ArticleCritical care (London, England)2016
Development and validation of a prehospital prediction model for acute traumatic coagulopathy.
Article in Critical care (London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Early Identification of Acute Traumatic Coagulopathy Using Clinical Prediction Tools: A Systematic Review.Medicina (Kaunas, Lithuania) · 2019Pooled it
- Construction and preliminary trial test of a decision-making app for pre-hospital damage control resuscitation.Chinese journal of traumatology = Zhonghua chuang shang za zhi · 2025Article
- Predicting postoperative trauma-induced coagulopathy in patients with severe injuries by machine learning.Scientific reports · 2025Article
- Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study.Journal of medical Internet research · 2025Article
- Development and validation of the tic score for early detection of traumatic coagulopathy upon hospital admission: a cohort study.Critical care (London, England) · 2024Article
- A cost-aware framework for the development of AI models for healthcare applications.Nature biomedical engineering · 2022Article
- Can Prehospital Data Improve Early Identification of Sepsis in Emergency Department? An Integrative Review of Machine Learning Approaches.Applied clinical informatics · 2022Review
- A Machine Learning Approach for the Prediction of Traumatic Brain Injury Induced Coagulopathy.Frontiers in medicine · 2021Article
- Tools to predict acute traumatic coagulopathy in the pre-hospital setting: a review of the literature.British paramedic journal · 2020Article
- Institution-Specific Machine Learning Models for Prehospital Assessment to Predict Hospital Admission: Prediction Model Development Study.JMIR medical informatics · 2020Article
- Early identification of trauma patients in need for emergent transfusion: results of a single-center retrospective study evaluating three scoring systems.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2019Article
- The European guideline on management of major bleeding and coagulopathy following trauma: fifth edition.Critical care (London, England) · 2019Article
- Thromboelastometry and Thrombelastography Analysis under Normal Physiological Conditions - Systematic Review.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2017Article
- A Machine Learning-Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
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7 authors.
Funding
Abstract
backgroundAcute traumatic coagulopathy (ATC) is a syndrome of early, endogenous clotting dysfunction that afflicts up to 30% of severely injured patients, signaling an increased likelihood of all-cause and hemorrhage-associated mortality. To aid identification of patients within the likely therapeutic window for ATC and facilitate study of its mechanisms and targeted treatment, we developed and validated a prehospital ATC prediction model.
methodsConstruction of a parsimonious multivariable logistic regression model predicting ATC - defined as an admission international normalized ratio >1.5 - employed data from 1963 severely injured patients admitted to an Oregon trauma system hospital between 2008 and 2012 who received prehospital care but did not have isolated head injury. The prediction model was validated using data from 285 severely injured patients admitted to a level 1 trauma center in Seattle, WA, USA between 2009 and 2013.
resultsThe final Prediction of Acute Coagulopathy of Trauma (PACT) score incorporated age, injury mechanism, prehospital shock index and Glasgow Coma Score values, and prehospital cardiopulmonary resuscitation and endotracheal intubation. In the validation cohort, the PACT score demonstrated better discrimination (area under the receiver operating characteristic curve 0.80 vs. 0.70, p = 0.032) and likely improved calibration compared to a previously published prehospital ATC prediction score. Designating PACT scores ≥196 as positive resulted in sensitivity and specificity for ATC of 73% and 74%, respectively.
conclusionsOur prediction model uses routinely available and objective prehospital data to identify patients at increased risk of ATC. The PACT score could facilitate subject selection for studies of targeted treatment of ATC.
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