STUDY OBJECTIVES: Sleep disordered breathing events conceptually separate into "obstructive" and "central" events. Esophageal manometry is the definitive but invasive means of classifying hypopneas. The purpose of this project was to identify noninvasive markers for discriminating high vs. low resistance hypopneas. METHODS: Forty subjects with obstructive or central sleep apnea underwent diagnostic polysomnography with nasal cannula airflow and esophageal manometry; 200% resistance relative to reference breaths was used to define "high" resistance. Noninvasive parameters from 292 randomly selected hypopneas in 20 subjects were analyzed and correlated to resistance. The best parameter and cutoff for predicting high relative resistance was determined and tested prospectively in 2 test sets in the 20 remaining subjects. Test Set A: 15 randomly selected hypopneas in each subject; Test Set B: all hypopneas in 7 subjects. RESULTS: In the development set, prolongation of inspiratory time during the 2 smallest breaths of a hypopnea (T(i)) relative to baseline had the best correlation to high relative resistance. In the Test Set A, relative T(i) > 110% classified obstructive events with sensitivity = 72%, specificity = 77%, PPV = 64%, NPV = 83%. Similar numbers were obtained for classification of hypopneas based on presence of flow limitation (FL) alone. When either relative T(i) or presence of FL were used to define high resistance, sensitivity = 84%, specificity = 74%, PPV = 65%, NPV = 89%. Similar results were obtained for Test Set B. CONCLUSIONS: Relative prolongation of T(i) is a good noninvasive predictor of high/low resistance in a dataset with both FL and NFL hypopneas. Combination of FL and relative T(i) improves this classification. The use of T(i) to separate obstructive and central hypopneas needs to be further tested for clinical utility (outcomes and treatment effects).
STUDY OBJECTIVES: Sleep disordered breathing events conceptually separate into "obstructive" and "central" events. Esophageal manometry is the definitive but invasive means of classifying hypopneas. The purpose of this project was to identify noninvasive markers for discriminating high vs. low resistance hypopneas. METHODS: Forty subjects with obstructive or central sleep apnea underwent diagnostic polysomnography with nasal cannula airflow and esophageal manometry; 200% resistance relative to reference breaths was used to define "high" resistance. Noninvasive parameters from 292 randomly selected hypopneas in 20 subjects were analyzed and correlated to resistance. The best parameter and cutoff for predicting high relative resistance was determined and tested prospectively in 2 test sets in the 20 remaining subjects. Test Set A: 15 randomly selected hypopneas in each subject; Test Set B: all hypopneas in 7 subjects. RESULTS: In the development set, prolongation of inspiratory time during the 2 smallest breaths of a hypopnea (T(i)) relative to baseline had the best correlation to high relative resistance. In the Test Set A, relative T(i) > 110% classified obstructive events with sensitivity = 72%, specificity = 77%, PPV = 64%, NPV = 83%. Similar numbers were obtained for classification of hypopneas based on presence of flow limitation (FL) alone. When either relative T(i) or presence of FL were used to define high resistance, sensitivity = 84%, specificity = 74%, PPV = 65%, NPV = 89%. Similar results were obtained for Test Set B. CONCLUSIONS: Relative prolongation of T(i) is a good noninvasive predictor of high/low resistance in a dataset with both FL and NFL hypopneas. Combination of FL and relative T(i) improves this classification. The use of T(i) to separate obstructive and central hypopneas needs to be further tested for clinical utility (outcomes and treatment effects).
Authors: S Javaheri; T J Parker; J D Liming; W S Corbett; H Nishiyama; L Wexler; G A Roselle Journal: Circulation Date: 1998-06-02 Impact factor: 29.690
Authors: R Condos; R G Norman; I Krishnasamy; N Peduzzi; R M Goldring; D M Rapoport Journal: Am J Respir Crit Care Med Date: 1994-08 Impact factor: 21.405
Authors: Sushmita Pamidi; Susan Redline; David Rapoport; Indu Ayappa; Luciana Palombini; Ramon Farre; Jason Kirkness; Jean-Louis Pépin; Olli Polo; Andrew Wellman; R John Kimoff Journal: Ann Am Thorac Soc Date: 2017-07
Authors: Dwayne L Mann; Philip I Terrill; Ali Azarbarzin; Sara Mariani; Angelo Franciosini; Alessandra Camassa; Thomas Georgeson; Melania Marques; Luigi Taranto-Montemurro; Ludovico Messineo; Susan Redline; Andrew Wellman; Scott A Sands Journal: Eur Respir J Date: 2019-07-04 Impact factor: 16.671
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