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Comparative study of the SleepImage ring device and polysomnography for diagnosing obstructive sleep apnea.

ABSTRACT: Purpose We aim to evaluate the diagnostic performance of the SleepImage Ring device in identifying obstructive sleep apnea (OSA) across different severity in comparison to standard polysomnography (PSG). Methods Thirty-nine patients (mean age, 56.8 ± 15.0 years; 29 [74.3%] males) were measured with the SleepImage Ring and PSG study simultaneously in order to evaluate the diagnostic performance of the SleepImage device for diagnosing OSA. Variables such as sensitivity, specificity, positive and negative likelihood ratio, positive and negative predictive value, and accuracy were calculated with PSG-AHI thresholds of 5, 15, and 30 events/h. Receiver operating characteristic curves were also built according to the above PSG-AHI thresholds. In addition, we analyzed the correlation and agreement between the apnea-hypopnea index (AHI) obtained from the two measurement devices. Results There was a strong correlation (r = 0.89, P < 0.001 and high agreement in AHI between the SleepImage Ring and standard PSG. Also, the SleepImage Ring showed reliable diagnostic capability, with areas under the receiver operating characteristic curve of 1.00 (95% CI, 0.91, 1.00), 0.90 (95% CI, 0.77, 0.97), and 0.98 (95% CI, 0.88, 1.000) for corresponding PSG-AHI of 5, 15 and 30 events/h, respectively. Conclusion The SleepImage Ring could be a clinically reliable and cheaper alternative to the gold standard PSG when aiming to diagnose OSA in adults.

Supplementary information

The online version contains supplementary material available at 10.1007/s13534-023-00304-9.

SUBMITTER: Lu M

PROVIDER: S-EPMC10382437 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Comparative study of the SleepImage ring device and polysomnography for diagnosing obstructive sleep apnea.

Lu Mi M Brenzinger Lisa L Rosenblum Lisa L Salanitro Matthew M Fietze Ingo I Glos Martin M Fico Giuseppe G Penzel Thomas T

Biomedical engineering letters 20230717 3

<i>Purpose</i> We aim to evaluate the diagnostic performance of the SleepImage Ring device in identifying obstructive sleep apnea (OSA) across different severity in comparison to standard polysomnography (PSG). <i>Methods</i> Thirty-nine patients (mean age, 56.8 ± 15.0 years; 29 [74.3%] males) were measured with the SleepImage Ring and PSG study simultaneously in order to evaluate the diagnostic performance of the SleepImage device for diagnosing OSA. Variables such as sensitivity, specificity, ...[more]

PMID: 37519866

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Project description:RationaleTherapies for obstructive sleep apnea (OSA) could be administered on the basis of a patient's own phenotypic causes ("traits") if a clinically applicable approach were available.ObjectivesHere we aimed to provide a means to quantify two key contributors to OSA-pharyngeal collapsibility and compensatory muscle responsiveness-that is applicable to diagnostic polysomnography.MethodsBased on physiological definitions, pharyngeal collapsibility determines the ventilation at normal (eupneic) ventilatory drive during sleep, and pharyngeal compensation determines the rise in ventilation accompanying a rising ventilatory drive. Thus, measuring ventilation and ventilatory drive (e.g., during spontaneous cyclic events) should reveal a patient's phenotypic traits without specialized intervention. We demonstrate this concept in patients with OSA (N = 29), using a novel automated noninvasive method to estimate ventilatory drive (polysomnographic method) and using "gold standard" ventilatory drive (intraesophageal diaphragm EMG) for comparison. Specialized physiological measurements using continuous positive airway pressure manipulation were employed for further comparison. The validity of nasal pressure as a ventilation surrogate was also tested (N = 11).Measurements and main resultsPolysomnography-derived collapsibility and compensation estimates correlated favorably with those quantified using gold standard ventilatory drive (R = 0.83, P < 0.0001; and R = 0.76, P < 0.0001; respectively) and using continuous positive airway pressure manipulation (R = 0.67, P < 0.0001; and R = 0.64, P < 0.001; respectively). Polysomnographic estimates effectively stratified patients into high versus low subgroups (accuracy, 69-86% vs. ventilatory drive measures; P < 0.05). Traits were near-identical using nasal pressure versus pneumotach (N = 11, R ≥ 0.98, both traits; P < 0.001).ConclusionsPhenotypes of pharyngeal dysfunction in OSA are evident from spontaneous changes in ventilation and ventilatory drive during sleep, enabling noninvasive phenotyping in the clinic. Our approach may facilitate precision therapeutic interventions for OSA.

Project description:ObjectivesThe present study aimed to investigate the characteristics of salivary microbiota of children with obstructive sleep apnea (OSA) and to assess longitudinal alterations in salivary microbiota before and after adenotonsillectomy.MethodsA set of cross-sectional samples consisted of 36 OSA children (17 boys and 19 girls, 7.47 ± 2.24 years old) and 22 controls (9 boys and 13 girls, 7.55 ± 2.48 years old) were included in the study, among which eight OSA children (five boys and three girls, 8.8 ± 2.0 years old) who underwent treatment of adenotonsillectomy were followed up after 1 year. Saliva samples were collected, and microbial profiles were analyzed by bioinformatics analysis based on 16S rRNA sequencing.ResultsIn cross-sectional samples, the OSA group had higher α-diversity as estimated by Chao1, Shannon, Simpson, Pielou_e, and observed species as compared with the control group (p < 0.05). β-Diversity based on the Bray-Curtis dissimilarities (p = 0.004) and Jaccard distances (p = 0.001) revealed a significant separation between the OSA group and control group. Nested cross-validated random forest classifier identified the 10 most important genera (Lactobacillus, Escherichia, Bifidobacterium, Capnocytophaga, Bacteroidetes_[G-7], Parvimonas, Bacteroides, Klebsiella, Lautropia, and Prevotella) that could differentiate OSA children from controls with an area under the curve (AUC) of 0.94. Linear discriminant analysis effect size (LEfSe) analysis revealed a significantly higher abundance of genera such as Prevotella (p = 0.027), Actinomyces (p = 0.015), Bifidobacterium (p < 0.001), Escherichia (p < 0.001), and Lactobacillus (p < 0.001) in the OSA group, among which Prevotella was further corroborated in longitudinal samples. Prevotella sp_HMT_396 was found to be significantly enriched in the OSA group (p = 0.02) with significantly higher levels as OSA severity increased (p = 0.014), and it had a lower abundance in the post-treatment group (p = 0.003) with a decline in each OSA child 1 year after adenotonsillectomy.ConclusionsA significantly higher microbial diversity and a significant difference in microbial composition and abundance were identified in salivary microbiota of OSA children compared with controls. Meanwhile, some characteristic genera (Prevotella, Actinomyces, Lactobacillus, Escherichia, and Bifidobacterium) were found in OSA children, among which the relationship between Prevotella spp. and OSA is worth further studies.

Project description:Background/Objectives: Factors underlying excessive daytime sleepiness (EDS) in obstructive sleep apnea (OSA) are not fully understood. We investigated whether polysomnography (PSG) parameters differed between non-sleepy and sleepy (based on the Epworth Sleepiness Scale (ESS)) OSA patients with the same disease severity, which may play a role in the presence of EDS. Methods: A total of 1307 patients, without cardiovascular, metabolic, respiratory, or inflammatory comorbidities, diagnosed with OSA (apnea-hypopnea index (AHI) ≥ 5 per hour of sleep) with type 1 PSG were included. Based on the AHI, patients were classified into mild- (AHI 5-14.9, n = 236), moderate- (AHI 15-29.9, n = 367), and severe-OSA (AHI ≥ 30, n = 704) groups. These groups were further divided into two subgroups based on the ESS, the most convenient and widely used tool to assess excessive daytime sleepiness: sleepy (ESS > 10) and non-sleepy (ESS ≤ 10). PSG data were compared between groups, and multivariable logistic regression was used to identify differences after adjustment for confounders. Results: For the entire population, male sex, younger age, obesity, depression, increased wakefulness after sleep onset (WASO), the arousal index, shorter sleep latency, and all indices of OSA severity (AHI, oxygen desaturation index, mean and lowest resting room air pulse oximetry (SpO2), and sleep time with oxygen saturation < 90% (TST90)) were significantly associated with EDS. The arousal index consistently showed a strong association with EDS across all OSA severity groups. Moderate-OSA sleepy patients were younger, with shorter sleep latency and increased indices of OSA severity, excluding the AHI. Severe-OSA sleepy patients were younger, males, and obese; had depression, decreased slow-wave sleep (SWS) and sleep latency, and increased WASO; and presented an increase in all indices of OSA severity. Conclusions: Our results suggest that male sex, younger age, obesity, the presence of depression, WASO, lower sleep efficiency, the arousal index, and all indices of OSA severity may account for the presence or absence of EDS in OSA patients and could be useful for exploring the underlying pathophysiological mechanisms for precision medicine.

Dataset Information

Comparative study of the SleepImage ring device and polysomnography for diagnosing obstructive sleep apnea.

Supplementary information

Publications

Comparative study of the SleepImage ring device and polysomnography for diagnosing obstructive sleep apnea.

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