Roghieh Molaei-Langroudi; Ahmad Alizadeh; Ehsan Kazemnejad-Leili; Vahid Monsef-Kasmaie; Seyed-Younes Moshirian
Volume 7, Issue 3 , July 2019, , Pages 269-277
Abstract
Objective: To investigate the risk factors that can be proper indications for performing brain computerized tomography (CT)-scan in patients with mild and moderate traumatic brain injury (TBI) in order to avoid unnecessary exposure to radiation, saving on costs as well as time wasted in emergency wards.Methods: ...
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Objective: To investigate the risk factors that can be proper indications for performing brain computerized tomography (CT)-scan in patients with mild and moderate traumatic brain injury (TBI) in order to avoid unnecessary exposure to radiation, saving on costs as well as time wasted in emergency wards.Methods: Data of patients with mild traumatic brain injury (TBI) referring to Emergency Department with age ≥2 years and primary GCS of 13-15 were examined including focal neurological deficit, anisocoria, skull fracture, multiple trauma, superior injury of clavicle, decreased consciousness, and amnesia. Brain CT-scan was performed in all the patients. Kappa Coefficient was used to determine the ratio of agreement of the CT indications (+ and ⎼) and multiple logistic regression to determine the relative odds of positive CTs.Results: Overall we included 610 patients. One-hundred and one patients (16.5%) had positive and 509 (83.5%) had negative CT findings. Of positive CTs, the highest percentage was dedicated to high-energy mechanism of trauma. High-energy trauma mechanism (OR=1.056, 95% CI, OR, 1.03-1.04, P<0.001), superior injury of clavicle (OR=1.07, 95% CI, OR, 1.03-1.1, P<0.001) and moderate to severe headache (OR=1.04, 95% CI, OR, 1.02-1.05, P<0.001) were positive predictors of CT findings. The combined mean of positive symptoms equaled 0.29 ± 0.64 in negative CTs, but 5.13 ± 2.4 in positive CTs, showing a significant difference. (P<0.001)Conclusion: Abnormal positive brain CT in victims with mild TBI is predictable if one or several risk factors are taken into account such as moderate to severe headache, decreased consciousness, skull fracture, high-energy trauma mechanism, superior injury of clavicle and GCS of 13-14. The more the symptoms, the more likely the positive CT results would be.
Elahe Parva; Reza Boostani; Zahra Ghahramani; Shahram Paydar
Volume 5, Issue 2 , April 2017, , Pages 90-95
Abstract
Clinical databases can be categorized as big data, include large quantities of information about patients and their medical conditions. Analyzing the quantitative and qualitative clinical data in addition with discovering relationships among huge number of samples using data mining techniques could unveil ...
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Clinical databases can be categorized as big data, include large quantities of information about patients and their medical conditions. Analyzing the quantitative and qualitative clinical data in addition with discovering relationships among huge number of samples using data mining techniques could unveil hidden medical knowledge in terms of correlation and association of apparently independent variables. The aim of this research is using predictive algorithm for prediction of trauma patients on admission to hospital to be able to predict the necessary treatment for patients and provided the necessary measures for the trauma patients who are before entering the critical situation. This study provides a review on data mining in clinical medicine. The relevant, recently-published studies of data mining on medical data with a focus on emergency medicine were investigated to tackle pros and cons of such approaches. The results of this study can be used in prediction of trauma patient’s status at six hours after admission to hospital.
