A mathematical model to detect inspiratory flow limitation during sleep.

The physiological significance of inspiratory flow limitation (IFL) has recently been recognized, but methods of detecting IFL can be subjective. We sought to develop a mathematical model of the upper airway pressure-flow relationship that would objectively detect flow limitation. We present a theoretical discussion that predicts that a polynomial function [F(P) = AP(3) + BP(2) + CP + D, where F(P) is flow and P is supraglottic pressure] best characterizes the pressure-flow relationship and allows for the objective detection of IFL. In protocol 1, step 1, we performed curve-fitting of the pressure-flow relationship of 20 breaths to 5 mathematical functions and found that highest correlation coefficients (R(2)) for quadratic (0.88 +/- 0.10) and polynomial (0.91 +/- 0.05; P < 0.05 for both compared with the other functions) functions. In step 2, we performed error-fit calculations on 50 breaths by comparing the quadratic and polynomial functions and found that the error fit was lowest for the polynomial function (3.3 +/- 0.06 vs. 21.1 +/- 19.0%; P < 0.001). In protocol 2, we performed sensitivity/specificity analysis on two sets of breaths (50 and 544 breaths) by comparing the mathematical determination of IFL to manual determination. Mathematical determination of IFL had high sensitivity and specificity and a positive predictive value (>99% for each). We conclude that a polynomial function can be used to predict the relationship between pressure and flow in the upper airway and objectively determine the presence of IFL.

[1]  D. Rapoport,et al.  Classification of sleep-disordered breathing. , 2001, American journal of respiratory and critical care medicine.

[2]  Carolyn Craggs,et al.  Statistics in Research: Basic Concepts and Techniques for Research Workers. , 1989 .

[3]  B. Wuyam,et al.  Characterization of pharyngeal resistance during sleep in a spectrum of sleep-disordered breathing. , 2000, Journal of applied physiology.

[4]  D. Rapoport,et al.  Detection of flow limitation with a nasal cannula/pressure transducer system. , 1998, American journal of respiratory and critical care medicine.

[5]  D. Rapoport,et al.  Non-Invasive detection of respiratory effort-related arousals (REras) by a nasal cannula/pressure transducer system. , 2000, Sleep.

[6]  J. Rowley,et al.  Influence of gender on upper airway mechanics: upper airway resistance and Pcrit. , 2001, Journal of applied physiology.

[7]  C Guilleminault,et al.  A cause of excessive daytime sleepiness. The upper airway resistance syndrome. , 1993, Chest.

[8]  M. M. Mozell,et al.  Numerical simulation of airflow in the human nasal cavity. , 1995, Journal of biomechanical engineering.

[9]  Richard Edwin Sonntag,et al.  Fundamentals of Thermodynamics , 1998 .

[10]  W A Whitelaw,et al.  Interaction of cross-sectional area, driving pressure, and airflow of passive velopharynx. , 1997, Journal of applied physiology.

[11]  Badr Ms,et al.  Long-term facilitation of ventilation in humans during NREM sleep. , 1998 .

[12]  C Hendricks,et al.  Characteristics of the upper airway pressure-flow relationship during sleep. , 1988, Journal of applied physiology.

[13]  A. V. Pollock How to Report Statistics in Medicine , 2001 .

[14]  J. Skatrud,et al.  Effect of induced hypocapnic hypopnea on upper airway patency in humans during NREM sleep. , 1997, Respiration physiology.

[15]  I Schnittger,et al.  Upper airway resistance syndrome, nocturnal blood pressure monitoring, and borderline hypertension. , 1996, Chest.

[16]  N. Collop,et al.  The upper airway resistance syndrome. , 1999, Chest.

[17]  G. Ferretti,et al.  Somnofluoroscopy, computed tomography, and cephalometry in the assessment of the airway in obstructive sleep apnoea. , 1992, Thorax.

[18]  Robert Schrek,et al.  Statistics in Research. Basic Concepts and Techniques for Research Workers , 1955 .