Table 3.

Confusion Matrix With Varying Cutoffs (Test Data, n = 33,726)^a

Cutoff percentile	True positive rate, (%)	True negative rate, (%)	Positive predictive rate, (%)	Negative predicted value, (%)	Ratio of false positives to true positives
10th	97.3	10.5	1.87	99.54	52.4
20th	94.0	20.6	2.04	99.49	48.1
30th	88.5	30.6	2.19	99.34	44.7
40th	83.8	40.6	2.42	99.31	40.4
50th	78.9	50.4	2.72	99.27	35.8
60th	70.6	60.6	3.05	99.16	31.8
70th	60.5	70.5	3.48	99.03	27.8
80th	50.3	80.6	4.36	98.93	21.9
90th	42.3	90.5	8.50	98.69	10.8

^aThe true positive rate is the percentage of patients who actually developed an infection outcome, in the group of patients who were predicted to have an infection outcome by the statistical model. The true negative rate is the percentage of patients who did not have an infection outcome, in the group of patients who were predicted not to have an infection outcome by the statistical model. The positive predictive value is the ability of the statistical model to accurately predict whether a patient who is identified as having an infection outcome by the model actually has an infection outcome. The negative predictive value is the ability of the statistical model to accurately predict a patient who does not have an infection outcome.