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. 2022 Mar 16;90(6):691–699. doi: 10.1227/neu.0000000000001895

TABLE 3.

Performance of the Quantitative GLM Model vs the CHIIDA Model in the Training Data set

Training data set (n = 1126) GLM RP KIIDS-TBI
<1% <3% <5% <1% <3% <5% <1% <3% <5%
High acuity disposition
  Composite outcome 79 76 75 80 80 77 82 80 78
  No composite outcome 235 130 106 230 230 141 752 314 192
Low acuity disposition
  Composite outcome 3 6 7 2 2 5 0 2 4
  No composite outcome 809 914 938 814 814 903 292 730 852
Sensitivity (95% CI) 0.96 (0.90-0.99) 0.93 (0.85-0.97) 0.91 (0.83-0.96) 0.98 (0.91-1.0) 0.98 (0.91-1.0) 0.94 (0.86-0.98) 1.0 (0.96-1.0) 0.98 (0.91-1.0) 0.95 (0.88-0.99)
Specificity (95% CI) 0.77 (0.75-0.80) 0.88 (0.85-0.89) 0.90 (0.88-0.92) 0.78 (0.75-0.80) 0.78 (0.75-0.80) 0.86 (0.84-0.89) 0.28 (0.25-0.31) 0.70 (0.67-0.73) 0.82 (0.79-0.84)
PPV (95% CI) 0.25 (0.20-0.30) 0.37 (0.30-0.44) 0.41 (0.34-0.49) 0.26 (0.21-0.31) 0.26 (0.21-0.31) 0.35 (0.29-0.42) 0.10 (0.08-0.12) 0.20 (0.16-0.25) 0.29 (0.24-0.35)
NPV (95% CI) 0.996 (0.99-1.0) 0.99 (0.99-1.0) 0.99 (0.98-1.0) 0.998 (0.99-1.0) 0.998 (0.99-1.0) 0.99 (0.99-1.0) 1.0 (0.99-1.0) 0.997 (0.99-1.0) 0.995 (0.99-1.0)

CHIIDA, Children's Intracranial Injury Decision Aid; GLM, generalized linear modeling; KIIDS-TBI, kids intracranial injury decision support tool for traumatic brain injury; NPV, negative predictive value; PPV, positive predictive value; RP, recursive partitioning.