Measure

Estimates in training sample

Estimates with 1,000 bootstrap resamples


Sensitivity% (95% CI)

82.1 (64.492.1)

82.1 (66.795.8*)

Specificity% (95% CI)

71.7 (62.879.2)

71.7 (62.879.8*)

Positive predictive value% (95% CI)

41.8 (29.755.0)

41.8 (29.155.8*)

Negative predictive value% (95% CI)

94.2 (87.197.5)

94.2 (88.898.8*)

Positive likelihood ratio (95% CI)

2.90 (2.064.08)

2.90 (1.814.74*)

Negative likelihood ratio (95% CI)

0.25 (0.110.57)

0.25 (0.110.58*)

Area under ROC curve (95% CI)

0.77 (0.690.85)

0.77 (0.690.85*)

 • *95% asymptotic confidence intervals.
 Sensitivity: number of participants classified at risk both by the PR and the postoperative WOMAC score divided by all participants classified at risk by the postoperative WOMAC score (actual outcome).
 Specificity: number of participants classified not at risk by the PR and the postoperative WOMAC score divided by all participants classified not at risk by the postoperative WOMAC score (actual outcome).
 Positive predictive value: number of participants classified at risk by the PR and the postoperative WOMAC score divided by all participants classified at risk by the PR (predicted outcome).
 Negative predictive value: number of participants classified not at risk by the PR and the postoperative WOMAC score divided by all participants classified not at risk by the PR (predicted outcome).
 Positive likelihood ratio: sensitivity/(1specificity).
 Negative likelihood ratio: (1sensitivity)/specificity.
 Area under the ROC curve is defined as the area under the sensitivity vs. 1specificity curve.