Literature DB >> 15169753

Noninvasive determination of upper airway resistance and flow limitation.

Khaled F Mansour1, James A Rowley, M Safwan Badr.   

Abstract

We have shown that a polynomial equation, FP = AP3 + BP2 + CP + D, where F is flow and P is pressure, can accurately determine the presence of inspiratory flow limitation (IFL). This equation requires the invasive measurement of supraglottic pressure. We hypothesized that a modification of the equation that substitutes time for pressure would be accurate for the detection of IFL and allow for the noninvasive measurement of upper airway resistance. The modified equation is Ft = At3 + Bt2 + Ct + D, where F is flow and t is time from the onset of inspiration. To test our hypotheses, data analysis was performed as follows on 440 randomly chosen breaths from 18 subjects. First, we performed linear regression and determined that there is a linear relationship between pressure and time in the upper airway (R2 0.96 +/- 0.05, slope 0.96 +/- 0.06), indicating that time can be a surrogate for pressure. Second, we performed curve fitting and found that polynomial equation accurately predicts the relationship between flow and time in the upper airway (R2 0.93 +/- 0.12, error fit 0.02 +/- 0.08). Third, we performed a sensitivity-specificity analysis comparing the mathematical determination of IFL to manual determination using a pressure-flow loop. Mathematical determination had both high sensitivity (96%) and specificity (99%). Fourth, we calculated the upper airway resistance using the polynomial equation and compared the measurement to the manually determined upper airway resistance (also from a pressure-flow loop) using Bland-Altman analysis. Mean difference between calculated and measured upper airway resistance was 0.0 cmH2O x l(-1) x s(-1) (95% confidence interval -0.2, 0.2) with upper and lower limits of agreement of 2.8 cmH2O x l(-1) x s(-1) and -2.8 cmH2O x l(-1) x s(-1). We conclude that a polynomial equation can be used to model the flow-time relationship, allowing for the objective and accurate determination of upper airway resistance and the presence of IFL.

Entities:  

Mesh:

Year:  2004        PMID: 15169753     DOI: 10.1152/japplphysiol.01319.2003

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN: 0161-7567


  9 in total

1.  An Examination of Methodological Paradigms for Calculating Upper Airway Critical Pressures during Sleep.

Authors:  Grace W Pien; Brendan T Keenan; Carole L Marcus; Bethany Staley; Sarah J Ratcliffe; Nicholas J Jackson; William Wieland; Yi Sun; Richard J Schwab
Journal:  Sleep       Date:  2016-05-01       Impact factor: 5.849

2.  Relative prolongation of inspiratory time predicts high versus low resistance categorization of hypopneas.

Authors:  Anne M Mooney; Khader K Abounasr; David M Rapoport; Indu Ayappa
Journal:  J Clin Sleep Med       Date:  2012-04-15       Impact factor: 4.062

3.  Compensatory responses to upper airway obstruction in obese apneic men and women.

Authors:  Chien-Hung Chin; Jason P Kirkness; Susheel P Patil; Brian M McGinley; Philip L Smith; Alan R Schwartz; Hartmut Schneider
Journal:  J Appl Physiol (1985)       Date:  2011-11-17

4.  Inspiratory airflow dynamics during sleep in irritable bowel syndrome: a pilot study.

Authors:  Avram R Gold; Joan E Broderick; Mohammad M Amin; Morris S Gold
Journal:  Sleep Breath       Date:  2009-05-29       Impact factor: 2.816

5.  Altered K-complex morphology during sustained inspiratory airflow limitation is associated with next-day lapses in vigilance in obstructive sleep apnea.

Authors:  Ankit Parekh; Korey Kam; Anna E Mullins; Bresne Castillo; Asem Berkalieva; Madhu Mazumdar; Andrew W Varga; Danny J Eckert; David M Rapoport; Indu Ayappa
Journal:  Sleep       Date:  2021-07-09       Impact factor: 5.849

6.  Weighted Polynomial Approximation for Automated Detection of Inspiratory Flow Limitation.

Authors:  Sheng-Cheng Huang; Hao-Yu Jan; Tieh-Cheng Fu; Wen-Chen Lin; Geng-Hong Lin; Wen-Chi Lin; Cheng-Lun Tsai; Kang-Ping Lin
Journal:  Comput Math Methods Med       Date:  2017-05-28       Impact factor: 2.238

7.  Endotyping Sleep Apnea One Breath at a Time: An Automated Approach for Separating Obstructive from Central Sleep-disordered Breathing.

Authors:  Ankit Parekh; Thomas M Tolbert; Anne M Mooney; Jaime Ramos-Cejudo; Ricardo S Osorio; Marcel Treml; Simon-Dominik Herkenrath; Winfried J Randerath; Indu Ayappa; David M Rapoport
Journal:  Am J Respir Crit Care Med       Date:  2021-12-15       Impact factor: 21.405

8.  Snoring: a source of noise pollution and sleep apnea predictor.

Authors:  Mudiaga Sowho; Francis Sgambati; Michelle Guzman; Hartmut Schneider; Alan Schwartz
Journal:  Sleep       Date:  2020-06-15       Impact factor: 5.849

9.  Frequency of flow limitation using airflow shape.

Authors:  Dwayne L Mann; Thomas Georgeson; Shane A Landry; Bradley A Edwards; Ali Azarbarzin; Daniel Vena; Lauren B Hess; Andrew Wellman; Susan Redline; Scott A Sands; Philip I Terrill
Journal:  Sleep       Date:  2021-12-10       Impact factor: 6.313

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.