1. Predicting postoperative morbidity in adult elective surgical patients using the Surgical Outcome Risk Tool (SORT) 
D.J.N. Wong, C.M. Oliver, S.R. Moonesinghe 
British Journal of Anaesthesia 
Volume 119, Issue 1, Pages (July 2017)
DOI: /bja/aex117
Copyright © 2017 The Author(s) Terms and Conditions

2. Fig 1
Flow diagram summarizing patients included and excluded from analysis.
British Journal of Anaesthesia  , DOI: ( /bja/aex117)
Copyright © 2017 The Author(s) Terms and Conditions

3. Fig 2
(A) Calibration plot of SORT-morbidity compared with POSSUM: observed vs predicted occurrence of day 7 or 8 morbidity at varying levels of risk in the validation cohort of 527 patients; (B) ROC curve plot of SORT-morbidity compared against POSSUM (AUROC=0.72 and 0.66, respectively) tested in the validation cohort. AUROC, area under the receiver operating characteristic curve; ROC, receiver operating characteristic.
British Journal of Anaesthesia  , DOI: ( /bja/aex117)
Copyright © 2017 The Author(s) Terms and Conditions

4. Fig 3
Sensitivity analyses. (A) Calibration plot of SORT-morbidity for predicting modified POMS, comparing low-grade and high-grade POMS morbidity outcomes. (B) ROC curve plot showing SORT-morbidity discrimination performance for predicting low-grade and high-grade POMS morbidity outcomes (AUROC=0.75 and 0.72, respectively). (C) Calibration plot of SORT-morbidity for predicting day 14 or 15, 21, and 28 POMS outcomes. (D) ROC curve plot showing SORT-morbidity discrimination performance for predicting day 14 or 15, 21, and 28 POMS outcomes (AUROC=0.73, 0.79, and 0.81, respectively). AUROC, area under the receiver operating characteristic curve; ROC, receiver operating characteristic.
British Journal of Anaesthesia  , DOI: ( /bja/aex117)
Copyright © 2017 The Author(s) Terms and Conditions