Literature DB >> 3605826

Accuracy of spirometric and flow-volume indices obtained by digitizing volume-time tracings.

C R O'Donnell, S L Sneddon, M Schenker, E Garshick, F E Speizer, J Mead.   

Abstract

We tested the accuracy of a new system for deriving standard spirometric indices, maximal expiratory flow rates, and slope ratios from volume-time tracings. A computer-based technique employing a hand-operated cursor was used to put discrete values of volume and time into a memory array. Spirometric values obtained on 102 subjects using the computer system were compared with the corresponding "hand-read" values. The difference between the 2 measuring techniques were not significant for the FVC, the FEV75, and the FEF25-75; however, the average FEV1 differed by 6.7 ml (SD, 20.3 ml), which was significant. In addition, 10 subjects performed FVC maneuvers through a spirometer and flowmeter connected in series. Flows and slope ratios obtained from the volume-time tracings were compared with those obtained directly from the flowmeter. There was a high degree of correlation between the 2 types of flow measurements (r = 0.989), whereas slope ratios were less well correlated (r = 0.589). Configurational detail such as the presence of "bumps" on slope ratio versus volume plots were recovered with the computer technique. Using this new system, it is possible for 1 operator to process 10 to 12 sets of spirometry tracings per hour.

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Year:  1987        PMID: 3605826     DOI: 10.1164/ajrccm/136.1.108

Source DB:  PubMed          Journal:  Am Rev Respir Dis        ISSN: 0003-0805


  2 in total

1.  Deep neural network analyses of spirometry for structural phenotyping of chronic obstructive pulmonary disease.

Authors:  Sandeep Bodduluri; Arie Nakhmani; Joseph M Reinhardt; Carla G Wilson; Merry-Lynn McDonald; Ramaraju Rudraraju; Byron C Jaeger; Nirav R Bhakta; Peter J Castaldi; Frank C Sciurba; Chengcui Zhang; Purushotham V Bangalore; Surya P Bhatt
Journal:  JCI Insight       Date:  2020-07-09

2.  New Spirometry Indices for Detecting Mild Airflow Obstruction.

Authors:  Surya P Bhatt; Nirav R Bhakta; Carla G Wilson; Christopher B Cooper; Igor Barjaktarevic; Sandeep Bodduluri; Young-Il Kim; Michael Eberlein; Prescott G Woodruff; Frank C Sciurba; Peter J Castaldi; MeiLan K Han; Mark T Dransfield; Arie Nakhmani
Journal:  Sci Rep       Date:  2018-11-30       Impact factor: 4.379

  2 in total

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