Obstructive sleep apnea and hypopnea syndrome in patients admitted in a tertiary hospital in Cameroon: Prevalence and associated factors.

PURPOSE: Obstructive sleep apnea and hypopnea syndrome (OSAHS) is poorly documented in Sub-Saharan Africa, especially in the hospital setting. The aim of this study was to determine its prevalence and to investigate the associated factors in patients admitted in a tertiary referral hospital in Cameroon.
METHODS: In this cross-sectional study conducted in the Cardiology, Endocrinology and Neurology departments of the Yaounde Central Hospital; all patients aged 21 and older were included consecutively. A sample of randomly selected patients was recorded using a portable sleep monitoring device (PMD). OSAHS was defined as apnea-hypopnea index (AHI) ≥ 5/hour (with > 50% of events being obstructive) and moderate to severe OSAHS as an AHI > 15/hour. Logistic regression was used to identify factors associated to OSAHS.
RESULTS: Of the 359 patients included, 202 (56.3%) patients were women. The mean age (standard deviation) was 58 (16) years. The prevalence of OSAHS assessed by PMD (95% CI) was 57.7% (48.5-66.9%), 53.8% in men and 62.7% in women (p = 0.44). The median (25th-75th percentiles) AHI, body mass index and Epworth Sleepiness Scale score of OSAHS patients were 17 (10.6-26.9)/hour, 27.4 (24.7-31.6) kg/m2 and 7 (5-9) respectively. The only factor associated to moderate to severe OSAHS was hypertension [odds ratio (95% CI)]: 3.24 (1.08-9.72), p = 0.036.
CONCLUSION: OSAHS is a common condition in patients in this health care centre of Cameroon. In the hospital setting, screening for OSAHS in patients with hypertension is recommended.

Introduction

Obstructive Sleep Apnea and Hypopnea Syndrome (OSAHS) is now recognized as a cardiovascular risk factor responsible for significant morbidity and mortality if untreated [1-4]. Prevalence estimates depend on populations examined, time periods of assessment, and how breathing events of obstructive sleep apnea and hypopnea are defined, but can reach large minorities to majorities of specific population subgroups[5].

The prevalence of OSAHS defined as an apnea hypopnea index (AHI) ≥ 5 per hour has varied from 6% in men and 4% in women (1993) to 83.8% in men and 60.8% in women (2013)[6-8]. In developing countries, particularly in sub-Saharan Africa (SSA), the prevalence of high risk of OSAHS, assessed by questionnaires, is between 30 and 60%[9-11]. Using portable sleep monitoring devices (PMD) or polysomnography, the prevalence of the disease in the general population is 28.5% and that of moderate to severe OSAHS is 6.3% while the prevalence is between 40–60% in patients attending hospital [10,12,13].

The prevalence of OSAHS is even larger in health care setting. It amounts 40 to 80% in developed countries [14-17]. In SSA, few studies document the prevalence of OSAHS in health care setting [9,18]. In daily clinical practice, patients with high risk of OSAHS are frequently admitted to hospital, but the OSAHS is rarely detected and, as a consequence, subsequent management is not optimal [19]. Knowing the prevalence of OSAHS in our hospital patients will enable to take appropriate measures to improve the diagnosis and the overall management of patients. The aim of this study was to evaluate the prevalence of OSAHS and to investigate associated factors in patients admitted in a tertiary referral health care centre in Cameroon.

Materials and methods

Participants and study setting

This cross-sectional study, conducted over a 7-month period from November 2016 to May 2017, was carried out at the Yaounde Central Hospital (YCH), a government-run tertiary health facility in the capital city of Cameroon, which serves as referral centre for Yaounde and its environs. All patients aged 21 and older admitted in the Cardiology, Neurology and Endocrinology departments of the YCH were eligible for the study. Patients unable to answer questionnaires, with nasogastric tubes were excluded. The participants were recruited consecutively during the inclusion period.

Procedure

All eligible patients who signed an informed consent completed a STOP-BANG questionnaire. They were classified into two groups according to the risk of OSAHS (low versus high) as assessed from the STOP-BANG questionnaire. Every day, a participant was randomly selected from each group to be recorded by a portable sleep monitoring device (PMD).

Data collection

The socio-demographic characteristics recorded were: age, sex, marital status and occupational category. The comorbidities recorded were hypertension, diabetes mellitus, heart failure, stroke, human immunodeficiency virus (HIV) infection, and epilepsy. Alcohol consumption was assessed as follows: current regular, occasional, former consumer (at least 12 months without alcohol consumption) or never consumer of alcohol and the ethylic index was calculated in grams per day [amount of alcohol consumed daily in ml x alcohol percentage x density (0.8)]. Tobacco smoking was assessed and participants ranked as current smokers (participants having smoked at least one cigarette a day for at least one year, or having smoked at least 20 cigarettes in their lifetime and still smoking), ex-smokers (participants who declared having stopped smoking for at least six months) and never-smokers.

The following symptoms were collected were: snoring, apnea witnessed by family members, nocturia, daytime fatigue, daytime sleepiness, morning headaches, non-restorative sleep. The daytime sleep propensity was assessed by the Epworth Sleepiness Scale (ESS) which consists of eight items (described situations) arranged on a 4-point Likert scale ranging from 0 (‘never doze’) to 3 (‘high chance of dozing’ during daytime). The summed scores range from 0 to 24; scores above 10 are commonly interpreted as consistent with excessive daytime sleepiness [20]. Neck circumference, hip circumference, weight, height were measured and body mass index (BMI) derived as the ratio: weight (kg) / height / height (m2). A BMI ≥ 30 kg / m2 defines obesity.

OSAHS assessment

Screening for risk of OSAHS

The risk of OSAHS was evaluated by the STOP-BANG questionnaire, a tool validated in different clinical situations for OSAHS screening [21]. It consists of 8 questions that can be answered by “yes” or “no”. The number of "yes" answers determines the questionnaire score. The risk of OSAHS is high when the score ≥ 3 [22].

Diagnosis of OSAHS

Respiratory events during sleep were recorded by PMD (SLEEP FAIRY Lt, Co), a type III recording system. The PMD was placed on the participant in hospital at bedtime and the recording was started by the participant or his/her family member at the time of falling asleep and stopped at awakening. The signals recorded included airflow through a nasal pressure sensor, oxyhaemoglobin saturation and pulse rate from pulse oximetry as well as thoracic and abdominal movements through respiratory inductance plethysmography. The sleep recordings were manually scored by a certified polysomnologist, with appropriate sleep related training. Recordings with unreadable signal on more than 25% of the recording time and recordings of less than 4 hours were excluded. The respiratory events were scored according to the “The AASM Manual for the Scoring of Sleep and Associated Events”[23]. Obstructive sleep apnea was defined as a reduction ≥ 90% in airflow for ≥ 10 seconds during sleep with persistent ventilatory efforts. Hypopnea was defined as a reduction of ≥ 30% airflow for ≥ 10 seconds during sleep associated with a desaturation ≥ 3%. The apnea-hypopnea index (AHI) was the result of the ratio of the sum of all apneas and hypopneas divided by the total recording time. According to the "International Classification of Sleep Diseases" 3rd version criteria, OSAHS was diagnosed when the AHI was ≥ 5 per hour of recording in presence of OSAHS symptoms with > 50% of events being obstructive, and moderate to severe OSAHS when the AHI was ≥ 15 per hour[24].

Ethical statement

The study was approved by the Ethics Committee of the Faculty of Medicine and Biomedical Sciences of the University of Yaounde I, Cameroon. The study received administrative authorisation from the Centre Region Delegation of the Ministry of Public Health of Cameroon. Subsequently, a recruitment authorization from the YCH administrative team was obtained, as well as the written informed consent of all included participants.

Statistical analysis

The sample size was determined assuming that two participants a day would be recorded by PMD during the study period, thus 400 subjects. Assuming a 40% prevalence of OSAHS in in-hospital patients [17], a type 1 error of 5%, a power of 80%, the required sample size was 182 participants.

Data were analysed using IBM-SPSS Version 20 for Windows (SPSS Inc., Chicago, IL). Qualitative data are presented as counts and proportions, and quantitative variables as mean and standard deviation (SD) or median and 25th-75th percentiles. Chi squared test and Fisher exact test were used to compare proportions. Quantitative variables were compared by Student's T test or its non-parametric equivalent. The prevalence of OSAHS was that obtained in the sub-sample of patients who were recorded by PMD. Logistic regression models were used to investigate factors associatedto moderate to severe OSAHS. Potential associated factors were first tested in univariate analysis, and significant ones (based on p < 0.10 threshold) were further tested in multivariate models. A p-value < 0.05 was used to define statistically significant results.

Results

As shown in Fig 1, a total of 383 subjects were invited to take part in the study, of whom 24 declined (response rate of 93.7%). Three hundred and fifty-nine subjects participated in the study, from which 193 patients were randomly selected for PMD recording. Only 176 subjects were recorded, of which data were valid in 111 subjects.

Fig 1

Flow chart of the inclusion of participants.

PMD: Portable Monitoring Device.

General characteristics of the study population

Of the 359 participants, 202 (56.3%) were women. The mean age (standard deviation) was 58 (16) years. As presented in Table 1, the most common comorbidities were hypertension (50.1%) and diabetes mellitus (34.3%). Hypertension was significantly more frequent in women than men. Current smoking and regular or occasional alcohol consumption were found in 8.6% and 58.2% of participants respectively.

Table 1

Sociodemographic characteristics and comorbidities of the study population.

Characteristics	Overalln = 359 (%)	Menn = 157 (%)	Womenn = 202 (%)	p-value
Age in years, mean (SD)	58 (16)	56 (15)	59 (16)	0.059
Marital status
Alone	173 (48.2)	39 (24.8)	134 (66.3)	<0.001
Living in couple	186 (51.8)	118 (75.2)	68 (33.7)
Occupational category
Unemployed	321 (89.4)	129 (17.8)	192 (96)	<0.001
Employed	38 (10.6)	28 (82.2)	10 (4)
Hypertension	180 (50.1)	67 (42.7)	113 (55.9)	0.014
Diabetes mellitus	123 (34.3)	55 (35)	68 (33.7)	0.823
Heart failure	53 (14.8)	20 (12.7)	33 (16.3)	0.371
Stroke	111 (31)	55 (35.3)	56 (15.6)	0.135
HIV infection	48 (13.4)	15 (9.6)	33 (16.3)	0.085
Epilepsy	10 (2.8)	7 (4.5)	3 (1.5)	0.111
Tobacco smoking
Smokers	31 (8.6)	17 (10.8)	14 (6.9)	<0.001
Ex-smokers	30 (8.4)	24 (15.3)	6 (3)
Non-smokers	298 (83)	116 (73.9)	182 (90.1)
Alcohol consumption
Regular	65 (18.1)	39 (24.8)	26 (12.9)	<0.001
Occasional	144 (40.1)	78 (49.7)	66 (32.7)
Old consumer	78 (21.7)	26 (16.6)	52 (25.7)
Never	72 (20.1)	14 (8.9)	58 (28.7)
Ethylic index, g/day, median in (25th-75th percentiles)	16.5 (2.9–57.2)	28.6 (5.7–93.8)	2.86 (0.2–28.6)	<0.001

SD: Standard Deviation; HIV: Human Immunodeficiency Virus.

The Table 2 summarises the clinical characteristics of participants. Snoring was the most common symptom of OSAHS and was significantly more prevalent in men. Two hundred and five (57.1%) participants reported sleepiness, while only 24 (6.7%) had an ESS consistent with excessive daytime sleepiness. Obesity was present in 30.6% of patients and more prevalent in women than men (28% vs. 21%, p = 0.001). The neck circumference of men was higher than that of women (39 vs. 35 cm, p < 0.001).

Table 2

Clinical characteristics of the study population.

Characteristics	Overalln = 359 (%)	Menn = 157(%)	Womenn = 202(%)	p-value
OSAHS symptoms
Snoring	215 (59.9)	109 (69.4)	106 (52.5)	0.001
Apnea witnessed	64 (17.8)	37 (23.6)	27 (13.4)	0.018
Nocturia	141 (39.3)	94 (59.9)	124 (61.4)	0.828
Daytime fatigue	293 (81.6)	128 (81.5)	165 (81.7)	1
Non-restorative sleep	44 (31.8)	53 (33)	31 (31)	0.494
Sleepiness	205 (57.1)	91 (58)	114 (56.4)	0.83
Morning headaches	140 (39)	54 (34.4)	86 (42.6)	0.127
BMI, kg/m2	26.1 (22.3–30.8)	25.7 (23.2–29.3)	26.4 (21.3–32.9)	0,31
BMI > 30 kg/m2	110 (30.6)	33 (21)	74 (28.1)	0.001
Hip circumference, cm	90 (78–102)	88 (80–99)	94 (76–108)	0.047
Neck circumference, cm	37 (34–39)	39 (37–41)	35 (33–37.5)	<0.001
ESS	6 (3–8)	7 (5–9)	5 (3–7)	<0.001
ESS score > 10	24 (6.7)	12 (7.6)	12 (5.9)	0.531

All continuous variables are expressed as median (25th-75th percentiles); OSAHS: Obstructive Sleep Apnea and Hypopnea Syndrome; BMI: Body Mass Index; ESS: Epworth Sleepiness Scale

Prevalence of high risk of OSAHS

As shown in Fig 2, The prevalence [95% confidence interval (95% CI)] of high risk of OSAHS, as assessed from the STOP-BANG questionnaire, was 64.1% (59.1–69.1%) in the whole population, 78.3% (71.9–81.7%) in men and 53% (46.1–59.9%) in women (p < 0.001).

Fig 2

Risk of obstructive sleep apnea and hypopnea syndrome assessed by STOP-BANG questionnaire in the population study.

Prevalence and characteristics of OSAHS

One hundred and eleven (30.9%) participants with valid PMD records constituted the sub-sample in which the prevalence of OSAHS was objectively evaluated. In those participants, hypertension, diabetes mellitus, snoring, non-restorative sleep and high risk of OSAHS were more frequent (Table 3).

Table 3

Characteristics of participants recorded and not recorded by the portable sleep monitoring device.

Characteristics	Recorded by PMDn = 111 (%)	Not recorded by PMDn = 248 (%)	p-value
Women	59 (53.2)	143 (57.7)	0.49
Age in years, mean (SD)	58 (12)	57 (17)	0.69
Hypertension	70 (63.1)	110 (44.1)	0.001
Diabetes mellitus	49 (44.1)	74 (29.8)	0.011
Heart failure	20 (18)	33 (13,3)	0.371
Stroke	38 (34.5)	73 (29.4)	0.262
Snoring	79 (71.2)	136 (54.8)	0.004
Apnea witnessed	27 (24.3)	37 (14.9)	0.037
Daytime fatigue	95 (85.6)	198 (79.8)	0.238
Non-restorative sleep	44 (39.6)	70 (28.9)	0.037
Sleepiness	71 (64)	134 (54)	0.083
Morning headaches	47 (42.3)	93 (37.5)	0.413
BMI > 30 kg/m2	42 (37.8)	68 (27.4)	0.063
Neck circumference, cm (25th-75th percentiles)	37.5 (34–41)	36 (34–39)	0.106
Daytime sleepiness (ESS >10)	10 (9)	14 (5.6)	0.257
STOP-BANG ≥ 3	85 (76.6)	145 (58.5)	0.001

SD: Standard Deviation; BMI: Body Mass Index; PMD: Portable sleep Monitoring Device; OSAHS: Obstructive Sleep Apnea and Hypopnea Syndrome; ESS: Epworth Sleepiness Scale

The prevalence of OSAHS (95% CI) was 57.7% (48.5–66.9%). As presented in Table 4, of the 65 patients diagnosed with OSAHS, 35 had moderate to severe OSAHS, giving a prevalence (95% CI) of 31.5% (22.9–40.1%). OSAHS was found in 37 (62.7%) women vs 28 (53.8%) men (p = 0.44) and the equivalent figure for moderate to severe OSAHS was 22 (37.3%) women vs 13 (25%) men (p = 0.22). The median (25th-75th percentiles) AHI, BMI and ESS score of OSAHS patients were respectively 17 (10.6–26.9) per hour, 27.4 (24.7–31.6) kg/m2 and 7 (5–9). The median arterial oxygen saturation was lower in women and women had a lower ESS score. None of the participants diagnosed with OSAHS was previously aware of this diagnosis.

Table 4

Characteristics of patients diagnosed with obstructive sleep apnoea and hypopnea syndrome.

Characteristics	Overalln = 65 (%)	Menn = 28 (%)	Womenn = 37 (%)	p-value
Total recording time, min	420 (360–480)	420 (360–450)	480 (360–480)	0.026
Number of OA	38 (12–73)	28 (11–69)	48 (15–114)	0.25
Number of hypopnea	55 (32–92)	58 (29–92)	54 (36–92)	0.88
Mean SaO2, %	94 (92–96)	95 (93–96)	94 (92–95)	0.043
Minimal SaO2, %	81 (73–86)	81 (74–88)	82 (72–85)	0.67
ODI, h-1	23 (15–36)	23 (13–38)	23 (16–35)	0.62
AHI, h-1	17 (10.6–26.9)	14.1 (10.8–26.6)	17.9 (9.5–29.6)	0.89
AHI > 15	35 (53.8)	13 (46.4)	22 (59.4)	0.33
Ethylic index, g/day	28.6 (2.86–59.8)	57.2 (6.2–120.3)	2.9 (0–28.6)	0.015
Sleepiness	47 (73.3)	21 (75)	26 (70.3)	0.79
BMI, kg/m2	27.4 (24.7–31.6)	27.6 (24.7–30.9)	27.3 (24–31.6)	0.88
BMI > 30 kg/m2	40 (61.5)	20 (71.4)	20 (54.1)	0.20
ESS score	7 (5–9)	8 (5–10)	6 (4–9)	<0.001
ESS score > 10	9 (13.8)	4 (14.3)	5 (13.5)	1

All continuous variables are expressed as median (25th-75th percentiles); OSAHS: Obstructive Sleep Apnea and Hypopnea Syndrome; AHI: Apnea-hypopnea index; SaO2: arterial oxygen saturation; ODI: oxygen desaturation index; OA: Obstructive apnea; ESS: Epworth Sleepiness Scale; BMI: Body Mass Index

Factors associated to moderate to severe OSAHS

Patients with moderate to severe OSAHS (n = 35) were compared to those without sleep apnea syndrome (n = 40) as presented in Table 5. In univariate analysis, hypertension was present in 82.9% of patients with moderate to severe OSAHS and in 52.9% of patients unaffected (p = 0.004). Forty percent of patients with moderate to severe OSAHS were living alone compared to 20% of those without OSAHS (p = 0.032). In multivariate analysis, the only factor associated with moderate to severe OSAHS [odds ratio (95% CI)] was hypertension [3.24 (1.08–9.72)]. Exclusion of OSAHS symptoms as potential associated factors did change neither the direction neither the strength of the association between moderate to severe OSAHS and its potentially associated factors.

Table 5

Factors associated to moderate to severe OSAHS.

Factors	n (%)	Univariate analysis		Multivariate analysis
		OR (95% CI)	p-value	OR (95% CI)	p-value
Male sex	13 (37.1)	0.62 (0.27–1.43)	0.268	-	-
Age > 50 years	31 (88.6)	1.58 (1.35–1.73)	0.05	1.81 (0.50–6.58)	0.37
Living alone	14 (40)	2.66 (1.10–6.52)	0.032	1.50 (0.46–4.93)	0.51
Illeterate	31 (88.6)	1.67 (0.42–6.68)	0.463	-	-
Employed	17 (48.6)	1.19 (0.53–2.68)	0.678	-	-
Ethylic index > 30 g/day	14 (40)	0.6 (0.26–1,41)	0.24	-	-
Hypertension	29 (82.9)	4.31 (1.59–11.68)	0.004	3.24 (1.08–9.72)	0.036
Heart failure	10 (28.6)	2.7 (0.98–7.47)	0.054	1.94 (0.63–6.01)	0.25
Stroke	10 (28.6)	0.79 (0.33–1.94)	0.619	-	-
Snoring	27 (77.1)	1.65 (0.65–4.20)	0.292	-	-
Apnea witnessed	9 (24.7)	1.17 (0.45–2.99)	0.746	-	-
Daytime fatigue	33 (94.3)	3.76 (0.79–17.71)	0.094	2.53 (0.48–13.22)	0.27
Non-restorative sleep	18 (51.4)	2.03 (0.89–4.64)	0.093	2.05 (0.82–5.13)	0,13
Sleepiness	26 (74.3)	2.04 (0.83–5)	0.118	-	-
Morning headaches	19 (54.3)	1.89 (0.83–4.30)	0.128	-	-
ESS score > 10	6 (17.1)	3.41 (0.89–13.01)	0.072	1.75 (0.41–7.53)	0.45
Neck circumference≥ 38 cm	18 (51.4)	0.75 (0.33–1.69)	0.49	-	-
BMI > 30 kg/m2	24 (68.4)	1.54 (0.65–3.62)	0.321	-	-

95% CI: 95% Confidence Interval; OR: Odds Ratio; OSAHS: Obstructive Sleep Apnoea and Hypopnoea Syndrome; ESS: Epworth Sleepiness Scale

Discussion

The aim of this cross-sectional study was to determine the prevalence of OSAHS and to investigate factors associated to OSAHS in patients admitted in a tertiary hospital in Cameroon. The main results are: 1) a high risk of OSAHS was present in 64% of participants, as assessed from the STOP-BANG questionnaire; 2) about 2/3 of participants were diagnosed with OSAHS, while 1/3 had moderate to severe OSAHS; 3) hypertension was the only factor associated to moderate to severe OSAHS.

The prevalence of high risk of OSAHS we found in the present study using the STOP-BANG questionnaire is as high as previously reported by Sharma et al in 2015, in a study including obese patients admitted in a department of internal medicine [14]. In another study conducted by Njamnshi et al in Cameroon, 60% of patients with hypertension treated as outpatients were found to have a high risk of OSAHS using the Berlin questionnaire [25]. In the present study including patients with several comorbidities, the risk of OSAHS was found to be much higher than that assessed in the general population using the same questionnaire; namely 17.8% in Cameroon [10] or 36.9% in Nigeria [9].

To the best of our knowledge, few studies until now have characterised OSAHS in in-hospital patients in SSA. Other studies using PMD as diagnostic tool for OSAHS in hospitalized patients found that the prevalence of OSAHS was between 40 and 80% [16-18]. The prevalence of OSAHS in this cross-sectional study was 57.7%. An even higher prevalence of 87% was found in obese patients at high risk of OSAHS at Philadelphia, using polysomnography, the gold standard for the diagnosis of OSAHS [14,26]. These prevalence rates are higher than those found in the community, probably because of the existence of an association between OSAHS and conditions leading to hospitalization, as already reported in other studies[27,28]. Furthermore, 31.5% of the participants had moderate to severe OSAHS, potentially requiring specific management. However, none of these patients were aware of their diagnosis of OSAHS, corroborating the results of previous works that underline the under-diagnosis of OSAHS in health care centres [14,29].

Factors associated to OSAHS in a hospital setting may differ according to the comorbidities present in the study population. In a Chinese study including type 2 diabetes patients, a per 1 kg/m2 increase in BMI and a per 1 year increase in age were associated to OSAHS [16]. The ESS score ≥ 4 and nocturnal desaturation < 82% in hospitalized patients for acute myocardial infarction in Tunisia were associated with OSAHS [18]. In our study hypertension was independently associated to moderate to severe OSAHS, with an odd ratio as high as 3.24 in a sample where 63.1%, 44.1%, 34.5% and 18% respectively presented with hypertension, diabetes mellitus, stroke and heart failure. In a group of patients hospitalized for the management of a metabolic syndrome with controlled hypertension in France, Hansel et al also found hypertension to be associated to moderate to severe OSAHS [17].

The main limitation of the present study is that only one-third of the participants initially interviewed were recorded by PMD. Despite the random selection of patients to be recorded, while taking in consideration the risk of OSAHS, the two groups (recorded vs. non-recorded) were not entirely similar. Indeed, the frequency of known comorbidities of OSAHS (hypertension and diabetes mellitus), symptoms of OSAHS (snoring, non-restorative sleep) and high risk of OSAHS were greater in the recorded patients, probably justifying the high prevalence of OSAHS. Another limitation is the use of PMD as a diagnostic tool for OSAHS, and not the gold standard which is polysomnography. In our country, only one centre has a polysomnograph. Polysomnography, which requires more resources, is thus not very accessible. Although using PMD for the type of study that we performed seems to be appropriate, further research using the gold standard is necessary in the future. Nevertheless, PMD has a good sensitivity in high risk patients and / or with a strong clinical presumption of OSAHS [26], which was the case in this work. Furthermore, PMD yields a lower than expected AHI, since the total recording time is higher than the total sleep time and as PMD does not identify micrarousals, another diagnostic criteria of the hypopneas [26]. All this suggests that the prevalences obtained in this study may be plausible. To our knowledge, our study is the first in Cameroon, and even in whole SSA, to assess OSAHS through respiratory recordings during sleep and to evaluate the factors associated to OSAHS in a large group of hospitalized patients.

Conclusion

OSAHS is a common and under-diagnosed condition in patients with comorbidities in this Cameroonian tertiary health care centre. Hypertension is a factor significantly associated to moderate to severe OSAHS. In hospital setting, the screening for OSAHS in patients with hypertension, particularly if resistant or uncontrolled, is recommended. Additional studies, preferably using polysomnography for the diagnosis of OSAHS, are needed to confirm and extend the results obtained in this study.

Database of all patients included in the study.

(XLSX)

Click here for additional data file.

Database of randomly selected patients, recorded by portable sleep monitoring device in the study.

(XLSX)

Click here for additional data file.

9 Oct 2019

PONE-D-19-25768

Obstructive sleep apnea and hypopnea syndrome in patients admitted in a tertiary hospital in Cameroon: prevalence and determinants

PLOS ONE

Dear Dr. Poka-Mayap,

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Please take a close look at the comments of Reviewer #1 who has made many specific comments that will improve the readability of the manuscript.

In addition to the above, this editor has questions re: the analysis for moderate-severe OSA.  It is not clear to me why BMI is not included in the analysis and why an age>58 was chosen as a cutoff. Also, the authors could consider using the STOP-BANG as a factor for prediction as the STOP-BANG has been shown to be predictive of moderate-severe OSA.

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1. Please include additional information regarding the STOP-BANG questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information.

2. In your Methods section, please provide additional information about the participant recruitment method and the demographic details of your participants. Please ensure you have provided sufficient details to replicate the analyses such as: a) the recruitment date range (month and year), b) a description of any inclusion/exclusion criteria that were applied to participant recruitment,  and c) a description of how participants were recruited.

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: No

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: 1.AHI should replace OAHI : the standard abbreviation is AHI (Apnea hypopnea index) which makes your article more searchable. Also unless you have excluded the few central events which may coexist with obstructive events in OSAHS, then OAHI is a misnomer.

2. Rephrase last sentence in the conclusion of the abstract " Screening...in patients especially "in those with" hypertension....

3. Abstract conclusion: I do not agree screening is mandatory in all in patients with hypertension but rather in 1) those with resistant hypertension and 2) in those with hypertension and additional risk factors for .

4. Line 66 and 68 of introduction: Define "sleep records", describe what you mean by "particular groups of patients" so the readers understand exactly what you are referring to.

5. Line 105 in data collection: propensy should be "propensity"; after ESS insert "which"

6. Line 126 of Diagnosis of OSAHS: what is illisible? likely a typo, please correct

7. Line 131 of Diagnosis of OSAHS: consider taking out obstructive and using the universal term "Apnea hypopnea index" except all central events were excluded from the calculation

8. Line 132 of Diagnosis of OSAHS: consider changing total registration time to "total recording time" which is a more universal term. Thiswill need to be changed throughout the manuscript and in the tables if applicable.

9. Table 1: please correct all p values with commas inserted instead of decimal points. These are probably erroneous. Also ensure p values are placed in the appropriate rows for which they were calculated.

10. Table 2: again correct p values with commas instead of decimal points

11. Line 227: please rephrase, using the word "but" suggests that a lower median arterial oxygen saturation is associated with lower ESS scores, which it is not. Consider expressing these 2 findings as separate sentences.

12. Table 4: if changing total registration time to total recording time as discussed above, then correct it in this table, also OAHI to AHI. also correct p values with commas instead of decimal points. Change this in Lines 233 and 234 as well (OAHI to AHI)

13. Lines 238 to 239: The numbers do not add up. If 111 had valid data per the Results on line 162 then 6 particants are unaccounted for (40 - No OSA, 65 had OSAHS (30 had mild OSA, 35 with moderate to severe OSA)). Was there any other missing data? I missed any statements on further exclusions after the total of 111.

14. Lines 244-246. Please explain or rephrase. This sentence is confusing and has no clear meaning as it is written.

15. Table 5. why age > 58 years? How did you come about 58?? was there something in the data to suggest that 58 was an age that impacted having OSAHS or was it just based on the calculated mean age?

I believe age > 50 is what standard questionnaires use. Or if you want to look at teh geriatric population vs the other adults then maybe age of 65 and above etc. 58 appears random. Also, may be better to use "BMI>30" in the last row of the table rather than the term obesity.

16. Line 287: consider replacing "underline" with "depict"

17. Line 288 - 294: Starting from the sentence "Other studies..."These lines should follow line 284 for the sake of continuity.

18. Lines 285 - 288 ending with ref (14,26). should come after line 294. You may choose to say " Further more in our study....." to bring the readers attention back to the fact that you are referring to the findings from your study.

19. Line 303: Remove "a" before controlled hypertension, did you mean uncontrolled or controlled hypertension?

20. Line 313: The polysomnogram is not time consuming (takes the same amount of time as a portable study - in both cases overnight). More appropriate to say it is more expensive and requires more resources (skilled staff, sleep lab, equipment etc)

21. Line 317: Please replaced with AHI. and total recording time

22. Consider adding to discussion RE: results lines 179 - 180 state that ESS scores did not correlate with sleepiness. This is corroborated by several papers. Examples to look at include: 1. Smith et al . Multiple dimensions of excessive daytime sleepiness J Thorac Dis 2018, 2. Silva et al. identifiction of patients with sleep disordered breathing: comparing the four-variable screening tool... J Clin Sleep med 2011. etc. It may be nice to mention that your study finding corroborates the fact that the ESS should not be used in isolation to determine the presence of sleepiness.

23. Line 327 - 328 in conclusion: Amend to say "in patients with resistant/uncontrolled hypertension in hospital settings" . It is not cost effective or required in all hospitalized patients with hypertension. Patients with hypertension and risk factors for OSAHS can be studied in the outpatient setting.

Final comments: Overall a very good paper with excellent potential to publish regarding the OSA experience in Subsaharan Africa.

Reviewer #2: Interesting study, I commend the authors to undergo such an investigation in a country in which sleep services are not as developed as in other parts of the world.

Several comments and recommendations are listed here;

1. Have the ESS and STOP-BANG questionnaires been translated and validated in local languages? If so, how does one explain the major discrepancy between the prevalence of sleepiness (assessed qualitatively) and that of ESS>10 (Table 4)?

2. In the study flow diagram - you list 65 invalid PMD records; this is a high rate - one could want to see those repeated, so that power is not affected by the significantly lower sample size analyzed.

3. Abstract (results section) and manuscript: I would avoid causal inferences such as hypertension being the determinant of moderate to severe OSA... It may not be correct and you may not be able to prove it in a cross-sectional study. It is an association.

4. Abstract (conclusion) and manuscript: too strong a language ('is mandatory...') as a conclusion to this study's findings.

**********

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Reviewer #1: No

Reviewer #2: No

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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

20 Nov 2019

Response to reviewers

To

The Editorial office

PLOS ONE

Submission of a revised manuscript

Manuscript ID: PONE-D-19-25768 entitled " Obstructive sleep apnea and hypopnea syndrome in patients admitted in a tertiary hospital in Cameroon: prevalence and associated factors"

By Virginie Poka-Mayap et al

Dear Editor,

We are grateful to the managing editor and reviewers for their time and comments on our manuscript (referenced above). We have addressed their comments and queries and would like to submit an updated version of our manuscript for publication in the Journal. Changes in the main document have been inserted with the use of red and blue color. In addition we are providing below a point-by-point response to each query from the reviewers.

We look forward to the outcome of our submission.

Journal requirements

1. Please include additional information regarding the STOP-BANG questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information

Our answer: Thank you for raising this point. We have not developed STOP-BANG questionnaire. As mentioned in the manuscript, this screening questionnaire for OSAHS have been validated (see in the reference list: number 21).

2. In your Methods section, please provide additional information about the participant recruitment method and the demographic details of your participants. Please ensure you have provided sufficient details to replicate the analyses such as: a) the recruitment date range (month and year), b) a description of any inclusion/exclusion criteria that were applied to participant recruitment, and c) a description of how participants were recruited.

Our answer: This has been fixed. The recruitment date range was already mentioned in our initial submission and exclusion criteria were have been added. We can read now on line 85: “Patients unable to answer questionnaires, with nasogastric tubes were excluded”

From the Reviewer 1

1. AHI should replace OAHI : the standard abbreviation is AHI (Apnea hypopnea index) which makes your article more searchable. Also unless you have excluded the few central events which may coexist with obstructive events in OSAHS, then OAHI is a misnomer.

Our answer: This has been fixed.

2. Rephrase last sentence in the conclusion of the abstract " Screening...in patients especially "in those with" hypertension...

Our answer: This has been fixed. In the conclusion we can now read: “Screening for OSAHS in patients with hypertension is recommended to improve the overall management of these patients”

3. Abstract conclusion: I do not agree screening is mandatory in all in patients with hypertension but rather in 1) those with resistant hypertension and 2) in those with hypertension and additional risk factors for.

Our answer: Thank you for raising this point. In this work on patients admitted to hospital, that had cardiovascular risk factors, we found that hypertension was independently associated to moderate to severe OSAHS, with an odd ratio as high as 3.24. That is why we conclude that in the context of patients admitted to hospital, we need to particularly screen for OSAHS in this group of patients. .

4. Line 66 and 68 of introduction: Define "sleep records", describe what you mean by "particular groups of patients" so the readers understand exactly what you are referring to.

Our answer: Thank for the remark. We have expanded the section which now reads: “Using portable monitoring device (PMD) or polysomnography, the prevalence of the disease in the general population is 28.5%, and that of moderate to severe OSAHS is 6.3%, while the prevalence is between 40-60% in patients attending hospital [10,12,13]”

5. Line 105 in data collection: propensy should be "propensity"; after ESS insert "which"

Our answer: This has been fixed.

6. Line 126 of Diagnosis of OSAHS: what is illisible? likely a typo, please correct

Our answer: This has been fixed. We can now read: “Recordings with unreadable signal on more than 25% of the recording time and recordings of less than 4 hours were excluded”

7. Line 131 of Diagnosis of OSAHS: consider taking out obstructive and using the universal term "Apnea hypopnea index" except all central events were excluded from the calculation

Our answer: This has been fixed.

8. Line 132 of Diagnosis of OSAHS: consider changing total registration time to "total recording time" which is a more universal term. This will need to be changed throughout the manuscript and in the tables if applicable.

Our answer: This has been fixed.

9. Table 1: please correct all p values with commas inserted instead of decimal points. These are probably erroneous. Also ensure p values are placed in the appropriate rows for which they were calculated.

Our answer: This has been fixed. All commas have been replaced by decimal points.

10. Table 2: again correct p values with commas instead of decimal points

Our answer: This has been fixed.

11. Line 227: please rephrase, using the word "but" suggests that a lower median arterial oxygen saturation is associated with lower ESS scores, which it is not. Consider expressing these 2 findings as separate sentences.

Our answer: Two separate sentences have been written. We can now read: “The median arterial oxygen saturation was lower in women and women had a lower ESS score.”

12. Table 4: if changing total registration time to total recording time as discussed above, then correct it in this table, also OAHI to AHI. also correct p values with commas instead of decimal points. Change this in Lines 233 and 234 as well (OAHI to AHI)

Our answer: This has been fixed.

13. Lines 238 to 239: The numbers do not add up. If 111 had valid data per the Results on line 162 then 6 particants are unaccounted for (40 - No OSA, 65 had OSAHS (30 had mild OSA, 35 with moderate to severe OSA)). Was there any other missing data? I missed any statements on further exclusions after the total of 111.

Our answer: Thank you for the raising this important point. Please, 40 patients without sleep apnea syndrome were compared with 35 patients with moderate to severe OSAHS, and 30 patients have mild OSAHS. Six patients who had central sleep apnea syndrome were excluded from this analysis because our objective was to focus on OSAHS.

14. Lines 244-246. Please explain or rephrase. This sentence is confusing and has no clear meaning as it is written.

Our answer: Thank you for the remark. We presented the results of the logistic regression where we tested some potential factors associated with OSAHS. We did another analysis where we excluded symptoms of OSAHS as potential associated factors, and hypertension is still the only factor significantly associated with OSAHS.

15. Table 5. why age > 58 years? How did you come about 58?? was there something in the data to suggest that 58 was an age that impacted having OSAHS or was it just based on the calculated mean age? I believe age > 50 is what standard questionnaires use. Or if you want to look at teh geriatric population vs the other adults then maybe age of 65 and above etc. 58 appears random. Also, may be better to use "BMI>30" in the last row of the table rather than the term obesity

Our answer: Thank you for the raising this important point. We settled our cut off at 58 years because it is the median age of patients that had been recorded by PMD. We have addressed your remark by modifying the age cut to 50, as seen in the revised table 5. We have also replaced “obesity” by “BMI>30”, as you suggested.

.

16. Line 287: consider replacing "underline" with "depict"

Our answer: This has been fixed

17. Line 288 - 294: Starting from the sentence "Other studies..."These lines should follow line 284 for the sake of continuity.

Our answer: This has been fixed

18. Lines 285 - 288 ending with ref (14,26). should come after line 294. You may choose to say " Further more in our study....." to bring the readers attention back to the fact that you are referring to the findings from your study.

Our answer: This has been fixed

19. Line 303: Remove "a" before controlled hypertension, did you mean uncontrolled or controlled hypertension?

Our answer: This has been fixed. In that study, OSAHS was assessed in patients with metabolic syndrome and “controlled hypertension”.

20. Line 313: The polysomnogram is not time consuming (takes the same amount of time as a portable study - in both cases overnight). More appropriate to say it is more expensive and requires more resources (skilled staff, sleep lab, equipment etc)

Our answer: This has been fixed and the sentence has been written accordingly.

21. Line 317: Please replaced with AHI. and total recording time

Our answer: This has been fixed.

22. Consider adding to discussion RE: results lines 179 - 180 state that ESS scores did not correlate with sleepiness. This is corroborated by several papers. Examples to look at include: 1. Smith et al . Multiple dimensions of excessive daytime sleepiness J Thorac Dis 2018, 2. Silva et al. identifiction of patients with sleep disordered breathing: comparing the four-variable screening tool... J Clin Sleep med 2011. etc. It may be nice to mention that your study finding corroborates the fact that the ESS should not be used in isolation to determine the presence of sleepiness.

Our answer: Thank you for raising this important point. However in this study we have not objectively assessed sleepiness and we are unable to test the correlation of the ESS score with any objective assessment of sleepiness.

23. Line 327 - 328 in conclusion: Amend to say "in patients with resistant/uncontrolled hypertension in hospital settings" . It is not cost effective or required in all hospitalized patients with hypertension. Patients with hypertension and risk factors for OSAHS can be studied in the outpatient setting.

Our answer: Thank you very much for the remark that we addressed by modifying the sentence, we can read now: “In hospital setting, the screening for OSAHS in patients with hypertension, particularly if resistant or uncontrolled, is recommended”

Final comments: Overall a very good paper with excellent potential to publish regarding the OSA experience in Subsaharan Africa.

From the Reviewer 2

1. Have the ESS and STOP-BANG questionnaires been translated and validated in local languages? If so, how does one explain the major discrepancy between the prevalence of sleepiness (assessed qualitatively) and that of ESS>10 (Table 4)?

Our answer: Thank you for this remark. The STOP-BANG and ESS questionnaires were used in well validated French and English versions. No other language was used. It should be emphasized that many studied have found a discrepancy, similar to that in our study, between the prevalence of sleepiness assessed qualitatively and that of ESS>10 [1,2]. It can be explained by the fact that participants may not adequately discriminate fatigue and sleepiness [3].

[1] Vennelle M, Engleman HM, Douglas NJ. Sleepiness and sleep-related accidents in commercial bus drivers. Sleep Breath 2010;14:39–42. doi:10.1007/s11325-009-0277-z.

[2] Al-Abri MA, Al-Adawi S, Al-Abri I, Al-Abri F, Dorvlo A, Wesonga R, et al. Daytime sleepiness among young adult omani car drivers. Sultan Qaboos Univ Med J 2018;18:e143–8. doi:10.18295/squmj.2018.18.02.004.

[3] Neu D, Mairesse O, Hoffmann G, Valsamis J-B, Verbanck P, Linkowski P, et al. Do “sleepy” and “tired” go together? Rasch analysis of the relationships between sleepiness, fatigue and nonrestorative sleep complaints in a nonclinical population sample. Neuroepidemiology 2010;35:1–11. doi:10.1159/000301714.

2. In the study flow diagram - you list 65 invalid PMD records; this is a high rate - one could want to see those repeated, so that power is not affected by the significantly lower sample size analyzed.

Our answer: Thank you for raising this important point. However, as our study involved patients admitted to hospital for a limited period of time, we were unable to repeat the recording in case of invalid initial recording.

3. Abstract (results section) and manuscript: I would avoid causal inferences such as hypertension being the determinant of moderate to severe OSA... It may not be correct and you may not be able to prove it in a cross-sectional study. It is an association.

Our answer: We agree with this comment. We have replaced “determinant” by “associated factor” in the whole manuscript.

4. Abstract (conclusion) and manuscript: too strong a language ('is mandatory...') as a conclusion to this study's findings.

Our answer: We agree too. We have replaced “is mandatory” by “is recommended” in the whole manuscript.

Submitted filename: Response to reviewers_Revision 1_ OSAHS _YCH.docx

Click here for additional data file.

20 Dec 2019

PONE-D-19-25768R1

Obstructive sleep apnea and hypopnea syndrome in patients admitted in a tertiary hospital in Cameroon: prevalence and associated factors

PLOS ONE

Dear Dr. Poka-Mayap,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

ACADEMIC EDITOR: Be sure to:

See below for one final edit.

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We look forward to receiving your revised manuscript.

Kind regards,

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Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

As the academic editor, I reviewed the author's revisions based upon the reviewers' comments and find that they have responded in a satisfactory manner.

However, there is one wording change that I have found upon my review that needs changing before full acceptance. Line 336 in the version with the edits shown, the word 'weaker' is not correct. Portable monitoring devices yield a lower than expected AHI given the denominator is recording time and not sleep time but this does not make the AHI 'weaker'. Please word 'Furthermore, PMD yields a lower AHI compared to full polysomnography,' (Note also to take the 'O' out before 'AHI')

[Note: HTML markup is below. Please do not edit.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

24 Dec 2019

To the Editors-in-Chief

Plos One

Submission of a revised manuscript

Manuscript ID: PONE-D-19-25768 entitled " Obstructive sleep apnea and hypopnea syndrome in patients admitted in a tertiary hospital in Cameroon: prevalence and associated factors"

Dear Editor,

We are grateful to the managing editor and reviewers for their time and comments on our manuscript (referenced above). We have addressed their comments and queries and would like to submit an updated version of our manuscript for publication in the Journal. Changes in the main document have been inserted with the use of red and blue color. In addition we are providing below a point-by-point response to each journal requirements.

Additional Editor Comments

Please amend your list of authors on the manuscript to ensure that each author is linked to an affiliation.

We note that you have included affiliation numbers 1-7, ¶ and & however only affiliations 1-7 have authors linked to them. Please amend affiliation & and ¶ to link an author to it or remove if added in error.

Our answer: This has been fixed.

We look forward to the outcome of our submission.

Sincerely,

Virginie Poka-Mayap, Dodo Balkissou Adamou, Massongo Massongo, Steve Voufouo Sonwa, Jacqueline Alime, Ben Patrick Michel Moutlen, Alfred Kongnyu Njamnshi, André Noseda And Eric Walter Pefura-Yone

Submitted filename: Response to reviewer_R3_PO_OSAHS_YCH.docx

Click here for additional data file.

30 Dec 2019

Obstructive sleep apnea and hypopnea syndrome in patients admitted in a tertiary hospital in Cameroon: prevalence and associated factors

PONE-D-19-25768R2

Dear Dr. Poka-Mayap,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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With kind regards,

James Andrew Rowley

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

8 Jan 2020

PONE-D-19-25768R2

Obstructive sleep apnea and hypopnea syndrome in patients admitted in a tertiary hospital in Cameroon: prevalence and associated factors

Dear Dr. Poka-Mayap:

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on behalf of

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