Literature DB >> 17198008

Classifying the severity of corneal ulcers by using the "1, 2, 3" rule.

Mark C Vital1, Marcel Belloso, Thomas C Prager, Jeffrey D Lanier.   

Abstract

PURPOSE: To propose and define the "1, 2, 3" rule as a system of categorizing the severity of bacterial keratitis and to determine its value in predicting the likelihood of visual loss after healing of bacterial corneal infection.
METHODS: Seventy patients were evaluated for infectious corneal ulcers by 2 cornea subspecialists (J.D.L., M.C.V.) at a tertiary facility between October 30, 2001, and November 1, 2004. Forty-one patients met the inclusion criteria. Visual acuities, ulcer characteristics, culture results, and treatment data were collected.
RESULTS: The sensitivity of the "1, 2, 3" rule for detecting potentially sight-threatening (PST) ulcers that would result in 0.20 logMAR (2 Snellen lines) or greater loss in best spectacle-corrected visual acuity (BSCVA) was 100%. The specificity of the "1, 2, 3" rule in correctly labeling an ulcer that did not cause vision loss as rarely sight threatening (RST) was 57.14%. The positive predictive value of the "1, 2, 3" rule was 28.57%. The negative predictive value of the "1, 2, 3" rule was 100%.
CONCLUSIONS: Corneal ulcers classified as PST are at significantly higher risk for sustaining loss of BCSVA compared with RST corneal ulcers. The "1, 2, 3" rule is sensitive and specific enough to be clinically useful in predicting which ulcers are more likely to have vision loss and which ulcers are not.

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Year:  2007        PMID: 17198008     DOI: 10.1097/ICO.0b013e31802b2e47

Source DB:  PubMed          Journal:  Cornea        ISSN: 0277-3740            Impact factor:   2.651


  7 in total

1.  Risk Factors, Clinical Outcomes, and Prognostic Factors of Bacterial Keratitis: The Nottingham Infectious Keratitis Study.

Authors:  Darren Shu Jeng Ting; Jessica Cairns; Bhavesh P Gopal; Charlotte Shan Ho; Lazar Krstic; Ahmad Elsahn; Michelle Lister; Dalia G Said; Harminder S Dua
Journal:  Front Med (Lausanne)       Date:  2021-08-11

2.  First use of a new rapid multiplex PCR system for the microbiological diagnosis and the clinical management of severe infectious keratitis: A case report.

Authors:  Thomas Ferreira de Moura; Anne Limelette; Carl Arndt; Thomas Guillard; Laurent Andreoletti; Alexandre Denoyer
Journal:  Am J Ophthalmol Case Rep       Date:  2022-05-28

3.  Evaluation of fungal keratitis using a newly developed computer program, Optscore, for grading digital corneal photographs.

Authors:  Christine M Toutain-Kidd; Travis C Porco; Eric M Kidd; M Srinivasan; Namperumalsamy V Prajna; Nisha Acharya; Thomas Lietman; Michael E Zegans
Journal:  Ophthalmic Epidemiol       Date:  2014-02       Impact factor: 1.648

4.  Open-Source Automatic Segmentation of Ocular Structures and Biomarkers of Microbial Keratitis on Slit-Lamp Photography Images Using Deep Learning.

Authors:  Jessica Loo; Matthias F Kriegel; Megan M Tuohy; Kyeong Hwan Kim; Venkatesh Prajna; Maria A Woodward; Sina Farsiu
Journal:  IEEE J Biomed Health Inform       Date:  2021-01-05       Impact factor: 5.772

5.  Development and Validation of a Natural Language Processing Algorithm to Extract Descriptors of Microbial Keratitis From the Electronic Health Record.

Authors:  Maria A Woodward; Nenita Maganti; Leslie M Niziol; Sejal Amin; Andrew Hou; Karandeep Singh
Journal:  Cornea       Date:  2021-12-01       Impact factor: 2.651

6.  Effects of 3% diquafosol sodium ophthalmic solution on higher-order aberrations in patients diagnosed with dry eye after cataract surgery.

Authors:  Yasushi Inoue; Shintarou Ochi
Journal:  Clin Ophthalmol       Date:  2016-12-23

7.  Hospital-Associated Multidrug-Resistant MRSA Lineages Are Trophic to the Ocular Surface and Cause Severe Microbial Keratitis.

Authors:  Paulo J M Bispo; Lawson Ung; James Chodosh; Michael S Gilmore
Journal:  Front Public Health       Date:  2020-06-03
  7 in total

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