• J Sainz Cabrejas, C García Fuentes, C García Juarranz, A M González López, L Maure Blesa, J C Montejo González, and M Chico Fernández.
• Servicio de Medicina Intensiva, Hospital Universitario 12 de Octubre, Madrid, España. Electronic address: jvsc89@gmail.com.
• Med Intensiva. 2020 Aug 1; 44 (6): 325-332.

ObjectiveTo evaluate the ability of the TRISS and PS14 models to predict mortality rates in our medical system and population.DesignA retrospective observational study was carried out over a 66-month period.BackgroundThe study was conducted in the Trauma Intensive Care Unit (ICU) of a third level hospital.PatientsAll severe trauma patients (Injury Severity Score≥16 and/or Revised Trauma Score <12) aged> 14 years were included.Variables Of InterestMedical care data were prospectively recorded. The "W" statistic (difference between expected and observed mortality for every 100 patients) and its significance were calculated for each model. Discrimination and calibration were evaluated by means of receiver operating characteristic (ROC) curves, and the Hosmer-Lemeshow test and GiViTI calibration belt, respectively.ResultsA total of 1240 patients were included. Survival at hospital discharge was 81.9%. The "W" scores for the TRISS, TRISS 2010 and PS14 models were+6.72 (P<.01), +1.48 (P=.08) and +2.74 (P<.01) respectively. Subgroup analysis revealed significant favorable results for some populations. The areas under the ROC curve for the TRISS, TRISS 2010 and PS14 models were 0.915, 0.919 and 0.914, respectively. There were no significant differences among them (P>.05). Both the Hosmer-Lemeshow test and GiViTI calibration belt demonstrated poor calibration for the three models.ConclusionsThese models are suitable tools for assessing quality of care in a Trauma ICU, affording excellent discrimination but poor calibration. In our institution, survival rates higher than expected were observed.Copyright © 2019 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

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