Extended Data Table 2 |. Daily frequency of true and false positive alerts when predicting different stages of AKI.

The frequency of alerts and its standard deviation are shown for a time window of 48 hours an operating point corresponding to a 1:2 TP:FP ratio (N=5101 days). On an average day, clinicians would receive true positive alerts of AKI predicted to occur within a window of 48 hours ahead in 0.85% of all in-hospital patients, and a false positive prediction of a future AKI in 1.89% of patients, when predicting the future AKI of any severity. Assuming none of the false positives can be filtered out and immediately discarded, clinicians would need to attend to approximately 2.7% of all in-hospital patients. For the most severe stages of AKI, the model alerts on an average day in 0.8% of all patients. Of those, 0.27% are true positives and 0.56% are false positives. Note that there are multiple time steps at which the predictions are made within each day, so the TP:FP ratio of the daily alerts differs slightly from the step-wise ratio. (a) Daily frequency of true and false positive alerts when predicting any stage of AKI. (b) Daily frequency of true and false positive alerts when predicting KDIGO AKI stages two and above. (c) Daily frequency of true and false positive alerts when predicting the most severe stage of AKI - KDIGO AKI stage 3.

a
Alert type	Frequency predicting any stage of AKI
True positive alerts	0.85% ± 0.71
False positive alerts	1.89% ± 1.20
No alerts	97.26% ± 1.63
b
Alert type	Frequency predicting KDIGO AKI stages 2 and above
True positive alerts	0.30% ± 0.35
False positive alerts	0.64% ± 0.55
No alerts	99.06% ± 0.75
c
Alert type	Frequency predicting KDIGO AKI stage 3
True positive alerts	0.27% ± 0.33
False positive alerts	0.56% ± 0.85
No alerts	99.17% ± 0.96