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Microbiome of the Eye01:22

Microbiome of the Eye

The human eye has a specialized microbiota that reflects its unique anatomical and immunological environment. This low-biomass microbial community predominantly colonizes the conjunctiva and eyelid margins, playing a vital role in ocular surface homeostasis and defense. Despite its proximity to the richly colonized facial skin, the ocular surface maintains a distinct microbial profile due to continuous mechanical and biochemical defense mechanisms.The conjunctival surface hosts fewer microbial...

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Intense Pulsed Light for the Treatment of Dry Eye Owing to Meibomian Gland Dysfunction
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Inter-examiner reliability in meibomian gland dysfunction assessment.

Daniel R Powell1, Jason J Nichols, Kelly K Nichols

  • 1College of Optometry, The Ohio State University, Columbus, Ohio, USA.

Investigative Ophthalmology & Visual Science
|April 14, 2012
PubMed
Summary

Digital grading of meibomian gland dysfunction (MGD) shows moderate reliability for gland dropout and telangiectasias. However, grading acini appearance and lid debris from images is less reliable than real-time examination.

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Clinical Diagnostics

Background:

  • Meibomian gland dysfunction (MGD) is a common condition affecting the ocular surface.
  • Accurate clinical assessment of MGD is crucial for effective management.
  • Inter-examiner reliability in grading MGD signs can impact diagnostic consistency.

Purpose of the Study:

  • To evaluate the inter-examiner reliability of grading clinical variables associated with MGD.
  • To compare the reliability of real-time examination versus digital image grading for MGD signs.

Main Methods:

  • 410 post-menopausal women were assessed for MGD.
  • Meibography and slit-lamp photography were performed.
  • Examiners graded gland atrophy, acini appearance, lid debris, and telangiectasias from both real-time exams and digital images.

Main Results:

  • Observed agreement varied, with acini appearance (54.5%) and lid debris (50.9%) showing lower agreement than gland dropout (42.8%) and telangiectasias (40.6%).
  • Weighted kappas (κ(w)) indicated fair to moderate inter-examiner reliability.
  • Reliability was fair for acini appearance (κ(w) = 0.23) and lid debris (κ(w) = 0.24), and moderate for gland dropout (κ(w) = 0.50) and telangiectasias (κ(w) = 0.47).

Conclusions:

  • Grading gland dropout and telangiectasias from digital images demonstrates higher reliability compared to real-time examination.
  • Grading acini appearance and lid debris from images is less reliable than real-time assessment.
  • Future research should explore alternative grading scales and MGD clinical variables.