Uvemaster: A Mobile App-Based Decision Support System for the Differential Diagnosis of Uveitis.
Invest Ophthalmol Vis Sci
; 58(10): 3931-3939, 2017 08 01.
Article
em En
| MEDLINE
| ID: mdl-28772309
ABSTRACT
Purpose:
To examine the diagnostic accuracy and performance of Uvemaster, a mobile application (app) or diagnostic decision support system (DDSS) for uveitis. The app contains a large database of knowledge including 88 uveitis syndromes each with 76 clinical items, both ocular and systemic (total 6688) and their respective prevalences, and displays a differential diagnoses list (DDL) ordered by sensitivity, specificity, or positive predictive value (PPV).Methods:
In this retrospective case-series study, diagnostic accuracy (percentage of cases for which a correct diagnosis was obtained) and performance (percentage of cases for which a specific diagnosis was obtained) were determined in reported series of patients originally diagnosed by a uveitis specialist with specific uveitis (N = 88) and idiopathic uveitis (N = 71), respectively.Results:
Diagnostic accuracy was 96.6% (95% confidence interval [CI], 93.2-100). By sensitivity, the original diagnosis appeared among the top three in the DDL in 90.9% (95% CI, 84.1-96.6) and was the first in 73.9% (95% CI, 63.6-83.0). By PPV, the original diagnosis was among the top DDL three in 62.5% (95% CI, 51.1-71.6) and the first in 29.5% (95% CI, 20.5-38.6; P < 0.001). In 71 (31.1%) patients originally diagnosed with idiopathic uveitis, 19 new diagnoses were made reducing this series to 52 (22.8%) and improving by 8.3% the new rate of diagnosed specific uveitis cases (performance = 77.2%; 95% CI, 71.1-82.9).Conclusions:
Uvemaster proved accurate and based on the same clinical data was able to detect more cases of specific uveitis than the original clinician only-based method.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Uveíte
/
Técnicas de Apoio para a Decisão
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Aplicativos Móveis
Tipo de estudo:
Diagnostic_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Adolescent
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Adult
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Aged
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Aged80
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Child
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Child, preschool
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article