Table 3:

Performance of the Clinical Decision Rule in the Latin American Cohort

A: When High ICP is defined as >22 mm Hg:

Performance	High ICP	Normal ICP
Rule Positive	61	49
Rule Negative	4	36
Sensitivity	93.9% (95% Confidence Interval [CI]: 85.0–98.3%)
Specificity	42.4% (95%CI: 31.7–53.6%)
Positive Predictive Value	55.5% (95%CI: 50.7–60.2%)
Negative Predictive Value	90.0% (95%CI: 77.1–96.0%)
Positive Likelihood Ratio	1.6 (95%CI: 1.3–2.0)
Negative Likelihood Ratio	0.2 (95%CI: 0.1–0.4)

B: When High ICP is defined as >25 mm Hg:

Performance	High ICP	Normal ICP
Rule Positive	50	60
Rule Negative	1	39
Sensitivity	98.0% (95% CI: 89.6–100.0%)
Specificity	39.4% (95%CI: 29.7– 49.7%)
Positive Predictive Value	45.5% (95%CI: 41.4–49.5%)
Negative Predictive Value	97.5% (95%CI: 84.7% to 99.6%)
Positive Likelihood Ratio	1.6 (95%CI: 1.4–1.9)
Negative Likelihood Ratio	0.1 (95%CI: 0.0–0.4)

C: When High ICP is defined as >30 mm Hg:

Performance	High ICP	Normal ICP
Rule Positive	40	70
Rule Negative	0	40
Sensitivity	100.0% (95% CI: 91.2–100.0%)
Specificity	36.4% (95%CI: 27.4–46.1%)
Positive Predictive Value	36.4% (95%CI: 33.2–39.7%)
Negative Predictive Value	100.0% (95%CI: 89.1% to 100.0%)
Positive Likelihood Ratio	1.6 (95%CI: 1.4–1.8)
Negative Likelihood Ratio	0.0 (95%CI: 0.0–0.0)

The area under the curve (AUC) for the logistic regression model that contains all the predictors is 0.861; P=0.49 for the Hosmer-Lemeshow goodness-of-fit test.

The AUC for the logistic regression model that contains all the predictors is 0.83; P=0.36 for the Hosmer-Lemeshow goodness-of-fit test.

The AUC for the logistic regression model that contains all the predictors is 0.82; P=0.72 for the Hosmer-Lemeshow goodness-of-fit test.