T1DMicro: A Clinical Risk Calculator for Type 1 Diabetes Related Microvascular Complications

Figures

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  Figure 1. Calibration plot (A) and nomogram (B) for DPN in a multivariate logistic regression model. Calibration plots and nomograms for AN (C and D), DR (E and F), and DN (G and H) are presented in Supplementary Figure S1. We applied the four microvascular complication models to the PAGODA dataset with 500 iterations of bootstrapping to generate the calibration plot showing the actual probability of complication in the y-axis and the predicted probability of complication based on the models in the x-axis. A bias correction was applied by calculating the difference in probability between the bootstrap iterations and the model prediction with the full dataset. The nomogram was generated again based on the beta coefficients from the four logistic microvascular complication models.

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  Figure 2. Predicted risk of DPN (A), AN (B), DR (C), and DN (D) with increasing HbA1c (left) and systolic blood pressure (right). We applied the four logistic microvascular complication models to simulated data by fixing the mean and standard deviation of the simulated data to that of the PAGODA population and varying the patient age at day of sample and our variables of interest, HbA1c and systolic blood pressure. We tested HbA1c at 5, 7, 9, and 11. We tested systolic blood pressure at 120, 140, 160, and 180. The gray zones show the 95% confidence interval of the predicted risk.