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- 저자 : Hosseinali Khalili (검색결과 2 건)
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Mehdi Nourelahi,Fardad Dadboud,Hosseinali Khalili,Amin Niakan,Hossein Parsaei 대한중환자의학회 2022 Acute and Critical Care Vol.37 No.1
Background: Traumatic brain injury (TBI), which occurs commonly worldwide, is among the more costly of health and socioeconomic problems. Accurate prediction of favorable outcomes in severe TBI patients could assist with optimizing treatment procedures, predicting clinical outcomes, and result in substantial economic savings.Methods: In this study, we examined the capability of a machine learning-based model in predicting “favorable” or “unfavorable” outcomes after 6 months in severe TBI patients using only parameters measured on admission. Three models were developed using logistic regression, random forest, and support vector machines trained on parameters recorded from 2,381 severe TBI patients admitted to the neuro-intensive care unit of Rajaee (Emtiaz) Hospital (Shiraz, Iran) between 2015 and 2017. Model performance was evaluated using three indices: sensitivity, specificity, and accuracy. A ten-fold cross-validation method was used to estimate these indices.Results: Overall, the developed models showed excellent performance with AUC around 0.81, sensitivity and specificity of around 0.78. The top-three factors important in predicting 6-month post-trauma survival status in TBI patients are “Glasgow coma scale motor response,” “pupillary reactivity,” and “age.”Conclusions: Machine learning techniques might be used to predict the 6-month outcome in TBI patients using only the parameters measured on admission when the machine learning is trained using a large data set.
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Shahram Paydar,Behnam Dalfardi,Hosseinali Khalili,Golnar Sabetian,Shahram Bolandparvaz,Mohammad Hadi Niakan,Hamidreza Abbasi,Donat R. Spahn 대한마취통증의학회 2017 Korean Journal of Anesthesiology Vol.70 No.6
Background: The current study assessed a recently developed resuscitation protocol for bleeding trauma patients called the Targeted Transfusion Protocol (TTP) and compared its results with those of the standard Massive Transfusion Protocol (MTP). Methods: Per capita utilization of blood products such as packed red blood cells (RBCs), fresh frozen plasma (FFP), and platelet concentrates was compared along with mortality rates during two 6-month periods, one in 2011 (when the standard MTP was followed) and another in 2014 (when the TTP was used). In the TTP, patients were categorized into three groups based on the presence of head injuries, long bone fractures, or penetrating injuries involving the trunk, extremities, or neck who were resuscitated according to separate algorithms. All cases had experienced motor vehicle accidents and had injury severity scores over 16. Results: No statistically significant differences were observed between the study groups at hospital admission. Per capita utilization of RBC (4.76 ± 0.92 vs. 3.37 ± 0.55; P = 0.037), FFP (3.71 ± 1.00 vs. 2.40 ± 0.52; P = 0.025), and platelet concentrate (1.18 ± 0.30 vs. 0.55 ± 0.18; P = 0.006) blood products were significantly lower in the TTP epoch. Mortality rates were similar between the two study periods (P = 0.74). Conclusions: Introduction of the TTP reduced the requirements for RBCs, FFP, and platelet concentrates in severely injured trauma patients.
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