Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A novel <i>CAPN5</i> missense variant associated with autosomal dominant neovascular inflammatory vitreoretinopathy.

Ophthalmic genetics·2026
Same author

Large Language Model Authorship in Ophthalmic Publications.

Ophthalmology·2026
Same author

Bilateral Occlusive Retinal Vasculitis After Faricimab Rechallenge.

JAMA ophthalmology·2026
Same author

Tattoo Granuloma Associated With Uveitis: A Useful Temporary Entity Pending Further Clarification-Response.

Clinical & experimental ophthalmology·2026
Same author

Roles of the nonvisual opsins in the mammalian retina.

Handbook of clinical neurology·2026
Same author

Vogt-Koyanagi-Harada-Like Disease Associated With Drug Reaction With Eosinophilia and Systemic Symptoms Syndrome.

Journal of vitreoretinal diseases·2026

Related Experiment Video

Updated: Nov 17, 2025

Experimental Autoimmune Uveitis: An Intraocular Inflammatory Mouse Model
07:40

Experimental Autoimmune Uveitis: An Intraocular Inflammatory Mouse Model

Published on: January 12, 2022

5.5K

Rational laboratory testing in uveitis: A Bayesian analysis.

K Matthew McKay1, Lyndell L Lim2, Russell N Van Gelder3

  • 1Department of Ophthalmology, University of Washington, Seattle, Washington, USA.

Survey of Ophthalmology
|February 12, 2021
PubMed
Summary
This summary is machine-generated.

Diagnosing uveitis (intraocular inflammation) requires careful laboratory testing. Applying Bayesian analysis to test performance and disease prevalence improves diagnostic accuracy for associated systemic conditions.

Keywords:
Bayes theoremBayesian analysisLaboratory testingOcular inflammationPost-test probabilityPretest probabilityUveitisUveitis causesUveitis epidemiologyUveitis etiology

More Related Videos

Primed Mycobacterial Uveitis PMU as a Model for Post-Infectious Uveitis
10:33

Primed Mycobacterial Uveitis PMU as a Model for Post-Infectious Uveitis

Published on: December 17, 2021

2.9K
Use of Rabbit Eyes in Pharmacokinetic Studies of Intraocular Drugs
10:02

Use of Rabbit Eyes in Pharmacokinetic Studies of Intraocular Drugs

Published on: July 23, 2016

32.7K

Related Experiment Videos

Last Updated: Nov 17, 2025

Experimental Autoimmune Uveitis: An Intraocular Inflammatory Mouse Model
07:40

Experimental Autoimmune Uveitis: An Intraocular Inflammatory Mouse Model

Published on: January 12, 2022

5.5K
Primed Mycobacterial Uveitis PMU as a Model for Post-Infectious Uveitis
10:33

Primed Mycobacterial Uveitis PMU as a Model for Post-Infectious Uveitis

Published on: December 17, 2021

2.9K
Use of Rabbit Eyes in Pharmacokinetic Studies of Intraocular Drugs
10:02

Use of Rabbit Eyes in Pharmacokinetic Studies of Intraocular Drugs

Published on: July 23, 2016

32.7K

Area of Science:

  • Ophthalmology
  • Immunology
  • Medical Diagnostics

Background:

  • Uveitis, characterized by intraocular inflammation, presents heterogeneously.
  • Establishing a specific diagnosis often necessitates laboratory investigations.
  • Consensus on optimal laboratory evaluation for uveitis is limited among specialists.

Purpose of the Study:

  • To review the performance of common laboratory tests for uveitis.
  • To analyze the prevalence of uveitic diagnoses across different geographic settings.
  • To propose a framework for effective laboratory testing in uveitis using Bayesian analysis.

Main Methods:

  • Summarizing laboratory test performance (sensitivity, specificity).
  • Reviewing disease prevalence data in various populations.
  • Applying Bayesian principles to interpret test results in clinical contexts.

Main Results:

  • Highly sensitive tests can effectively rule out systemic diseases.
  • Limited test specificity and low pretest probability often hinder definitive diagnosis.
  • Bayesian analysis provides a logical framework for test interpretation.

Conclusions:

  • Effective laboratory testing for uveitis requires considering patient-specific and epidemiologic factors.
  • Rigorous application of Bayesian analysis enhances diagnostic certainty.
  • While ruling out systemic disease is feasible, confirming it with certainty can be challenging.