Acute myocardial infarction is a life-threatening condition. Coronary dissection after blunt chest trauma is a rare event. Chest pain is a common symptom after chest trauma, which may relate to chest contusion without cardiac injury or myocardial infarction. Differentiation between minor cardiac contusion and significant cardiac injury is difficult and it is a challenge for physicians to diagnose traumatic cardiac injury early. We report a case of a 40-year-old man suffering from coronary artery dissection after a blunt chest trauma and intracranial hemorrhage after percutaneous coronary intervention.
The purpose of the present study was to explore the role of gender in the relation of high-sensitivity C-reactive protein (hsCRP), white blood cell (WBC) count, and serum uric acid (UA) to the risk of future cardiovascular disease (CVD) events. In total, 404 workers were recruited to obtain the measurements of serum markers for CVD risk. Demographic data, nutrition, exercise, smoking, and alcohol consumption were assessed through a questionnaire. The Framingham Risk Score (FRS) was adopted to estimate the risk of future CVD events. Multiple linear regression models were used to determine CVD risk markers in relation to the FRS by gender. The hsCRP was not significantly correlated with the FRS for all workers after adjusting for covariates, including demographic data and health-related lifestyle. WBC count was positively correlated with FRS for all workers, but WBC count did not show an interaction with gender with respect to the FRS. Serum UA showed an interaction with gender on the FRS, and UA positively correlated with the FRS in males though not in females. With respect to CVD prevention, the WBC count can be used to monitor the risk for all workers. Due to a gender difference shown in the relationship between serum UA and the FRS, serum UA can be a monitor of the risk of future CVD events in male workers only.
The most important problem to be solved in questionnaire dealing is the laborsaving of the method. In particular, in dealing with open-ended questionnaire are time-consuming and laborious. This study proposes a Delphi web-based opinion survey system, which is designed based on the method for convergence opinion from multiple experts with unstructured data. To demonstrate and evaluate the proposed unstructured data mining methods, Electronic Record Management Systems' questionnaires are adopted. In the experiments, the free-form survey responses are mined on the basis of Chinese word structures. The platform makes opinion convergence more convenient. Finally, we also compare and analyze the results of the manual processing of open-ended questionnaire, and hope this information will be helpful to the survey industry.
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