Anglia Ruskin Research Online (ARRO)
Browse
Willshire_2018.docx (167.84 kB)

Basal Tear Osmolarity as a metric to estimate body hydration and dry eye severity

Download (167.84 kB)
journal contribution
posted on 2023-08-30, 15:11 authored by Catherine Willshire, Anthony J. Bron, Eamonn A. Gaffney, Edward I. Pearce
The osmolarities of various bodily fluids, including tears, saliva and urine, have been used as indices of plasma osmolality, a measure of body hydration, while tear osmolarity is used routinely in dry eye diagnosis, the degree of tear hyperosmolarity providing an index of disease severity. Systemic dehydration, due to inadequate water intake or excessive water loss is common in the elderly population, has a high morbidity and may cause loss of life. Its diagnosis is often overlooked and there is a need to develop a simple, bedside test to detect dehydration in this population. We hypothesize that, in the absence of tear evaporation and with continued secretion, mixing and drainage of tears, tear osmolarity falls to a basal level that is closer to that of the plasma than that of a tear sample taken in open eye conditions. We term this value the Basal Tear Osmolarity (BTO) and propose that it may be measured in tear samples immediately after a period of evaporative suppression. This value will be particular to an individual and since plasma osmolarity is controlled within narrow limits, it is predicted that it will be stable and have a small variance. It is proposed that the BTO, measured immediately after a defined period of eye closure, can provide a new metric in the diagnosis of systemic dehydration and a yardstick against which to gauge the severity of dry eye disease.

History

Refereed

  • Yes

Volume

64

Page range

56-64

Publication title

Progress in Retinal and Eye Research

ISSN

1873-1635

Publisher

Elsevier

File version

  • Accepted version

Language

  • eng

Legacy posted date

2018-03-13

Legacy creation date

2018-03-13

Legacy Faculty/School/Department

ARCHIVED Faculty of Medical Science (until September 2018)

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC