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. 2025 Apr 14;11(2):00682-2024. doi: 10.1183/23120541.00682-2024

Clinical characteristics of obstructive sleep apnoea patients with residual sleepiness

Xujun Feng 1,3, Ye Zhang 1,3, Yuan Shi 1, Rong Ren 1, Fei Lei 1, Micheal V Vitiello 2, Xiangdong Tang 1,✉
PMCID: PMC11995279  PMID: 40230430

Abstract

Objective

This meta-analysis examines the clinical characteristics of continuous positive airway pressure (CPAP)-treated obstructive sleep apnoea (OSA) patients with residual excessive sleepiness (RES).

Method

We conducted a search for articles published from inception to 16 March 2024 in PubMed, Embase, Cochrane Library and Web of Science. Seven studies were included in this meta-analysis.

Results

The meta-analysis revealed that CPAP-treated OSA patients with RES were characterised by higher Epworth sleepiness scale and depression scale scores, lower body mass index (BMI) and apnoea–hypopnoea index (AHI) before CPAP treatment. RES patients also exhibit poorer CPAP adherence. Being female was also associated with RES.

Conclusion

Being female, having lower BMI and AHI, more severe daytime sleepiness and depressive symptoms before CPAP treatment, and lower CPAP adherence were characteristics of OSA patients with RES. These factors may prove helpful in identifying CPAP-treated OSA patients who may need additional treatment to minimise RES.

Shareable abstract

Residual excessive sleepiness (RES) is not uncommon in CPAP-treated OSA patients. Being female, having lower BMI and AHI, more severe daytime sleepiness and depressive symptoms before CPAP, and lower CPAP adherence were characteristics of RES-OSA patients. https://bit.ly/3XU9LEi

Introduction

Obstructive sleep apnoea (OSA) is characterised by recurrent partial or complete upper airway obstruction during sleep. A recent estimate of prevalence revealed that the number of OSA patients is 936 million worldwide [1]. Previous studies have suggested that OSA is significantly associated with the development of cardiovascular–metabolic diseases, such as systemic hypertension, cardiac arrhythmias and diabetes mellitus [2–5], and significantly increased the risk of all-cause mortality [6–9].

Excessive daytime sleepiness (EDS) is commonly seen in OSA patients [10, 11]. Previous studies reported that OSA with EDS is a more severe clinical phenotype of the disease [12–14] and significantly increased the risk of cardiovascular diseases (CVDs) [12, 13]. Moreover, EDS has been linked to a decreased quality of life [15] and an increased risk of motor vehicle accidents [16, 17]. Thus, the development of effective interventions for EDS in OSA is clinically important.

Continuous positive airway pressure (CPAP), the first-line treatment for OSA [18], is helpful for alleviating EDS [19, 20]. However, 7–30% of OSA patients with CPAP treatment still show EDS, which has been termed residual excessive sleepiness (RES) [21–23]. RES adversely impacts the safety, mood and cognitive function of OSA patients [23–25]. Clinically, RES commonly requires additional treatment [26]. However, it is challenging to identify individuals with RES at baseline before CPAP begins, which would be clinically useful for optimising OSA treatment. To date, the clinical characteristics of OSA patients with versus without RES are not completely understood.

Previous studies have explored the clinical characteristics of RES, including demographic characteristics, clinical symptoms, comorbidities, severity of OSA and CPAP adherence, but findings have been inconsistent [27, 28]. We conducted this first meta-analysis of the topic to better delineate the pre-treatment characteristics of CPAP-treated OSA patients with and without RES.

Methods

This meta-analysis adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The protocol has been registered (CRD42024495891).

Search strategy

PubMed, Embase, Cochrane Library and Web of Science were searched from inception to 16 March 2024. The specific search strategy is described in the supplementary material. We also reviewed the reference lists of all original studies and relevant reviews to identify additional eligible studies.

Inclusion and exclusion criteria

Included studies met the following criteria: 1) participants should be OSA patients who received CPAP treatment; 2) the studies included comparisons in demographic characteristics (i.e., sex, age and body mass index (BMI)), clinical symptoms (i.e., EDS and depressive symptoms), comorbidities (i.e., systemic hypertension, diabetes mellitus and CVD), severity of OSA or polysomnography (PSG)-measured sleep parameters at baseline (pre-treatment) and CPAP adherence (i.e., average duration of CPAP use per night); 3) OSA diagnosed by PSG or a home sleep apnoea test measuring the apnoea–hypopnoea index (AHI) or respiratory disturbance index (RDI) [29, 30]; and 4) RES after CPAP was identified by Epworth sleepiness scale (ESS) scores >10 in OSA patients. Papers were required to be published in peer-reviewed English journals. In the case of multiple publications on the same study, we selected the paper with the most relevant information to avoid duplication.

We excluded studies that 1) included OSA patients who were not adequately treated (defined as residual AHI/RDI ≥10 events·h−1 after CPAP treatment), 2) reported that all their participants were OSA patients with comorbid post-traumatic stress disorder and 3) reported patients receiving OSA treatments other than CPAP, such as mandibular advancement devices and surgery. We also excluded case reports, statements, reviews, editorials, comments, letters and conference abstracts.

Study selection

After removing duplicates, two authors (X.J.F. and Y.S.) independently screened titles and abstracts of articles and then reviewed full texts of potentially eligible articles according to the inclusion and exclusion criteria. Discrepancies were resolved through discussion with a senior author.

Data collection

Two researchers (X.J.F. and Y.S.) independently entered the data into an Excel spreadsheet and cross-checked their results. In the case of discrepancies, a consensus was reached through discussion with a senior author (X.D.T. or Y.Z.). The extracted information included demographic characteristics (i.e., sex, age and BMI), clinical symptoms (i.e., scores of EDS and depression symptoms), comorbidities (i.e., rates of systemic hypertension, diabetes mellitus and CVD), AHI and PSG-measured sleep parameters at baseline, and CPAP adherence.

Quality assessment

Studies were assessed using the Newcastle–Ottawa scale [31] by two independent researchers (X.J.F. and Y.S.) to evaluate the quality and risk of bias of included studies. In cases of discrepancies during quality assessment, the two authors discussed and decided jointly. If consensus was not reached after discussion, a senior author (Y.Z.) made the decision.

Statistical analysis

All analyses were performed by RevMan and STATA software. For continuous variables, mean values, standard deviations and sample sizes were entered separately to calculate the weighted mean difference (WMD) and 95% confidence intervals. When measurement standards (i.e., depressive symptoms) were inconsistent, standardised mean difference and 95% confidence intervals were used. For binary variables, results were presented as odd ratios (ORs) and 95% CIs. We first used multivariate-adjusted OR and relative risk, followed by OR and relative risk with univariate logistic regression. If specific OR and relative risk values were not provided, we calculated ORs according to the following formula: OR=(P1/1−P1)/(P0/1−P0) and OR=[(1-P0)/(1-P0*relative risk)]*relative risk [32], where P1 and P0 indicate the incidence rates of the outcome of interest in the RES group and in the group without RES, respectively [32]. The I2 statistic was used to evaluate the heterogeneity among included studies. A random-effects model was used to estimate the pooled effect size in our meta-analysis [33]. Where possible, the Egger regression method was used to examine publication bias. A subgroup analysis was performed according to whether the participants were only OSA patients who had an ESS score >10 before CPAP. Publication bias was not evaluated for these analyses due to the limited number of available studies.

Results

Study selection

The literature search identified 948 publications and one additional publication obtained through other sources. After removing duplicates, the titles and abstracts of the remaining 611 articles were screened. A total of 25 studies were selected for full-text review with seven found eligible for inclusion in the meta-analysis (figure 1).

FIGURE 1.

FIGURE 1

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Flow diagram for the search strategy. RES: residual excessive sleepiness.

Description of the included studies

The seven selected studies included a total of 2245 OSA patients with sample sizes ranging from 30 to 1047 and follow-up periods ranged from ≥3 to ≥12 months. The mean age of OSA patient samples ranged from 48.1 to 61.8 years old and the sample percentages of male patients ranged from 53.3% to 75% (table 1).

TABLE 1.

Characteristics and quality assessment of studies

Study, year Sample size Age (years) Percentage male Mean BMI (kg·m-2) CPAP usage time (h·night−1) Follow-up duration (months) Quality score
Werli et al. [25], 2016 15 RES 51.0±8.4 53.3 33.5±5.6 >4 (≥70% of sleep time) ≥12 7
15 non-RES 51.8±8.2 73.3 33.4±4.4
Vernet et al. [27], 2011 20 RES 61.1±9.9 75.0 31.3±5.4 >6 (>90% of nights) >6 7
20 non-RES 61.8±9.0 65.0 35.4±9.2
Koutsourelakis et al. [28], 2009 114 RES 57.8±12.5 73.7 33.9±8.3 >4  ≥6 7
94 non-RES 50.7±12.2 86.2 34.2±7.1
Pepin et al. [42], 2009 30 RES 54±12 70.0 31±5 >3 >12 6
377 non-RES 60±11 80.0 32±6
Gasa et al. [45], 2013 135 RES 56.12±11.55 60.0 31.14± 6.11 ≥3 ≥3 7
912 non-RES 57.56±12.57 71.0 32.08 ±6.65
Pascoe et al. [57], 2022 24 RES 54.4±12.3 58.3 39.8±10.6 ≥4 ≥3 7
95 non-RES 48.1±12.4 68.4 37.9±8.2
Budhiraja et al. [43], 2017 88 RES 51.2±12.5 67.0 31.6±6.8 NR ≥6 6
306 non-RES 53.0±12.0 65.4 32.2±7.3
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BMI: body mass index; CPAP: continuous positive airway pressure; NR: not reported; RES: residual excessive sleepiness.

Meta-analysis

CPAP-treated OSA patients with RES were more likely to be female, had lower BMI and AHI, and greater severity of depressive symptoms and higher ESS pre-treatment scores compared with those without RES (p<0.05). Patients with RES had a lower average duration of CPAP use per night during treatment compared with those without RES (p<0.05). There were no statistically significant differences in age or in rates of comorbidities (systemic hypertension, diabetes mellitus and CVD) between groups (figures 2–4).

FIGURE 2.

FIGURE 2

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Forest plots presenting baseline a) sex, b) age and c) body mass index (BMI) difference between groups with and without residual excessive sleepiness (RES). IV: inverse variance; OSA: obstructive sleep apnoea.

FIGURE 4.

FIGURE 4

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Forest plots presenting the association between a) depression questionnaire scales and b) Epworth Sleepiness Scale scores pre-treatment and residual excessive sleepiness (RES); and presenting the c) average usage of continuous positive airway pressure per night and d) baseline apnoea–hypopnoea index (AHI) difference between groups with and without RES. OSA: obstructive sleep apnoea; SMD: standardised mean difference.

FIGURE 3.

FIGURE 3

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Forest plots presenting the association between a) systemic hypertension , b) diabetes mellitus, c) cardiovascular disease and residual excessive sleepiness.

When analyses were restricted to the two studies that included only OSA patients with EDS before CPAP, CPAP-treated OSA patients with RES were significantly older (WMD 6.88, 95% CI 4.01–9.76) than those without RES. By comparison, when analyses were restricted to the three studies that included OSA patients both with and without EDS at baseline, the RES groups were younger compared to those without RES (WMD −2.44, 95% CI −4.68–−0.20) (Table S1).

Discussion

To our knowledge, this is the first meta-analysis to explore the baseline clinical characteristics of CPAP-treated OSA patients that are associated with RES. Our findings revealed that female OSA patients are more likely to show RES. Furthermore, CPAP-treated OSA patients with RES are more likely to have lower BMI and AHI, more severe EDS and depressive at baseline, and lower CPAP adherence compared to those without RES. Interestingly, there were no significant differences in basic rates of systemic hypertension, diabetes mellitus and CVD between patients with and without RES.

Previous studies have shown that female OSA patients have a 1.2-fold higher risk of discontinuing CPAP treatment compared to male patients [34] and Patel et al. [35] reported that female OSA patients have shorter average daily CPAP usage times compared with male patients. As even slight extensions of CPAP usage time can significantly decrease ESS scores [36–38], it is likely that lower CPAP adherence in female OSA patients may contribute to the presence of RES, consistent with the association of being female with CPAP-treated RES found in our meta-analysis. Similarly, it has been shown that female OSA patients commonly have lower AHI compared to male OSA patients [39, 40]. Thus, the higher proportion of female patients with RES may partly explain the lower AHI in RES patients compared to those without RES in our meta-analysis. Finally, as AHI has been shown to be positively associated with BMI in OSA patients [41], this may contribute to the lower BMI in patients with RES compared to those without RES found in our meta-analysis. We attempted to analyse the associations of the proportion of females across different studies with the characteristics of patients with RES, but were unable to do so due to the limitations of the available data. For an adequate assessment of the contributions of sex, BMI, AHI and their possible interactions with RES, more studies evaluating these factors are needed.

Our findings also suggest that, in RES patients, baseline EDS is more severe compared to in patients without RES, consistent with previous reports of high baseline ESS scores being a significant risk factor for CPAP-treated RES [42–45]. Increased baseline EDS severity may reflect more severe dysfunction in central arousal neurons resulting from hypoxia [46, 47], which may be improved by CPAP. Previous meta-analyses have reported that the ESS scores of OSA patients decrease by an average of 2.14–2.33 with CPAP treatment [48, 49]. However, in OSA patients with severe EDS (ESS ≥16) [50], a decrease of two to three points with CPAP treatment is insufficient to meet the criteria for non-EDS (ESS ≤10). This suggests that there is a range or limit to the improvement of OSA-related EDS by CPAP and that CPAP cannot completely reverse EDS in cases of very severe EDS prior to treatment. For instance, our meta-analysis revealed that, except for baseline EDS, RES patients showed more severe depressive symptoms compared with those without RES, indicating a link between baseline depressive symptoms and RES. Previous studies have reported that the prevalence of depression in OSA patients is 48.1% [51] and the comorbidity of depression is significantly associated with decreased CPAP adherence [52]. This may limit the effects of CPAP on EDS, contributing to RES. Thus, the comorbidity of depression with OSA should be closely monitored and effectively treated [53].

Regarding comorbidities beyond depression, systemic hypertension, diabetes mellitus and CVD are commonly seen in OSA patients. OSA patients with these comorbidities show an increased risk of mortality compared with those without [54, 55]. In recent years, the study of symptom phenotype has become a research hot spot in the field of OSA [56]. For OSA, the presence of EDS is associated with poor clinical prognosis. EDS has been identified as a potential independent prognostic factor for adverse outcomes in post-myocardial infarction patients suffering from moderate to severe sleep-disordered breathing [14]. Inadequate improvement in EDS among OSA patients undergoing CPAP treatment may correlate with an unfavourable prognosis in this cohort. Mazzotti et al. [12] classified 1207 OSA patients into four symptom subtypes, namely disturbed sleep, minimally symptomatic, excessively sleepy, and moderately sleepy. Of these, the excessively sleepy subtype was associated with a more increased risk of heart failure compared to the other subtypes [13]. While there were no significant associations between comorbidities and RES in our meta-analysis, it remains important to consider the co-occurrence of comorbidities and OSA patients with RES given their respectively demonstrated associations with poor clinical prognosis.

This review has several limitations. First, the number of the included studies is small and publication bias could not be formally evaluated. Second, the differences in baseline PSG-measured sleep architecture between patients with and without CPAP-treated RES could not be explored due to limited data on variables. Third, it should be noted that the diagnostic criteria of OSA and duration of CPAP treatment varied across studies, which could have biased our findings and is an important factor that should be explored in future research. Thus, our findings should be interpreted with caution. More high-quality studies with larger sample sizes and comprehensively assessed variables of interest are clearly warranted.

Conclusion

The current meta-analysis revealed clinical characteristics associated with RES, such as more severe EDS and depressive symptoms at baseline, and poorer CPAP adherence during therapy. Female gender, lower BMI and AHI before CPAP were associated with the development of RES following treatment. These findings are helpful for identifying at baseline individuals who may manifest RES during CPAP treatment and may be clinically useful for optimising OSA treatment.

Lessons for clinicians and questions for future research

  • Being female, having lower BMI and AHI, and more severe EDS and depressive symptoms before CPAP treatment, and lower CPAP adherence were characteristics of RES in CPAP-treated OSA patients.

  • It is important to identify the predictors and risk factors of RES, which would be clinically useful for optimising OSA treatment. There is need for more high-quality studies with larger sample sizes and comprehensively assessed variables of interest.

Supplementary material

Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.

Supplementary material 00682-2024.SUPPLEMENT (90.5KB, pdf)

Supplementary material 00682-2024.SUPPLEMENT2 (34.1KB, pdf)

Footnotes

Provenance: Submitted article, peer reviewed.

Author contributions: All authors contributed to the study conception and design. Writing – original draft preparation: X. Feng, Y. Shi, R. Ren, M.V. Vitiello, Y. Zhang and X. Tang; writing – review and editing: X. Feng, Y. Shi and M.V. Vitiello; conceptualisation: Y. Zhang and X. Tang; methodology: R. Ren and F. Lei; formal analysis and investigation: X. Feng and Y. Shi; funding acquisition: X. Tang; resources: X. Tang; supervision: Y. Zhang, M.V. Vitiello and X. Tang. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Conflict of interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Support statement: This work was supported by the Ministry of Science and Technology of the People's Republic of China (STI2030-Major Projects2021ZD0201900). Funding information for this article has been deposited with the Crossref Funder Registry.

Data availability

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.

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Associated Data

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Supplementary Materials

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Supplementary material 00682-2024.SUPPLEMENT (90.5KB, pdf)

Supplementary material 00682-2024.SUPPLEMENT2 (34.1KB, pdf)

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.

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