Computer categorization of spirometry data using statistical methods

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Publication Type thesis
School or College School of Medicine
Department Biomedical Informatics
Author Beus, Michael Lynn
Title Computer categorization of spirometry data using statistical methods
Date 1982-12
Description A statistical method for evaluating spirometry has been developed and proposed as a more acceptable criteria for categorizing airway obstruction and chest restriction disorders. The lower limit of normal for a predicted value was determined by calculating 95% confidence interval (CI) for each spirometric measurement. By choosing multiples of 95% CI, categories of severity were established. The impact from implementing the statistical method was measured by performing a retrospective analysis of 1390 patients present to the LDS Hospital Pulmonary Laboratory. Comparisons of the new statistical and the older Intermountain Thoracic Society (ITS) criteria were performed to identify which patients would be affected. It was found that more old and short subjects tend to be categorized as normal (or with a less severe categorization) with the statistical method then with the ITS criteria. The opposite was found for young and tall patients. Therefore, the patients most affected were those located at extremes of age and height. Another purpose of this study was to comare the FEV1/FVC% with the FE25-75%, FEV1, FEV3, FEV3/FVC%, and FEF25-75/FVC for their ability to detect abnormal airway obstruction. In all cases the FEV1/FVC% detected more abnormal cases.
Type Text
Publisher University of Utah
Subject Lactic Acid; Blood Gases
Subject MESH Spirometry; Computers; Computer Systems
Dissertation Institution University of Utah
Dissertation Name MS
Language eng
Relation is Version of Digital reproduction of "Computer categorization of spirometry data using statistical methods". Spencer S. Eccles Health Sciences Library. Print version of "Computer categorization of spirometry data using statistical methods". available at J. Willard Marriott Library Special Collection. R 117.5 1982 B48.
Rights Management © Michael Lynn Beus.
Format Medium application/pdf
Format Extent 1,573,303 bytes
Identifier undthes,4462
Source Original: University of Utah Spencer S. Eccles Health Sciences Library (no longer available).
Master File Extent 1,573,343 bytes
ARK ark:/87278/s6ft8ntg
Setname ir_etd
ID 190703
Reference URL https://collections.lib.utah.edu/ark:/87278/s6ft8ntg