Endoscopy evaluation to predict oral appliance outcomes in obstructive sleep apnoea

Okuno, Kentaro; Sasao, Yasuhiro; Nohara, Kanji; Sakai, Takayoshi; Pliska, Benjamin T.; Lowe, Alan A.; Ryan, C. Frank; Almeida, Fernanda R.

doi:10.1183/13993003.01088-2015

Cited by 57 publications

(34 citation statements)

References 31 publications

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“…13 However, a prospective study has found quantitative analysis of nasopharyngoscopic images in conjunction with baseline AHI to be predictive of OA outcome in Japanese patients with OSA. 19 In this study we wished to explore the influence of sex on OA treatment response. We targeted females in recruitment in an attempt to achieve sex balance, ending up with a 60:40 split of men and women.…”

Section: Discussionmentioning

confidence: 99%

Awake Multimodal Phenotyping for Prediction of Oral Appliance Treatment Outcome

Sutherland

Chan

Ngiam

et al. 2018

Journal of Clinical Sleep Medicine

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Study Objectives: An oral appliance (OA) is a validated treatment for obstructive sleep apnea (OSA). However, therapeutic response is not certain in any individual and is a clinical barrier to implementing this form of therapy. Therefore, accurate and clinically applicable prediction methods are needed. The goal of this study was to derive prediction models based on multiple awake assessments capturing different aspects of the pharyngeal response to mandibular advancement. We hypothesized that a multimodal model would provide robust prediction. Methods: Patients with OSA (apnea-hypopnea index [AHI] > 10 events/h) were recruited for treatment with a customized OA (n = 142, 59% male). Participants underwent facial photography (craniofacial structure), spirometry (mid-inspiratory flow at 50% vital capacity [MIF50] and mid-expiratory flow at 50% vital capacity [MEF50] and the ratio MEF50/MIF50) and nasopharyngoscopy (velopharyngeal collapse with Mueller maneuver and mandibular advancement). Treatment response was defined by 3 criteria: (1) AHI < 5 events/h plus ≥ 50% reduction, (2) AHI < 10 events/h plus ≥ 50% reduction, (3) ≥ 50% AHI reduction. Multivariable regression models were used to assess predictive utility of phenotypic assessments compared to clinical characteristics alone (age, sex, obesity, baseline AHI). Results: Craniofacial structure and flow-volume loops predicted treatment response. Accuracy of the prediction models (area under the receiver operating characteristic curve) for each criterion were 0.90 (criterion 1), 0.79 (criterion 2), and 0.78 (criterion 3). However, these prediction models including phenotypic assessments did not provide a statistically significant improvement over clinical predictors only. Conclusions: Multimodal awake phenotyping does not enhance OA treatment outcome prediction. These office-based, awake assessments have limited utility for robust clinical prediction models. Future work should focus on sleep-related assessments. Citation: Sutherland K, Chan AS, Ngiam J, Dalci O, Darendeliler MA, Cistulli PA. Awake multimodal phenotyping for prediction of oral appliance treatment outcome.

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Section: Discussionmentioning

confidence: 99%

Awake Multimodal Phenotyping for Prediction of Oral Appliance Treatment Outcome

Sutherland

Chan

Ngiam

et al. 2018

Journal of Clinical Sleep Medicine

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“…This finding provides the physiological framework for developing tools to discriminate between retropalatal and retroglossal contributions to OSA. Distinguishing between retropalatal and retroglossal airway collapse has implications for responses to therapies such as oral appliance therapy and pharyngeal surgery (11, 13).…”

Section: Discussionmentioning

confidence: 99%

Retropalatal and retroglossal airway compliance in patients with obstructive sleep apnea

Marques

Genta

Azarbarzin

et al. 2018

Respiratory Physiology & Neurobiology

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“…A prediction model combining the maximum CPAP pressures and baseline AHI seemed to identify a phenotypic trait not responding to OA, predicting treatment failure with high accuracy. Other methods that examine the change of upper airways dimensions during mandibular advancement, either by sleep monitoring with the simultaneous use of a remotely controlled mandibular positioner or by endoscopic evaluation, have shown promising results [ 28 , 29 ], but are invasive and operator dependent and time and cost consuming.…”

Section: Discussionmentioning

confidence: 99%

Oral appliance treatment outcome can be predicted by continuous positive airway pressure in moderate to severe obstructive sleep apnea

et al. 2017

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BackgroundStudies show that the therapeutic CPAP pressure is associated with oral appliance (OA) treatment outcome in obstructive sleep apnea (OSA) patients. However, these studies included either CPAP adherent patients using fixed pressure devices, or partly CPAP non-adherent patients using fixed pressure or auto-adjusting (auto-CPAP) devices. In many countries, auto-CPAP is predominately used, and only those non-adherent to therapy need a change to OA. Therefore, studies examining the relationship between CPAP pressures and OA treatment outcome should focus on patients non-adherent to auto-CPAP.PurposeThe purpose of this paper is to assess if CPAP pressures predicted OA treatment outcome in patients non-adherent to auto-CPAP therapy.MethodsThe OA treatment responders and non-responders were defined by two success criteria ((1) AHI < 5; (2) 5 ≤ AHI < 10 and > 50% AHI reduction). Logistic regression analyses were performed for CPAP pressures and baseline variables. ROC curve analyses were used to identify CPAP pressure cutoff values, alone and combined with other explanatory variables, predicting the OA treatment outcome.ResultsEighty-seven patients with moderate or severe OSA were included. Maximum CPAP pressures (CPAPmax) were higher in non-responders by both criteria and were, together with baseline AHI, associated with the OA treatment outcome in multivariate regression analyses. ROC curves identified an optimal CPAPmax cutoff of 12 cm H2O, corresponding to a positive predictive value (PPV) of 0.85 in predicting non-response using criterion 1. A prediction model combining CPAPmax > 12 and baseline AHI ≥ 30 had a PPV of 1.0 for non-response by both criteria.ConclusionsMaximum CPAP pressure was a moderate predictor of OA treatment outcome, but combined with baseline AHI, the ability to identify OA non-responders was high.

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Endoscopy evaluation to predict oral appliance outcomes in obstructive sleep apnoea

Cited by 57 publications

References 31 publications

Awake Multimodal Phenotyping for Prediction of Oral Appliance Treatment Outcome

Awake Multimodal Phenotyping for Prediction of Oral Appliance Treatment Outcome

Retropalatal and retroglossal airway compliance in patients with obstructive sleep apnea

Oral appliance treatment outcome can be predicted by continuous positive airway pressure in moderate to severe obstructive sleep apnea

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