简介：AbstractPurpose:The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury. Early recognition of patients is an important case of such decision-making with risk of worse prognosis. This article is to answer if clinical and paraclinical signs can predict the critical conditions of injured patients after traumatic injury resuscitation.Methods:The study included 1107 trauma patients, 16 years and older. The patients were trauma victims of Levels I and II triage and admitted to the Rajaee (Emtiaz) Trauma Hospital, Shiraz, in 2014-2015. The cross-industry process for data mining methodology and modeling was used for assessing the best early clinical and paraclinical variables to predict the patients' prognosis. Five modeling methods including the support vector machine, K-nearest neighbor algorithms, Bagging and Adaboost, and the neural network were compared by some evaluation criteria.Results:Learning algorithms can predict the deterioration of injured patients by monitoring the Bagging and SVM models with 99% accuracy. The most-fitted variables were Glasgow Coma Scale score, base deficit, and diastolic blood pressure especially after initial resuscitation in the algorithms for overall outcome predictions.Conclusion:Data mining could help in triage, initial treatment, and further decision-making for outcome measures in trauma patients. Clinical and paraclinical variables after resuscitation could predict short-term outcomes much better than variables on arrival. With artificial intelligence modeling system, diastolic blood pressure after resuscitation has a greater association with predicting early mortality rather than systolic blood pressure after resuscitation. Artificial intelligence monitoring may have a role in trauma care and should be further investigated.

简介：AbstractPurpose:Traumatic hemorrhagic shock is a life-threatening event worldwide. Severe brain trauma accompanying femoral fractures can trigger inflammatory responses in the body and increase preinflammatory cytokines such as TNF-α, IL-1. The primary treatment in these cases is hydration with crystalloids, which has both benefits and complications. The purpose of this study was to investigate the effects of fluid therapy on the hemodynamics, coagulation profiles, and blood gases in such patients.Methods:In this cross-sectional study, patients were divided into two groups: femoral fracture group and non-femoral group. The hemodynamic status, coagulation profile, and blood gases of patients in both groups were evaluated upon arrival at the hospital and again 2 h later. Data were analyzed by t-test and ANOVA with repeated data and paired samples t-test.Results:A total of 681 trauma patients (605 men and 76 women) participated in this study, including 69 (86.3%) men and 11 (13.8%) women in femoral fracture group and 536 men (89.2%) and 65 women (10.8%) in non-femoral group. The laboratory parameters were evaluated in response to the equal amount of crystalloid fluid given upon arrival and 2 h later. Blood gases decreased in the fracture group despite fluid therapy (p < 0.003), and the coagulation profile worsened although the change was not statistically significant.Conclusion:The treatment of multiple-trauma patients with femoral bone fractures should be more concerned with the need for the infusion of vasopressors such as norepinephrine. If there is evidence of clinical shock, excessive crystalloid infusion (limited to 1 L) should be avoided, and blood and blood products should be started as soon as possible.