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Fig 1.

Flowchart of participant selection for the development of nomogram to develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021.

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Table 1.

Socio-demographic and behavioral predictors of for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021 (n = 808).

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Table 2.

Clinical predictors for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021 (n = 808).

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Table 3.

Laboratory related predictors for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021 (n = 808).

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Fig 2.

Pie chart for the proportion diabetic neuropathy to develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia 2005–2021.

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Table 4.

Optimum shrinkage factor (lambda) and potential predictors identified by lasso regression by 10-fold cross validation selection method for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia 2005–2021 (n = 808).

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Table 5.

Multi variable logistic regression for variables retained in the final reduced model for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021 (n = 808).

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Fig 3.

The performance of the model using original beta coefficients A) AUC B) calibration plot, for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia 2005–2021.

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Fig 4.

Nomogram to develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021.

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Fig 5.

Performance of model using nomogram A) AUC B) Calibration plot, prediction for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia 2005–2021.

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Table 6.

Prediction rate for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021.

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Fig 6.

Classification and regression decision tree for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia 2005–2021.

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Fig 7.

The performance of the model using decision tree A) AUC B) calibration plot to develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia 2005–2021.

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Fig 8.

The performance of the model using nomogram after bootstrapping A) Area under the curve (AUC) B) calibration plot, for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021.

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Fig 9.

The performance of the model using classification and regression decision tree after bootstrapping A) AUC B) Calibration plot to develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia 2005–2021.

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Fig 10.

Comparison of nomogram and decision tree for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia 2005–2021.

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Table 7.

Sensitivity, specificity, PPV, NPV, LR+, LR- and accuracy of the nomogram at different cut-off points for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia 2005–2021.

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Table 8.

Risk classification for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021 (n = 808).

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Fig 11.

Decision curve plot A) Nomogram B) Decision tree, showing the net benefit of the developed model for carrying out a certain intervention measure to develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021.

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Fig 12.

Mobile based application outputs for develop and validation of risk prediction model for diabetic neuropathy among diabetes mellitus patients at selected referral hospitals, in Amhara regional state Northwest Ethiopia, 2005–2021.

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