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. 2019 Dec 6;2(12):e1916921. doi: 10.1001/jamanetworkopen.2019.16921

Table 3. Acute Kidney Injury Risk as Predicted by Models That Add and Do Not Add Intraoperative Data in Test Data Seta.

GBM Preoperative Model No. (%)
GBM-Perioperative Modela Total, No.
Low Risk High Risk
Low Riskb
Encounters 6414 (94.4) 381 (5.6) 6795
Events 283 (80.9) 67 (19.1) 350
Nonevents 6131 (95.1) 314 (4.9) 6445
Proportion of encounters with events 0.044 0.176 0.052
High Riskb
Encounters 381 (22.4) 1318 (77.6) 1699
Events 52 (10.5) 443 (89.5) 495
Nonevents 329 (27.3) 875 (72.7) 1204
Proportion of encounters with events 0.136 0.336 0.291

Abbreviation: GBM, gradient boosting machine.

a

Risk stratification of GBM models in the test set for the outcome of acute kidney injury using preoperative and perioperative data in the test data set (nā€‰=ā€‰8494). For the GBM model using the perioperative model, the overall proportion of encounters with events was 0.300 and 0.049 for high- and low-risk groups, respectively.

b

High risk was defined as the top 20% of predicted risk. Low risk was defined as the bottom 80% of predicted risk.