To establish the prediction model of renal dysfunction in patients with drug-induced renal injury and study the prognosis of different drug treatments
Study Type
OBSERVATIONAL
Enrollment
1,500
Observational study, no intervention
Zhejiang Provincial People's Hospital
Hangzhou, Zhejiang, China
RECRUITINGModel performance metrics assessed by AUC-ROC, accuracy and F1-score using 10-fold cross-validation
The prognosis of renal function was evaluated by measuring creatinine and proteinuria by laboratory tests. Predict outcomes using machine learning methods. And the prediction effect of the prediction model was evaluated by AUC-ROC, F1, accuracy and other indicators.
Time frame: through study completion, an average of 6 months
The rate at which creatinine falls
Time frame: 7 days, 1 month, 3 months after treatment
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