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Classification Criteria for Tubulointerstitial Nephritis With Uveitis Syndrome

  • The Standardization of Uveitis Nomenclature (SUN) Working Group
    Author Footnotes
    1 Members of the SUN Working Group are listed online at AJO.com.
    ,
    Author Footnotes
    2 Writing Committee: Douglas A. Jabs, Alastair K. Denniston, Anat Galor, Susan Lightman, Peter McCluskey, Neal Oden, Alan G. Palestine, James T. Rosenbaum, Sophia M. Saleem, Jennifer E. Thorne, and Brett E. Trusko
    ,
    Author Footnotes
    3 Writing Committee Affiliations: Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA (D.A.J., J.E.T.); Wilmer Eye Institute, Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA (D.A.J., J.E.T.); Academic Unit of Ophthalmology, University of Birmingham, Birmingham, United Kingdom (A.K.D.); Department of Ophthalmology, University of Miami Miller School of Medicine, Miami, Florida, USA (A.G.); Institute of Ophthalmology, University College London and Moorfields Eye Hospital, London, United Kingdom (S.L.); Save Sight Institute, Department of Ophthalmology, University of Sydney School of Medicine, Sydney, New South Wales, Australia (P.M.); The Emmes Company, LLC, Rockville, Maryland, USA (N.O.); Department of Ophthalmology, University of Colorado School of Medicine, Aurora, Colorado, USA (A.G.P.); Departments of Medicine and Ophthalmology, Oregon Health and Science University, Portland, Oregon, USA (J.T.R.); Legacy Devers Eye Institute, Portland, Oregon, USA (J.T.R.); Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, USA (S.M.S.); and Department of Medicine, Texas A&M University, College Station, Texas, USA (B.E.T.).
    ,
    Author Footnotes
    4 Inquiries to Douglas A. Jabs, Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 20215, USA. E-mail: [email protected]
  • Author Footnotes
    1 Members of the SUN Working Group are listed online at AJO.com.
    2 Writing Committee: Douglas A. Jabs, Alastair K. Denniston, Anat Galor, Susan Lightman, Peter McCluskey, Neal Oden, Alan G. Palestine, James T. Rosenbaum, Sophia M. Saleem, Jennifer E. Thorne, and Brett E. Trusko
    3 Writing Committee Affiliations: Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA (D.A.J., J.E.T.); Wilmer Eye Institute, Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA (D.A.J., J.E.T.); Academic Unit of Ophthalmology, University of Birmingham, Birmingham, United Kingdom (A.K.D.); Department of Ophthalmology, University of Miami Miller School of Medicine, Miami, Florida, USA (A.G.); Institute of Ophthalmology, University College London and Moorfields Eye Hospital, London, United Kingdom (S.L.); Save Sight Institute, Department of Ophthalmology, University of Sydney School of Medicine, Sydney, New South Wales, Australia (P.M.); The Emmes Company, LLC, Rockville, Maryland, USA (N.O.); Department of Ophthalmology, University of Colorado School of Medicine, Aurora, Colorado, USA (A.G.P.); Departments of Medicine and Ophthalmology, Oregon Health and Science University, Portland, Oregon, USA (J.T.R.); Legacy Devers Eye Institute, Portland, Oregon, USA (J.T.R.); Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, USA (S.M.S.); and Department of Medicine, Texas A&M University, College Station, Texas, USA (B.E.T.).
    4 Inquiries to Douglas A. Jabs, Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 20215, USA. E-mail: [email protected]
Published:April 09, 2021DOI:https://doi.org/10.1016/j.ajo.2021.03.041

      Purpose

      To determine classification criteria for tubulointerstitial nephritis with uveitis (TINU).

      Design

      Machine learning of cases with TINU and 8 other anterior uveitides.

      Methods

      Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set.

      Results

      One thousand eighty-three cases of anterior uveitides, including 94 cases of TINU, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set and 96.7% in the validation set (95% confidence interval 92.4, 98.6). Key criteria for TINU included anterior chamber inflammation and evidence of tubulointerstitial nephritis with either (1) a positive renal biopsy or (2) evidence of nephritis (elevated serum creatinine and/or abnormal urine analysis) and an elevated urine β-2 microglobulin. The misclassification rates for TINU were 1.2% in the training set and 0% in the validation set.

      Conclusions

      The criteria for TINU had a low misclassification rate and seemed to perform well enough for use in clinical and translational research.
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