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. 2023 Aug 19;8(11):2345–2355. doi: 10.1016/j.ekir.2023.08.006

Figure 1.

Figure 1

Equation development. (a) Figure with on the y-axis eight different covariates, with their color representing the β-coefficient as depicted in the legend. On the x-axis is the number of the covariate in the model. A higher coefficient represents a higher positive correlation of the covariate with the GFR. In a stepwise iterative removal method, covariates were first all included in the model and then removed in the sequence of importance, starting with the lowest contribution to the model's performance (African-American). The most important covariates were log(10) proenkephalin, log(10) creatinine, and age log(10). (b) RMSE (Root Mean Square Error) of the model with on the x-axis the number of covariates on the model. The covariates were added in a stepwise-enter method, in the sequence of importance, starting with log(10) proenkephalin. A lower RMSE value illustrates a more accurate predicting model. After adding covariate log (10) proenkephalin, log(10) creatinine, and log(10) age, the RMSE does not significantly improve any further. PENK, proenkephalin.