2020
DOI: 10.1093/sleep/zsaa067
|View full text |Cite
|
Sign up to set email alerts
|

An assessment of a simple clinical technique to estimate pharyngeal collapsibility in people with obstructive sleep apnea

Abstract: Study Objectives Quantification of upper airway collapsibility in obstructive sleep apnea (OSA) could help inform targeted therapy decisions. However, current techniques are clinically impractical. The primary aim of this study was to assess if a simple, novel technique could be implemented as part of a continuous positive airway pressure (CPAP) titration study to assess pharyngeal collapsibility. Methods A total of 35 partic… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
8
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 11 publications
(8 citation statements)
references
References 58 publications
0
8
0
Order By: Relevance
“…These include more scalable advanced signal processing techniques (Sands et al, 2018a,b), machine learning approaches (Dutta et al, 2021) and algorithms (Edwards et al, 2014) which simply make better use of the existing rich neurophysiological and respiratory information acquired from diagnostic polysomnography recordings and standard clinical metrics such as age and BMI. Other strategies to estimate specific OSA endotypes include estimates based on a simple intervention during a CPAP titration study (Osman et al, 2020), the therapeutic CPAP level (Landry et al, 2017) and wakefulness upper airway physiology testing (Wang et al, 2018;Osman et al, 2019). These principles and recent proof-of-concept findings have opened multiple new lines of investigation for the development of more clinically feasible and scalable approaches to help better guide targeted therapy and precision medicine for OSA.…”
Section: Osa Endotypesmentioning
confidence: 99%
“…These include more scalable advanced signal processing techniques (Sands et al, 2018a,b), machine learning approaches (Dutta et al, 2021) and algorithms (Edwards et al, 2014) which simply make better use of the existing rich neurophysiological and respiratory information acquired from diagnostic polysomnography recordings and standard clinical metrics such as age and BMI. Other strategies to estimate specific OSA endotypes include estimates based on a simple intervention during a CPAP titration study (Osman et al, 2020), the therapeutic CPAP level (Landry et al, 2017) and wakefulness upper airway physiology testing (Wang et al, 2018;Osman et al, 2019). These principles and recent proof-of-concept findings have opened multiple new lines of investigation for the development of more clinically feasible and scalable approaches to help better guide targeted therapy and precision medicine for OSA.…”
Section: Osa Endotypesmentioning
confidence: 99%
“…The pharyngeal critical closing pressure (Pcrit) is the most accurate index of upper airway collapsibility, but the invasivity and the complexity of its measurement do not make it clinically practical. With regard to this, A.M. Osman et al [ 29 ] recently presented the peak inspiratory flow percentage (PIF%) as a marker of the collapsibility of the upper airways; it is related to Pcrit and easy to obtain during a routine CPAP titration study. PIF% could represent an important opportunity to better quantify the structural collapsibility of the upper airways in clinical practice, allowing more direct estimation of the effective value of LPW surgery and optimizing, in this way, the treatment of OSAS patients.…”
Section: Discussionmentioning
confidence: 99%
“…There is growing search for simplified tools to evaluate physiological traits. [44][45][46] Considering these data it is possible to speculate that an acute CPAP challenge test (simple, accessible, and relatively inexpensive) should be built and could be an important supplementary tool in the management of patients with OSA before choosing long-term therapeutic options.…”
Section: Discussionmentioning
confidence: 99%