Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS
<b>Introduction:</b> Big data-based artificial intelligence (AI) has become increasingly important in medicine and may be helpful in the future to predict diseases and outcomes. For severely injured patients, a new analytics tool has recently been developed (WATSON Trauma Pathway Explore...
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doaj-b85f58b6ea5341c8baa19a5007e4b7192021-05-31T23:59:45ZengMDPI AGJournal of Clinical Medicine2077-03832021-05-01102115211510.3390/jcm10102115Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISSCédric Niggli0Hans-Christoph Pape1Philipp Niggli2Ladislav Mica3Department of Trauma Surgery, University Hospital Zurich, 8091 Zurich, SwitzerlandDepartment of Trauma Surgery, University Hospital Zurich, 8091 Zurich, SwitzerlandDepartment of Mathematics, ETH Zurich, 8092 Zurich, SwitzerlandDepartment of Trauma Surgery, University Hospital Zurich, 8091 Zurich, Switzerland<b>Introduction:</b> Big data-based artificial intelligence (AI) has become increasingly important in medicine and may be helpful in the future to predict diseases and outcomes. For severely injured patients, a new analytics tool has recently been developed (WATSON Trauma Pathway Explorer) to assess individual risk profiles early after trauma. We performed a validation of this tool and a comparison with the Trauma and Injury Severity Score (TRISS), an established trauma survival estimation score. <b>Methods:</b> Prospective data collection, level I trauma centre, 1 January 2018–31 December 2019. Inclusion criteria: Primary admission for trauma, injury severity score (ISS) ≥ 16, age ≥ 16. Parameters: Age, ISS, temperature, presence of head injury by the Glasgow Coma Scale (GCS). Outcomes: SIRS and sepsis within 21 days and early death within 72 h after hospitalisation. Statistics: Area under the receiver operating characteristic (ROC) curve for predictive quality, calibration plots for graphical goodness of fit, Brier score for overall performance of WATSON and TRISS. <b>Results:</b> Between 2018 and 2019, 107 patients were included (33 female, 74 male; mean age 48.3 ± 19.7; mean temperature 35.9 ± 1.3; median ISS 30, IQR 23–36). The area under the curve (AUC) is 0.77 (95% CI 0.68–0.85) for SIRS and 0.71 (95% CI 0.58–0.83) for sepsis. WATSON and TRISS showed similar AUCs to predict early death (AUC 0.90, 95% CI 0.79–0.99 vs. AUC 0.88, 95% CI 0.77–0.97; <i>p</i> = 0.75). The goodness of fit of WATSON (<i>X</i><sup>2</sup> = 8.19, Hosmer–Lemeshow <i>p</i> = 0.42) was superior to that of TRISS (<i>X</i><sup>2</sup> = 31.93, Hosmer–Lemeshow <i>p</i> < 0.05), as was the overall performance based on Brier score (0.06 vs. 0.11 points). <b>Discussion:</b> The validation supports previous reports in terms of feasibility of the WATSON Trauma Pathway Explorer and emphasises its relevance to predict SIRS, sepsis, and early death when compared with the TRISS method.https://www.mdpi.com/2077-0383/10/10/2115polytraumaWATSON Trauma Pathway ExploreroutcomeSIRSsepsisearly death |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Cédric Niggli Hans-Christoph Pape Philipp Niggli Ladislav Mica |
spellingShingle |
Cédric Niggli Hans-Christoph Pape Philipp Niggli Ladislav Mica Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS Journal of Clinical Medicine polytrauma WATSON Trauma Pathway Explorer outcome SIRS sepsis early death |
author_facet |
Cédric Niggli Hans-Christoph Pape Philipp Niggli Ladislav Mica |
author_sort |
Cédric Niggli |
title |
Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS |
title_short |
Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS |
title_full |
Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS |
title_fullStr |
Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS |
title_full_unstemmed |
Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS |
title_sort |
validation of a visual-based analytics tool for outcome prediction in polytrauma patients (watson trauma pathway explorer) and comparison with the predictive values of triss |
publisher |
MDPI AG |
series |
Journal of Clinical Medicine |
issn |
2077-0383 |
publishDate |
2021-05-01 |
description |
<b>Introduction:</b> Big data-based artificial intelligence (AI) has become increasingly important in medicine and may be helpful in the future to predict diseases and outcomes. For severely injured patients, a new analytics tool has recently been developed (WATSON Trauma Pathway Explorer) to assess individual risk profiles early after trauma. We performed a validation of this tool and a comparison with the Trauma and Injury Severity Score (TRISS), an established trauma survival estimation score. <b>Methods:</b> Prospective data collection, level I trauma centre, 1 January 2018–31 December 2019. Inclusion criteria: Primary admission for trauma, injury severity score (ISS) ≥ 16, age ≥ 16. Parameters: Age, ISS, temperature, presence of head injury by the Glasgow Coma Scale (GCS). Outcomes: SIRS and sepsis within 21 days and early death within 72 h after hospitalisation. Statistics: Area under the receiver operating characteristic (ROC) curve for predictive quality, calibration plots for graphical goodness of fit, Brier score for overall performance of WATSON and TRISS. <b>Results:</b> Between 2018 and 2019, 107 patients were included (33 female, 74 male; mean age 48.3 ± 19.7; mean temperature 35.9 ± 1.3; median ISS 30, IQR 23–36). The area under the curve (AUC) is 0.77 (95% CI 0.68–0.85) for SIRS and 0.71 (95% CI 0.58–0.83) for sepsis. WATSON and TRISS showed similar AUCs to predict early death (AUC 0.90, 95% CI 0.79–0.99 vs. AUC 0.88, 95% CI 0.77–0.97; <i>p</i> = 0.75). The goodness of fit of WATSON (<i>X</i><sup>2</sup> = 8.19, Hosmer–Lemeshow <i>p</i> = 0.42) was superior to that of TRISS (<i>X</i><sup>2</sup> = 31.93, Hosmer–Lemeshow <i>p</i> < 0.05), as was the overall performance based on Brier score (0.06 vs. 0.11 points). <b>Discussion:</b> The validation supports previous reports in terms of feasibility of the WATSON Trauma Pathway Explorer and emphasises its relevance to predict SIRS, sepsis, and early death when compared with the TRISS method. |
topic |
polytrauma WATSON Trauma Pathway Explorer outcome SIRS sepsis early death |
url |
https://www.mdpi.com/2077-0383/10/10/2115 |
work_keys_str_mv |
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