al. 
2008) 
USA 
52 
AHI ≥5 
55.8% 
↑ 
NA 
HOMA-IR 
↑* 
Free and TT 
↔ 
NA 
↔ 
↑ 
NA 
NA 
NA 
NA 
(Yang et al. 
2009) 
Taiwan, slim 
women 
18 
AHI ≥ 5 
0% 
 
 
 
 
 
 
 
 
 
 
 
(de Sousa 
et al. 2010) 
Germany, 
adolescents 
22 
Not stated 
0% 
 
 
 
 
 
 
 
 
 
 
 
(Nandalike 
et al. 2012) 
USA, 
adolescents, 
retrospective 
28 
AHI > 5 or  
apnoea index 
> 1 
57.2% 
↔ 
NA 
HOMA-IR 
↑ 
Free and TT 
↔ 
↑ 
↔ 
NA 
↑ 
NA 
NA 
NA 
(Tock et al. 
2014) 
Brazil 
38 
AHI ≥5 
31.6% 
↑ 
↑ 
HOMA-IR 
↑ 
Free 
testosterone 
↑* 
NA 
↔ 
↑ 
NA 
NA 
NA 
NA 
(Chatterjee 
et al. 2014) 
India 
50 
RDI ≥5 + 
symptoms or 
RDI >15 
66% 
↑ 
↑ 
HOMA-IR 
↔ 
Free 
testosterone 
↔ 
↑ 
↑* 
NA 
↑ 
NA 
↑ FGS 
NA 
Table 1 Differences between women with PCOS and OSA compared to women with PCOS only in published studies. n, number of participants; OSA, 
obstructive sleep apnoea; PCOS, polycystic ovary syndrome; BMI, body mass index; WHR, waist-hip-ration; IR, insulin resistance; HOMA-IR, homeostatic 
model assessment of insulin resistance; TT, total testosterone; BP, blood pressure; FPG, fasting plasma glucose; IGT, impaired glucose tolerance; MS, 
metabolic syndrome; FSH, follicular stimulating hormone; LH, luteinising hormone; QoL, quality of life; ↑ statistically significant increase; NA, not available; 
↔ equal; FGS, Ferriman-Gallwey score; *adjusted for weight.  

 
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6.5 Summary of the literature 
1. The majority of studies investigating OSA in women with PCOS were conducted in the USA. The 
prevalence of OSA in women with PCOS in the reported studies ranged from 0 – 69% (Median 55.8%, 
Mean 39.8%). The reason for this wide range in OSA prevalence is probably a combination of using 
different cut-offs and different methods to diagnose OSA; small studies sample size; and selection 
bias.  
2. The data available suggest that the risk for OSA in women with PCOS is, as expected, increased 
with age and obesity. However, while it is probable that PCOS precedes the development of OSA, it 
is also possible that OSA precedes and increases the risk of developing PCOS in some women. 
Observational long-term studies are needed to assess how frequent is the development of OSA in 
women with PCOS and vice versa. 
3. It seems plausible that OSA is a marker of severity in PCOS; however, it is difficult to conclude that 
from the studies conducted so far as abdominal adiposity and ethnicity have often not been 
accounted for in these studies. In addition, the relationship between OSA and hyperandrogenism in 
PCOS seems controversial. It is also not known if the presence of OSA in women with PCOS is 
associated with worse clinical outcomes including oligomenorrhoea, hirsutism, subfertility, 
depression, impaired quality of life, type 2 diabetes or cardiovascular disease. Subsequently, well 
conducted observational studies are needed to examine the effects of OSA in women with PCOS. 
4. While one study suggested that CPAP therapy in women with PCOS and OSA improves insulin 
sensitivity and reduces blood pressure, it is not clear if this will translate into long-term meaningful 
clinical outcomes. Interventional, randomised-controlled trials with long-term follow up are needed 
to assess the effect of CPAP therapy on clinical and metabolic function in women with PCOS and 
OSA. 
6.6 Justification for the study 
PCOS and OSA are common conditions that are associated with obesity. PCOS is associated with 
subfertility, depression and anxiety, impaired QoL, increased risk of type 2 diabetes, and high 
prevalence of OSA. Hyperandrogensim and low progesterone levels are commonly seen in women 
with PCOS and may explain the increased prevalence of OSA. OSA is associated with disturbed sleep 
pattern, increased IR, disturbed hypothalamic/pituitary/ovarian axis, and sympathetic overactivity 
and subsequently may lead to a more severe phenotype of PCOS in affected women. Data from 
studies investigating the relationship between OSA and PCOS are limited by small sample size; not 
accounting for important confounders; and being at risk of selection bias. In addition, the effects of 
OSA on clinical outcomes in women with PCOS have not been investigated. Subsequently well 
conducted large observational studies are needed to investigate the relationship between OSA and 
clinical outcomes in women with PCOS. This is particularly important as OSA is a treatable condition. 

 
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7. Hypothesis 
Women with PCOS and OSA, compared to women with PCOS only, have more severe clinical and 
biochemical features of PCOS and impaired QoL. 
8. Study aims 
Primary outcome: 
 
To examine if OSA is associated with impaired QoL in women with PCOS. 
Secondary outcomes: 
 
To assess the relationship between OSA and body composition, hirsutism (modified 
Ferriman-Gallwey score), period cyclicity, reproductive outcomes, insulin resistance (HOMA-
IR), hyperandrogenism, depression and anxiety, FPG, glycated haemoglobin (HbA1C), 
reproductive hormone profile, lipids, and inflammation (high sensitivity C-reactive protein, 
hCRP) in women with PCOS. 
9. Study design  
Observational cross-sectional study 
10. Study groups 
10.1 Source of subjects 
Women with PCOS will be recruited consecutively from the PCOS clinic at the WISDEM centre, 
University Hospital Coventry. In addition, patient information sheet (PIS) and a study invitation letter 
will be sent to women with PCOS who attended the PCOS clinic in the last 12 months. 
10.2 Inclusion criteria 
 
Women with PCOS, defined by the Rotterdam criteria as 2 out of 3: 
1. Oligo/anovulation  
2. Clinical or biochemical evidence of hirsutism  
3. Polycystic ovaries on ultrasound. 
       And the exclusion of other disorders with similar presentation including NC-CAH, androgen 
secreting tumours, Cushing’s syndrome; thyroid disorders and prolactinomas. 
 
Age ≥ 18 years. 
 
Able to provide written consent. 
 
Able to adequately understand English. 
 
Patients with unknown diagnosis of OSA, or who were investigated in the past and either 
found not to have OSA, or found to have OSA and are not on CPAP therapy.    
10.3 Exclusion criteria 
 
Pregnancy or breastfeeding women.  
 
Patients who are unable to give consent. 
 
Patients known to have OSA treated with CPAP. 

 
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 
Anyone under the age of 18 years. 
 
Unable to adequately understand or speak English. 
10.4 Expected number of eligible subjects 
In the PCOS clinic we usually see around 8 - 10 women with suspected PCOS per week. We expect 5 
– 6 of them will fulfil the inclusion and exclusion criteria and of those we expect 3 – 4 to agree to 
take part in the study.  
11. Recruitment and choosing participants 
 
Method of recruitment 
Patients will be given the PIS by the study investigator or clinic nurse while sitting in the waiting area 
before being seen in the PCOS clinic. They will be advised to take the PIS home and call back if they 
are happy to take part in the study or if they have any question related to the study. In addition, an 
invitation letter and study PIS will be sent to patients who attended the PCOS clinic in the last 12 
months. A list of patients who attended the PCOS clinic within the last year will be generated and 
from this list we will identify patients with confirmed diagnosis of PCOS and we will send the PIS and 
invitation letter to them by post.  
Patients will also be recruited from the Weight Management Clinic and the reproductive 
endocrinology clinic where the PIS will be given to patients with a history of PCOS by the clinic 
doctor. Patients will be advised to take the PIS home and call back if they are happy to take part in 
the study or if they have any questions related to the study. 
A poster inviting women with a history of PCOS to take part in the study will be displayed at 
University Hospital Coventry and an e-poster will be displayed at the hospital intranet. Women who 
answer the advert will be sent the PIS and advised to call back if they would like to take part or if 
they have any question about the study.  
 
 
Procedures to assess study suitability 
Initial biochemical and clinical screening to confirm the diagnosis of PCOS and investigate the 
likelihood of OSA will be performed as part of routine clinical care in the National Health Service 
(NHS).  
For patients who self-refer through the advertisement, the study doctor will clarify the diagnosis of 
PCOS with them on the phone and if the diagnosis is not clear, they will be offered the chance to be 
seen in the PCOS clinic if they wish. 
- 
Consent  
We expect patients to have the PIS for at least 24 hours before making a decision about taking part 
in the study. Patients who agree to take part in the study and have a confirmed diagnosis of PCOS 
will be invited for a study visit. Consent will be obtained by a study doctor/investigator from all study 
participants before taking part in any study related activity.  
 
 

 
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- 
Participants 
 38 women will be recruited after fulfilling the inclusion and exclusion criteria. Study participants will 
be screened for OSA using Berlin and Epworth Sleepiness Scale (ESS) questionnaires and if both were 
normal then no further testing for OSA is required. If the score on either of the questionnaires was 
abnormal then home-based sleep studies will be arranged and the patient will be referred to the 
Respiratory Physician as per routine clinical care. 
OSA will be assessed by a single overnight home-based cardiorespiratory sleep study using a 
portable multichannel device (Alice PDx, Philips, US) and scored in accordance with the International 
Classification of Sleep Disorders (ICSD-3) (American Academy of Sleep Medicine 2014). The scoring 
of the sleep studies will be performed by Dr Asad Ali, Respiratory Physician, or a sleep technician. 
Sleep studies with <4 hours of adequate recordings will be repeated and excluded if the quality 
remained poor. OSA is defined by either an AHI of ≥5 with daytime sleepiness as well as gasping, 
choking or snoring; or an AHI of ≥15 in the absence of symptoms (American Academy of Sleep 
Medicine 2014). 
 
Participants will be divided into two groups depending on the results of the ESS and Berlin 
questionnaires and sleep studies: 
1. PCOS low risk OSA: women with PCOS with either normal scores on both the ESS and Berlin 
questionnaires, or who had normal sleep studies. 
2. PCOS OSA: women with PCOS who had sleep studies confirming the presence of OSA. 
12. Overview of study visit 
Patients who agree to take part in the study will be asked to fast for 10 hours, where only water is 
allowed, before the study visit. Patients will also be asked to avoid exercise, caffeine (for example 
coffee, tea, and caffeine rich drinks), and chocolate in the 24 hours prior to the study visit; a clear 
instruction on which foods or drinks to avoid will be provided in the PIS. 
On the study visit and after obtaining consent from study participants, their eligibility criteria to take 
part in the study will be assessed by the study investigator. Participants who fulfil the study 
inclusion/exclusion criteria will have full medical history obtained, and physical examination 
performed. If risk of OSA has not already been assessed in the clinic using the Berlin and the ESS 
questionnaires, these questionnaires will be completed. Participants with a high score on either the 
Berlin or ESS questionnaires will be provided with a portable sleep machine to take home; and a 
referral to the respiratory clinic will be arranged as per routine clinical practice. Information on how 
to use the sleep machine will be explained to the study participant by study doctor. Participants will 
be asked to return the machine the next day. Participants will have fasting bloods and early morning 
urine samples collected and stored. They will fill QoL and depression questionnaires. They will also 
be asked detailed questions about their fertility history. For women with regular periods, this visit 
will occur at the follicular phase of the cycle (day 1 – 7); while for oligomenorrhoic women a random 
blood sample will be collected. The duration of the visit is approximately 1.5 hours. 
A summary of patient activity during the study visit is provided in Table 2.  
 

 
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Visit 
1 
Participants 
All 
Duration 
Approximately 1.5 hours 
Informed consent 
X 
Medical history 
X 
Reproductive history 
X 
Anthropometry 
X 
Physical examination 
X 
Screening for OSA 
X 
Early morning urine sample 
X 
Blood tests 
X 
QoL and HAD questionnaires 
X 
Table 2 Description of study visit. 
 
13. Data 
Data will be collected by the study investigator and/or a research nurse. 
13.1 Anthropometric measurements  
BMI is calculated as weight in kilograms divided by the square of height in meters. Waist 
circumference is defined as the widest circumference at the midpoint between the lateral iliac crest 
and the lowest rib margin at the end of normal expiration. Hips circumference is defined as the 
widest circumference over the femoral heads.  
13.2 Urine sample 
Each participant will be asked to provide an early morning urine sample. Urine samples will be 
frozen at -20°C until analysed. Samples will be stored at University Hospital Coventry. Urine samples 
will be used to measure markers relating to PCOS, OSA, obesity and components of the metabolic 
syndrome, such as urinary isoprostanes which are markers of oxidative stress (Patrono and 
FitzGerald 1997). Urinary isoprostanes, 8-iso PGF2α, will be measured by ELISA using urinary 
isoprostane EIA kit (Oxford Biomedical Research, Oxford, USA) as per manufacturer’s protocol by an 
operator who is blinded to study group of participants.  
13.3 Blood sampling 
The study visit and blood sampling will be performed at the follicular phase of the cycle, unless 
women are oligomenorrhoic where a random blood sample will be collected. Around 40ml of blood 
will be collected after an overnight fast. Blood samples will be centrifuged immediately and the 
serum and plasma aliquots are stored at -80оC till batch analysis. Blood samples will be stored at 
University Hospital Coventry. Samples will be used to measure markers relating to PCOS, OSA, 
obesity and components of the metabolic syndrome, such as markers of inflammation (hCRP), IR 
(FPG, insulin and HOMA-IR), hyperandrogenism (TT, sex hormone binding globulin, free androgen 
index, androstenedione, and dehydroepiandrosterone sulphate), diabetes (FPG and HbA1C), lipids 
(total cholesterol, low density lipoprotein, high density lipoprotein, and triglycerides),  and 
reproductive hormones (FSH, LH, oestradiol, Anti-Mullerian Hormone). Participants will be given a 

 
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blood form to have their day 21 progesterone measured, unless if oligomenorrhoic where a random 
sample will be measured. Participants on the combined oral contraception pill (OCP) will not have 
their reproductive hormones measured. 
13.4 Reproductive history 
Participants will be asked if they are currently trying for children. Infertility will be defined as failure 
to achieve a clinical pregnancy after 12 months or more of regular unprotected sexual intercourse 
(Zegers-Hochschild et al. 2009). 
Participants will be asked if they have tried for children in the past, and if so:  
- 
Number of pregnancies 
- 
Number of children 
- 
Number of miscarriages 
- 
Have they been seen in the fertility clinic? 
- 
Have they required any fertility treatment? 
- 
Have they developed gestational diabetes? 
- 
Have they developed pre-eclampsia or any pregnancy related complications? 
13.5 Clinical history 
Period cyclicity: Women will be asked to estimate how many periods they had in the four months 
preceding the study visit. We accept that there is a risk of recollection bias with this method. For 
participants using hormonal contraception, this information will not be collected. 
Hirsutism: This will be assessed using the modified Ferriman-Gallwey score (Appendix). The modified 
Ferriman-Gallwey scoring system (Ferriman and Gallwey 1961) is a useful clinical tool, though 
subjective, in assessing hirsutism. Women are asked to assess the degree of their body hair using 
pictures of nine body areas and to give a score ranging from 0 (absence of terminal hair growth) to 4 
(heavy terminal hair growth) for each area. A total score of 8 or more on the modified Ferriman-
Gallwey scoring system is widely considered suggestive of hirsutism (DeUgarte et al. 2006). 
Risk of OSA: The risk of OSA will be assessed as per clinical practice using the Berlin and ESS 
questionnaires. Although the ESS (Appendix) is commonly used, it mainly assesses sleepiness (Johns 
1991). A score of more than 10 on the ESS is consistent with excessive daytime sleepiness. The Berlin 
questionnaire (Appendix) assesses the risk of OSA and has a sensitivity of around 85% (Netzer et al. 
1999). 
13.6 Quality of life 
QoL will be assessed using the PCOS health-related quality of life questionnaire (PCOSQ), and the 
World Health Organisation QoL questionnaire (WHOQOL-BREF). We will not be using an OSA 
disease-specific QoL questionnaire as only a proportion of study participants will have OSA and 
subsequently such a questionnaire will not reflect the QoL in controls well.  
The PCOSQ (Cronin et al. 1998) is a validated method of assessing QoL in women with PCOS. It is the 
only PCOS condition-specific measure of QoL. The PCOSQ includes 26 items (questions) to cover 5 
domains which were found to be of most importance to women with PCOS: emotions (8 items), 

 
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body hair (5 items), weight problems (5 items), menstrual problems (4 items) and infertility (4 
items). Each item is scored out of 7, in which a score of 7 denotes no problems or difficulties and a 
score of 1 indicates maximum impairment. Each domain score is calculated by dividing the total 
score of all items within a domain by the number of items in that domain. The PCOSQ takes 10–15 
minutes to complete and lower scores suggest impaired QoL. The PCOSQ has been found to 
demonstrate acceptable internal consistency (0.70–0.97) and test-retest reliability (Malik-Aslam et 
al. 2010). A difference of 0.5 on the 1 to 7 scale has been suggested to represent the minimal 
important difference in the questionnaire score, i.e. the smallest change in score that women feel is 
important in their daily lives (Cronin et al. 1998). 
The WHOQOL-BREF (Skevington and McCrate 2012) is a validated generic measure of QoL. It 
includes 26 questions to assess four major domains (subscales): physical, psychological, social and 
environment. Scores are given out of a hundred and higher scores are better; a score of more than 
50% indicates an acceptable to good QoL. The WHOQOL-BREF has been shown to display high 
internal consistency (0.92); good test-retest reliability (0.66 – 0.72); discriminant validity 
(discriminating sick from healthy people), and content validity (correlation with the Short Form 36 
Health Survey (SF-36)) (Skevington and McCrate 2012). WHOQOL-BREF provides a very good holistic 
assessment of QoL in the general population and its validation study included a group of women 
with PCOS, and a group of people with sleep disorders (Skevington and McCrate 2012). 
13.7 Depression and anxiety 
Depression and anxiety will be assessed using the Hospital Anxiety and Depression (HAD) scale. 
Participants on antidepressant medications will be considered as having ‘clinical depression’. 
The HAD scale (Zigmond and Snaith 1983) is an internationally validated  (Herrmann 1997) method 
of assessing patients’ mood. It consists of 14 items (questions), seven reflecting anxiety and seven 
reflecting depression. Each question answered will give the patient a four point (0 – 3) response 
category with the possible scores range from 0 to 21 for anxiety and 0 to 21 for depression. A score 
of 0 to 7 in each sub-scale is regarded as normal while a score of 11 or higher indicates probable 
presence of mood disorder. The HAD scale takes 3 – 5 minutes to answer and the patient is asked to 
choose the answer which best reflects how they felt in the last week. 
13.8. Sleep studies 
The diagnosis of OSA will be made using portable home-based sleep machines (Aice PDx, Philips, US). 
Alice PDx is a small, portable, easy to use and validated device for the diagnosis of OSA. The device is 
connected to a nasal cannula to measure patient airflow; pulse oximeter to measure oxygen 
saturation; and two belts applied around the chest and abdomen to measure chest and abdominal 
wall movements. The device also has an indicator which displays how many hours of good quality 
data were obtained. The study doctor will explain to the patient how to use the device and the 
patient needs to wear the device before going to bed. The analysis of the sleep study data will be 
performed by Dr. Asad Ali or a sleep technician.  Patients with confirmed diagnosis of OSA on sleep 
studies will be followed up in the chest clinic as part of NHS routine care. 
 
 
 

 
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14. Statistical considerations 
14.1 Sample size calculation 
The QoL between the two groups will be compared based on the PCOSQ and the WHOQOL-BREF 
questionnaires.  
The validation study for the WHOQOL-BREF (Skevington and McCrate 2012) included a group of 
people with sleep disorders and a group of healthy controls. Based on this study a total sample size 
of 38 participants will give us 80% power, and 5% significance (two-tailed), to detect a mean 
difference of 17.8 on one item of the WHOQOL-BREF (large effect size 0.98) between cases (PCOS 
OSA) and controls (PCOS low risk of OSA), Table 3. We used an allocation ratio for cases/controls of 
0.67, 40% of participants in the PCOS OSA group, and 60% in the PCOS low risk OSA group. Sample 
size was calculated using GPower 3.1. 
 
Well 
n=141 
Sleep disorders 
group 
n=45 
Pooled 
SD 
Mean 
difference 
Effect 
size 
n/ PCOS 
OSA 
group 
n/PCOS 
low risk 
OSA 
group 
Total 
sample 
Item 
Mean 
SD 
Mean 
 
SD 
 
 
 
 
 
Physical 
Health 
75.41 
18.72 
57.65 
17.67 
18.2 
17.8 
0.98 
15 
23 
38 
Table 3. Difference in WHOQoL-Bref scores on the physical health item between people with sleep 
disorders breathing and healthy controls (Skevington and McCrate 2012). 
 
14.2 Statistical analysis 
Continuous baseline characteristics for each of the PCOS OSA and PCOS low risk OSA groups will be 
summarised using the mean (±SD) and the median (interquartile range). If the data are 
approximately normally distributed, the means for the two groups will be compared using the 
independent t-test. If the data are not normally distributed, the two groups will be compared using 
the Mann-Whitney U test. Data will be checked for normality using the Shapiro-Wilk test (Razali and 
Wah 2011). Categorical baseline characteristics for each of the PCOS OSA and PCOS low risk OSA 
groups will be summarised by reporting the count and percentages in each category. The two groups 
will be compared using the chi-squared test. 
To compare quality of life for the PCOS OSA and PCOS low risk OSA groups, we will fit linear models 
for each of the primary outcomes of interest (domain scores on the PCOSQ and WHOQOL-BREF 
questionnaires). The dependent variable in a linear model will be a primary outcome and 
independent (predictor) variable of interest will be whether a woman is from the PCOS OSA or PCOS 
low risk OSA group. As the groups may be imbalanced in other predictors for the primary outcomes, 
the models will adjust for potential confounders such as age, BMI, WHR, use of oral contraceptive 
pill, ethnicity, education level, marital status, other ongoing illnesses, and parity. Data will be 
assessed if they are approximately normally distributed; and if they are not, they will be 
transformed, for example, by taking the logarithm of the outcome variables.  
Correlations will be evaluated using Pearson’s coefficient (or Spearman’s coefficient for non-
normally distributed data). A two tailed P value of <0.05 will be considered statistically significant. 
Statistical analysis will performed using the SPSS statistics package (SPSS Inc., Chicago, USA). 

 
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15. Ethical Considerations 
The study will be performed subject to favourable opinion from NHS Research Ethics Committee 
(REC), and the NHS Health Related Authority (HRA), and approvals from University Hospitals 
Coventry and Warwickshire NHS Trust Research and Development Department. Patients will be 
offered the PIS by a nurse while they are sitting in the waiting area before being seen in the PCOS 
clinic. The PIS and a study invitation letter will also be sent to patients who attended the PCOS clinic 
in the last 12 months.  
We excluded women who do not speak adequate English from the study. However, almost all the 
women attending the PCOS clinic at University Hospital Coventry speak and understand English 
adequately.  
We are asking study participants to fast before obtaining their written consent. However, these 
women will already have a confirmed diagnosis of PCOS as they will be recruited from the PCOS 
clinic. They will also have had enough time to read the PIS to consider whether they would like to 
take part in the study. When a patient calls back to express interest in the study and book a study 
visit, the study doctor will run through the inclusion/exclusion criteria with the patient and obtain 
her verbal consent on the phone to ensure she is happy to fast before attending the study visit and 
signing the written consent form. This will save the study participant time and effort, particularly as 
we are not paying for participants’ transport or car parking fees.  
Depending on the scores from the HAD scale, this study may result in the identification of women 
with PCOS who may suffer from depression or anxiety. Women with high scores on the HAD 
questionnaire will be advised to attend their GP for further evaluation of their mood. 
Study participants who are sleepy during the daytime will be advised not to drive if feeling sleepy. 
Those with a confirmed diagnosis of OSA will be seen in the respiratory clinic and issues related to 
driving and DVLA regulations will be discussed with them by the Respiratory physician as per routine 
clinical care; this information will also be included in the PIS.  
Women with high risk of OSA will be offered a portable sleep study machine to take home. Studies 
with less than 4 hours of good quality recordings will be repeated and if the quality remained poor 
they will be excluded from the study. However, this should not affect women’s clinical care as all 
women with high risk of OSA will be referred to the Chest clinic. 
16. Side effects 
There are no serious side effects to any of the study procedures. Taking blood samples may well 
cause discomfort and risks of inflammation/ infection/ bruising at the needle site. The procedure will 
be explained to the study participant before it is done to minimise the anxiety. The blood taking will 
be performed by an experienced study nurse or doctor in accordance with the local guidelines.  
17. Insurance 
UHCW has agreed to act as sponsor for this trial and will undertake the responsibilities of sponsor as 
defined by the Research Governance Framework and ICH Good Clinical Practice. An authorised 
representative of the Sponsor has approved the final version of this protocol with respect to the trial 
design, conduct, data analysis and interpretation and plans for publication and dissemination of 
results. As sponsor, UHCW provides indemnity for this trial and, as such, will be responsible for 

 
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claims for any non-negligent harm suffered by anyone as a result of participating in this trial. The 
indemnity is renewed on an annual basis and will continue for the duration of this trial. 
18. Funding 
Dr. Hassan Kahal is an NIHR clinical lecturer in Diabetes and Endocrinology and 50% of his time is 
allocated to research and funded by NIHR.  
19. Public and Patient Involvement 
We discussed the study with seven patients attending the PCOS clinic at University Hospital 
Coventry. All women felt the study is important particularly as it may help women with PCOS to 
understand their condition better and may help explain some of their symptoms. They also felt the 
study may help to identify women with PCOS who suffer with OSA and may benefit from treatment. 
Five out of the seven women said they will be happy to take part in a similar study and one woman 
said she will consider it. 
20. Reporting and dissemination 
Results from the study will be presented in the British and/or International Endocrine Society 
Meetings, and we aim to publish the results of the study in high impact peer-reviewed 
Endocrinology journals. Study participants will be asked if they want to be informed about study 
results and if they do a summary of the research findings will be sent to them. 
21. Annual Progress Reports 
An annual progress report will be submitted to the main REC which gave the favourable opinion 12 
months after the date on which the favourable opinion was given and thereafter until the end of the 
study. 
22. Data handling and record keeping 
All information that is collected about you during the course of the research will be kept strictly 
confidential. Paper study documents will be retained in a secure (kept locked when not in use) office 
located at the WISDEM centre, University Hospital Coventry, during and after the study has finished. 
Electronic data will be stored on University Hospitals Coventry and Warwickshire NHS Trust 
computers, which are password protected and user-access restricted to authorised persons in 
adherence to Trust information Governance Policy. The authorised persons who may have access to 
the study data include study researchers, regulatory authorities, and people monitoring the quality 
of the research at University Hospital Coventry. If data is transferred electronically, for example to 
analyse on a University computer, the data will be encrypted and linked anonymised, i.e. it will have 
participant’s name, date of birth, and address removed and replaced with participant’s study ID 
number. Only the study researchers will be able to link the study ID and participant’s personal 
details. Data will be collected and retained in accordance with the Data Protection Act 1998. Data 
(paper and electronic) will be held for a total of 25 years. 
23. Monitoring and Auditing 
The study will be monitored by the Research, Development and Innovation Department at UHCW as 
representatives of the Sponsor, to ensure that the study is being conducted as per protocol, 
adhering to Research Governance and GCP. The approach to, and extent of, monitoring will be 

 
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specified in a study monitoring plan determined by the risk assessment undertaken prior to the start 
of the study.  
24. End of study 
End of the study is the date of the visit of the last study participant. An end of study declaration form 
will be sent to the main REC and sponsor within 90 days of the end of the study or within 15 days if 
the study is terminated early.  
 
 

 
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Appendix: 
1. Modified Ferriman-Gallwey Score. 
2. Epworth Sleepiness Scale (ESS). 
3. Berlin Questionnaire. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
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 1. Modified Ferriman-Gallwey Score 
 
Each of the nine body areas is rated from 0 (absence of terminal hairs) to 4 (extensive terminal hair 
growth) and the numbers in each area are added to obtain the total score. A total score  8 
generally defines hirsutism (Ferriman and Gallwey 1961; DeUgarte et al. 2006). 
 

 
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2. Epworth Sleepiness Scale (ESS) 
 
A score more than 10 on the ESS suggests an increased risk of OSA (Johns 1991; Greenstone and 
Hack 2014). 

 
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3. Berlin Questionnaire 
 
The test is suggestive of OSA if two or more categories were positive.  Category 1 is positive if 2 or 
more responses were positive (shaded areas). Category 2 is positive if 2 or more responses were 
positive. Category 3 is positive if the patient had a history of hypertension or BMI>30kg/m2 (Netzer 
et al. 1999).