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. Author manuscript; available in PMC: 2016 Jan 31.
Published in final edited form as: Seizure. 2014 Oct 5;25:104–111. doi: 10.1016/j.seizure.2014.09.013

Table 4.

Using the logistic regression formula or the pre-calculated resulting model scores for each combination of variables shown in Table 3, a patient's model score would be identified. Patients with model scores above a given, institutionally-determined model score cut-off would undergo CEEG. For various cut-offs the sensitivity and specificity are provided for the creation and validation datasets. Compared to all patients who underwent CEEG in the datasets, the percentage of patients who would be above the model score cutoff and thus undergo CEEG are provided for each cutoff. Bold font indicates the model score cut-off maximizing sensitivity and specificity.

Model Score Cut-Off 0.10 0.15 0.20 0.25 0.35 0.45
Creation Dataset Sensitivity/Specificity 94/52 87/67 79/73 72/79 67/84 53/91
Percentage of patients classified as needing CEEG at each cut-off 36 28 24 18 17 9
Validation Dataset Sensitivity/Specificity 86/58 62/76 59/81 43/88 34/92 19/97
Percentage of patients classified as needing CEEG at each cut-off 43 28 25 14 13 5