PURPOSE: The authors' previous models predicted local formation of diabetic retinopathy (DR) in adults with diabetes and existing retinopathy. Here they derived a multivariate model for local prediction of DR onset in patients with no previous retinopathy. METHODS: Seventy-eight eyes from 41 diabetes patients were tested annually for several years. The presence or absence of DR at the last study visit was the outcome measure, and measurements of risk factors from the previous visit were used for prediction. Logistic regression was used to assess the relationship between DR development and 7 factors: multifocal ERG (mfERG) implicit time (IT) Z-score, sex, diabetes duration, blood glucose, HbA1c, age, and diabetes type. Thirty-five retinal zones, spanning 45°, were constructed from the mfERG stimulus elements. The maximum IT Z-score for each zone was calculated based on data from 50 control subjects. ROC curve analysis, using fivefold cross-validation, was used to determine the model's predictive properties. RESULTS: Mild DR developed in 80 of 2730 retinal zones (3%) in 29 of 78 eyes (37%). Multivariate analysis showed mfERG IT to be predictive for DR development in a zone after adjusting for diabetes type. The multivariate model has a sensitivity of 80% and a specificity of 74%. CONCLUSIONS: mfERG IT is a good predictor of DR onset, 1 year later, in patients with diabetes without DR. It can be used to assess the risk for DR development in these patients and may be a valuable outcome measure in evaluation of novel prophylactic therapeutics directed at impeding DR.
PURPOSE: The authors' previous models predicted local formation of diabetic retinopathy (DR) in adults with diabetes and existing retinopathy. Here they derived a multivariate model for local prediction of DR onset in patients with no previous retinopathy. METHODS: Seventy-eight eyes from 41 diabetespatients were tested annually for several years. The presence or absence of DR at the last study visit was the outcome measure, and measurements of risk factors from the previous visit were used for prediction. Logistic regression was used to assess the relationship between DR development and 7 factors: multifocal ERG (mfERG) implicit time (IT) Z-score, sex, diabetes duration, blood glucose, HbA1c, age, and diabetes type. Thirty-five retinal zones, spanning 45°, were constructed from the mfERG stimulus elements. The maximum IT Z-score for each zone was calculated based on data from 50 control subjects. ROC curve analysis, using fivefold cross-validation, was used to determine the model's predictive properties. RESULTS: Mild DR developed in 80 of 2730 retinal zones (3%) in 29 of 78 eyes (37%). Multivariate analysis showed mfERG IT to be predictive for DR development in a zone after adjusting for diabetes type. The multivariate model has a sensitivity of 80% and a specificity of 74%. CONCLUSIONS:mfERG IT is a good predictor of DR onset, 1 year later, in patients with diabetes without DR. It can be used to assess the risk for DR development in these patients and may be a valuable outcome measure in evaluation of novel prophylactic therapeutics directed at impeding DR.
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