July 2019
Volume 60, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2019
Test efficacy of the fluorescein breakup time test in the diagnosis of dry eye – a re-examination
Author Affiliations & Notes
  • Jerry R Paugh
    SCCO at Marshall B. Ketchum University, Irvine, California, United States
  • Elaine Chen
    SCCO at Marshall B. Ketchum University, Irvine, California, United States
  • June Tse
    Private Practice , California, United States
  • Tiffany Nguyen
    Private Practice, Alaska, United States
  • Alan Sasai
    SCCO at Marshall B. Ketchum University, Irvine, California, United States
  • Melinda Thomas DeJesus
    Private Practice, California, United States
  • Justin Kwan
    Private Practice , California, United States
  • Andrew Nguyen
    Mathematics, California State University, Fullerton, California, United States
  • Marjan Farid
    Ophthalmology, University of California at Irvine, California, United States
  • Sumit Garg
    Ophthalmology, University of California at Irvine, California, United States
  • James V Jester
    Biomedical Engineering, University of California at Irvine, Irvine, California, United States
    Gavin Herbert Eye Institute, University of California at Irvine, Irvine, California, United States
  • Footnotes
    Commercial Relationships   Jerry Paugh, Alcon Research, Ltd (F); Elaine Chen, None; June Tse, None; Tiffany Nguyen, None; Alan Sasai, None; Melinda Thomas DeJesus, None; Justin Kwan, None; Andrew Nguyen, None; Marjan Farid, None; Sumit Garg, None; James Jester, None
  • Footnotes
    Support  Supported in part by an Investigator Initiated Trial grant (JP), NEI EY021510 (JJ) and supported by an RPB Unrestricted Grant.
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 6788. doi:
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    • Get Citation

      Jerry R Paugh, Elaine Chen, June Tse, Tiffany Nguyen, Alan Sasai, Melinda Thomas DeJesus, Justin Kwan, Andrew Nguyen, Marjan Farid, Sumit Garg, James V Jester; Test efficacy of the fluorescein breakup time test in the diagnosis of dry eye – a re-examination. Invest. Ophthalmol. Vis. Sci. 2019;60(9):6788.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The purpose of this investigation was to examine the volume effect of common clinical tear breakup time (TBUT) methods, and to evaluate test efficacy in an independent sample, both samples free of selection bias.

Methods : All subjects were evaluated using a battery of standard dry eye tests except TBUT. Efficacy study: Subjects were randomized to the Dry Eye Test (DET), Standard Strip (SS) and 2.0 microliters of 1.0% NaFl, on separate days. A masked examiner measured TBUTs from video recordings. Verification study: Subjects were analyzed, using NaFl volumes of 5.0 microliters of 2.0% and 2.0 microliters of 1.0% NaFl for TBUT. Raw values were log transformed prior to analysis. Cross validation was undertaken for efficacy and cut-point predictive ability by splitting the verification data.

Results : Efficacy study: 15 normals, and 31 dry eye subjects completed the study. Log-transformed TBUTs were all significantly different, normals vs. drys, for all 3 methods (all p values < 0.001). AUCs, cut-points, sensitivity and specificity were: 1) DET, 0.873, 4.4 secs, 0.97 and 0.67, respectively, 2) 2.0 microliters: 0.901, 3.22 secs. and 0.90 and 0.87, respectively, and 3) SS: 0.912, 3.42 secs, and 0.97 and 0.80, respectively. Verification study: There was no difference between the dry and normal eye TBUTs for the two NaFl volumes, so the data were combined providing 142 drys and 90 normals. Of these, ~70% were used for model building with the remainder for model checking. This resulted in an AUC of 0.81, cut-point of 5.31 secs, with sensitivity 0.78 and specificity 0.75. Predictive accuracy was 67% and 76% for normals and drys, respectively.

Conclusions : Little difference in TBUT was found using the three clinical methods, although TBUTs were short, due to the video recording approach. Test efficacy using liquid NaFl suggests that the TBUT test has acceptable diagnostic accuracy.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

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