Clinical decision support for severe trauma patients: Machine learning based definition of a bundle of care for hemorrhagic shock and traumatic brain injury. Issue 1 (January 2022)

• Record Type: Journal Article
• Authors: Lang, Elodie; Neuschwander, Arthur; Favé, Gersende; Abback, Paer-Selim; Esnault, Pierre; Geeraerts, Thomas; Harrois, Anatole; Hanouz, Jean-Luc; Kipnis, Eric; Leone, Marc; Legros, Vincent; Mellati, Nouchan; Pottecher, Julien; Hamada, Sophie; Pirracchio, Romain
• Is Part Of: Journal of trauma and acute care surgery. Volume 92:Issue 1(2022)
• Publication Date: 2022-01
• Subjects: Hemorrhagic shock -- traumatic brain injury -- machine learning -- bundle of care -- compliance; Surgical intensive care -- Periodicals; Surgical emergencies -- Periodicals; Wounds and injuries -- Surgery -- Periodicals; 617.026
• DOI: 10.1097/TA.0000000000003401
• Languages: English
• ISSNs: 2163-0755

Abstract

Abstract : BACKGROUND: Deviation from guidelines is frequent in emergency situations, and this may lead to increased mortality. Probably because of time constraints, 55% is the greatest reported guidelines compliance rate in severe trauma patients. This study aimed to identify among all available recommendations a reasonable bundle of items that should be followed to optimize the outcome of hemorrhagic shocks (HSs) and severe traumatic brain injuries (TBIs). METHODS: We first estimated the compliance with French and European guidelines using the data from the French TraumaBase registry. Then, we used a machine learning procedure to reduce the number of recommendations into a minimal set of items to be followed to minimize 7-day mortality. We evaluated the bundles using an external validation cohort. RESULTS: This study included 5, 924 trauma patients (1, 414 HS and 4, 955 TBI) between 2011 and August 2019 and studied compliance to 36 recommendation items. Overall compliance rate to recommendation items was 71.6% and 66.9% for HS and TBI, respectively. In HS, compliance was significantly associated with 7-day decreased mortality in univariate analysis but not in multivariate analysis (risk ratio [RR], 0.91; 95% confidence interval [CI], 0.90–1.17; p = 0.06). In TBI, compliance was significantly associated with decreased mortality in univariate and multivariate analysis (RR, 0.85; 95% CI, 0.75–0.92; p = 0.01). For HS, the bundle included 13 recommendation items. In the validation cohort, when this bundle was applied, patients were found to have a lower 7-day mortality rate (RR, 0.46; 95% CI, 0.27–0.63; p = 0.01). In TBI, the bundle included seven items. In the validation cohort, when this bundle was applied, patients had a lower 7-day mortality rate (RR, 0.55; 95% CI, 0.34–0.71; p = 0.02). DISCUSSION: Using a machine-learning procedure, we were able to identify a subset of recommendations that minimizes 7-day mortality following traumatic HS and TBI. These two bundles remain to be evaluated in a prospective manner. LEVEL OF EVIDENCE: Care Management, level II. Abstract : Supplemental digital content is available in the text.