Incomplete forced expiration - estimating vital capacity by a mathematical method.

BACKGROUND: Vital capacity is a key parameter in the determination of lung function, usually assessed by means of a forced expiration maneuver. This maneuver can be exhausting, and patients often cannot complete it. OBJECTIVES: This study evaluates a method to estimate forced vital capacity (FVC) based on the extrapolation of volume-time curves from forced expiration. METHODS: The algorithm was applied to 2,363 volume-time curves from patients with and without respiratory disease. 416 of these spirograms originated from incomplete maneuvers. For each spirogram, estimated (FVC(est)) and measured FVC were compared with inspiratory vital capacity. RESULTS: Reliable FVC(est) were obtained for 82% of all and for 76% of the incomplete maneuvers. Regardless of the category of respiratory disease and acceptability of forced expiration, FVC(est) were close to inspiratory vital capacities. CONCLUSIONS: When assessing the lung function of patients who cannot complete forced expiration, this method could help to reduce the duration of maneuvers required to provide a reliable estimate for vital capacity.

Diagnosis of sleep apnea by automatic analysis of nasal pressure and forced oscillation impedance.

Detecting and differentiating central and obstructive respiratory events is an important aspect of the diagnosis of sleep-related breathing disorders with respect to the choice of an appropriate treatment. The purpose of this study was to evaluate the performance of a new algorithm for automated detection and classification of apneas and hypopneas, compared with visual analysis of standard polysomnographic signals. The algorithm is based on time series analysis of nasal mask pressure and a forced oscillation signal related to mechanical respiratory input impedance, measured at a frequency of 20 Hz throughout the night. The method was applied to all-night measurements on 19 subjects. Two experts in sleep medicine independently scored the corresponding simultaneously recorded polysomnographic signals. Evaluating the agreement between two scorers by a weighted kappa statistic on a second-by-second basis, we found that inter-expert variability and the discrepancy between automatic analysis and visual analysis performed by an expert were not significantly different. Implementation of this algorithm in a device for home monitoring of breathing during sleep might aid in the differential diagnosis of sleep-related breathing disorders and/or as a means for follow-up and treatment control.