ArticleOphthalmic epidemiology2022
Accuracy of the International Classification of Diseases, 9th Revision for Identifying Infantile Eye Disease.
Article in Ophthalmic epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Predictive Value of the International Classification of Diseases, 9th Revision Codes for Identifying Ocular Oncology Diagnoses.Ocular oncology and pathology · 2023Article
- Incidence and distribution of ocular disorders in the first year of life.Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus · 2023Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
purposeTo determine the predictive value of International Classification of Diseases, 9th Revision (ICD-9) codes for identifying infantile eye diagnoses.
methodsPopulation-based retrospective cohort study of all residents of Olmsted County, Minnesota diagnosed at ≤1 year of age with an ocular disorder. The medical records of all infants diagnosed with any ocular disorder from January 1, 2005, through December 31, 2014, were identified. To assess ICD-9 code accuracy, the medical records of all diagnoses with ≥20 cases were individually reviewed and compared to their corresponding ICD-9 codes. Main outcome measures included positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of ICD-9 codes.
resultsIn a cohort of 5,109 infants with ≥1 eye-related ICD-9 code, 10 ocular diagnoses met study criteria. The most frequent diagnoses were conjunctivitis (N = 1,695) and congenital nasolacrimal duct obstruction (N = 1,250), while the least common was physiologic anisocoria (N = 23). The PPVs ranged from 8.3% to 88.0%, NPVs from 96.3% to 100%, sensitivity from 3.0% to 98.7%, and specificity from 72.6% to 99.9%. ICD-9 codes were most accurate at identifying physiologic anisocoria (PPV: 88.0%) and least accurate at identifying preseptal cellulitis (PPV: 8.3%). In eye specialists versus non-eye specialists, there was a significant difference in PPV of ICD-9 codes for conjunctivitis (26.8% vs. 63.9%,
conclusionThe predictive value of ICD-9 codes for capturing infantile ocular diagnoses varied widely in this cohort. These findings emphasize the limitations of database research methodologies that solely utilize claims data to identify pediatric eye diseases.
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