Article ; Online: Diagnosis of Dry Eye Disease Using Principal Component Analysis: A Study in Animal Models of the Disease.
2021 Volume 46, Issue 5, Page(s) 622–629
Abstract: Purpose: To evaluate whether principal component analysis (PCA) can assess various diagnostic tests of dry eye disease (DED), providing a simplified, more informative measure of disease status than individual clinical test parameters (ICTP).: ... ...
Abstract | Purpose: To evaluate whether principal component analysis (PCA) can assess various diagnostic tests of dry eye disease (DED), providing a simplified, more informative measure of disease status than individual clinical test parameters (ICTP). Materials and methods: ICTP were analyzed using PCA in two groups of normal rabbits (Groups 1 and 2). Group 3, not truly normal, was also assessed. DED was induced in Group 1 by complete dacryoadenectomy; in Groups 2 and 3 by injection of concanavalin A. Tear break up time, tear osmolarity, Schirmer's tear test and rose bengal staining were the ICTP measured in all groups. Statistical analysis including descriptive statistics, t test, correlation coefficients and PCA was done. PCA using ICTP data from Group 1 generated axes; Group 2 and 3 were plotted over these axes. Results: All groups had induction of DED. Correlations for all ICTP were in the correct direction and were strongest for Group 1 and weakest in Group 3. PCA clearly separated DED and normal eyes. Principal component (PC) 1, made up of nearly equal contributions from the four clinical tests, explained 73% of the variation and provided a means to separate normal from DED. PC 1 values under 0.52 can be mathematically defined as DED. Of all pairwise comparisons, PC 1 vs PC 2 and PC 1 vs PC 3 were the most informative providing excellent spatial separation and additional information regarding DED status. Conclusions: PCA proved useful for evaluating DED providing a simpler, more comprehensive assessment than ICTP. PC 1 is a valuable, clinically relevant, and informative metric for DED status and severity having superior diagnostic value and statistical strength compared to ICTP. Spatial information on biplots of PC 1 vs PC 3 is also informative. PCA, and specifically PC 1, has the potential to serve as a biomarker for DED. |
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MeSH term(s) | Animals ; Diagnostic Techniques, Ophthalmological ; Disease Models, Animal ; Dry Eye Syndromes/diagnosis ; Dry Eye Syndromes/physiopathology ; Male ; Osmolar Concentration ; Principal Component Analysis/methods ; Rabbits ; Tears/chemistry ; Tears/physiology |
Language | English |
Publishing date | 2021-01-14 |
Publishing country | England |
Document type | Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't |
ZDB-ID | 82079-9 |
ISSN | 1460-2202 ; 0271-3683 |
ISSN (online) | 1460-2202 |
ISSN | 0271-3683 |
DOI | 10.1080/02713683.2020.1830115 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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