Literature DB >> 30373687

Awake Multimodal Phenotyping for Prediction of Oral Appliance Treatment Outcome.

Kate Sutherland1,2,3, Andrew S L Chan1,2, Joachim Ngiam1,2, Oyku Dalci4, M Ali Darendeliler4, Peter A Cistulli1,2,3.   

Abstract

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. COMMENTARY: A commentary on this article appears in this issue on page 1837. CLINICAL TRIAL REGISTRATION: Registry: Australian New Zealand Clinical Trials Registry, Title: Multimodal phenotyping for the prediction of oral appliance treatment outcome in obstructive sleep apnoea, Identifier: ACTRN12611000409976, URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336663.
© 2018 American Academy of Sleep Medicine.

Entities:  

Keywords:  mandibular advancement; obstructive sleep apnea; oral appliance therapy; sex; treatment outcome prediction

Mesh:

Year:  2018        PMID: 30373687      PMCID: PMC6223562          DOI: 10.5664/jcsm.7484

Source DB:  PubMed          Journal:  J Clin Sleep Med        ISSN: 1550-9389            Impact factor:   4.062


  30 in total

1.  Mandibular advancement and obstructive sleep apnoea: a method for determining effective mandibular protrusion.

Authors:  L C Dort; E Hadjuk; J E Remmers
Journal:  Eur Respir J       Date:  2006-05       Impact factor: 16.671

2.  Nasopharyngoscopic evaluation of oral appliance therapy for obstructive sleep apnoea.

Authors:  A S L Chan; R W W Lee; V K Srinivasan; M A Darendeliler; R R Grunstein; P A Cistulli
Journal:  Eur Respir J       Date:  2009-09-24       Impact factor: 16.671

3.  Oral Appliance Treatment Response and Polysomnographic Phenotypes of Obstructive Sleep Apnea.

Authors:  Kate Sutherland; Hisashi Takaya; Jin Qian; Peter Petocz; Andrew T Ng; Peter A Cistulli
Journal:  J Clin Sleep Med       Date:  2015-08-15       Impact factor: 4.062

4.  Performance of Remotely Controlled Mandibular Protrusion Sleep Studies for Prediction of Oral Appliance Treatment Response.

Authors:  Kate Sutherland; Joachim Ngiam; Peter A Cistulli
Journal:  J Clin Sleep Med       Date:  2017-03-15       Impact factor: 4.062

5.  Therapeutic CPAP Level Predicts Upper Airway Collapsibility in Patients With Obstructive Sleep Apnea.

Authors:  Shane A Landry; Simon A Joosten; Danny J Eckert; Amy S Jordan; Scott A Sands; David P White; Atul Malhotra; Andrew Wellman; Garun S Hamilton; Bradley A Edwards
Journal:  Sleep       Date:  2017-06-01       Impact factor: 5.849

6.  Use of flow-volume curves to predict oral appliance treatment outcome in obstructive sleep apnea: a prospective validation study.

Authors:  Andrew S L Chan; Richard W W Lee; Vasantha K Srinivasan; M Ali Darendeliler; Peter A Cistulli
Journal:  Sleep Breath       Date:  2010-07-29       Impact factor: 2.816

7.  Craniofacial phenotyping in obstructive sleep apnea--a novel quantitative photographic approach.

Authors:  Richard W W Lee; Andrew S L Chan; Ronald R Grunstein; Peter A Cistulli
Journal:  Sleep       Date:  2009-01       Impact factor: 5.849

8.  Endoscopy evaluation to predict oral appliance outcomes in obstructive sleep apnoea.

Authors:  Kentaro Okuno; Yasuhiro Sasao; Kanji Nohara; Takayoshi Sakai; Benjamin T Pliska; Alan A Lowe; C Frank Ryan; Fernanda R Almeida
Journal:  Eur Respir J       Date:  2016-01-07       Impact factor: 16.671

9.  Optimal positive airway pressure predicts oral appliance response to sleep apnoea.

Authors:  S Tsuiki; M Kobayashi; K Namba; Y Oka; Y Komada; T Kagimura; Y Inoue
Journal:  Eur Respir J       Date:  2009-10-19       Impact factor: 16.671

10.  Remotely controlled mandibular protrusion during sleep predicts therapeutic success with oral appliances in patients with obstructive sleep apnea.

Authors:  John Remmers; Shouresh Charkhandeh; Joshua Grosse; Zbigniew Topor; Rollin Brant; Peter Santosham; Sabina Bruehlmann
Journal:  Sleep       Date:  2013-10-01       Impact factor: 5.849

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  7 in total

1.  The relationship between specific nasopharyngoscopic features and treatment deterioration with mandibular advancement devices: a prospective study.

Authors:  Eli Van de Perck; Sara Op de Beeck; Marijke Dieltjens; Anneclaire V Vroegop; Annelies E Verbruggen; Marc Willemen; Johan Verbraecken; Paul H Van de Heyning; Marc J Braem; Olivier M Vanderveken
Journal:  J Clin Sleep Med       Date:  2020-07-15       Impact factor: 4.062

2.  Polysomnographic Endotyping to Select Patients with Obstructive Sleep Apnea for Oral Appliances.

Authors:  Ahmad A Bamagoos; Peter A Cistulli; Kate Sutherland; Melanie Madronio; Danny J Eckert; Lauren Hess; Bradley A Edwards; Andrew Wellman; Scott A Sands
Journal:  Ann Am Thorac Soc       Date:  2019-11

Review 3.  Oral Appliance Therapy for Obstructive Sleep Apnoea: State of the Art.

Authors:  Kate Sutherland; Peter A Cistulli
Journal:  J Clin Med       Date:  2019-12-02       Impact factor: 4.241

4.  Optimizing Mandibular Advancement Maneuvers during Sleep Endoscopy with a Titratable Positioner: DISE-SAM Protocol.

Authors:  Patricia Fernández-Sanjuán; Juan José Arrieta; Jaime Sanabria; Marta Alcaraz; Gabriela Bosco; Nuria Pérez-Martín; Adriana Pérez; Marina Carrasco-Llatas; Isabel Moreno-Hay; Marcos Ríos-Lago; Rodolfo Lugo; Carlos O'Connor-Reina; Peter Baptista; Guillermo Plaza
Journal:  J Clin Med       Date:  2022-01-27       Impact factor: 4.964

5.  Mandibular advancement devices in obstructive sleep apnea: an updated review.

Authors:  Izabella Paola Manetta; Dominik Ettlin; Pedro Mayoral Sanz; Isabel Rocha; Miguel Meira E Cruz
Journal:  Sleep Sci       Date:  2022 Apr-Jun

6.  Prediction of Mandibular Advancement Device Response Using CPAP Pressure in Different Polysomnographic Phenotypes.

Authors:  Chien-Feng Lee; Yunn-Jy Chen; Wen-Chi Huang; Jen-Wen Hou; Yu-Ting Liu; Tiffany Ting-Fang Shih; Pei-Lin Lee; Chong-Jen Yu
Journal:  Nat Sci Sleep       Date:  2022-03-25

Review 7.  A consideration of factors affecting palliative oral appliance effectiveness for obstructive sleep apnea: a scoping review.

Authors:  Bruce S Haskell; Michael J Voor; Andrew M Roberts
Journal:  J Clin Sleep Med       Date:  2021-04-01       Impact factor: 4.062

  7 in total

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