The aim of this study was to investigate the relationship between pulmonary thromboembolism (PTE) and serum endocan levels. The study included 46 patients with a diagnosis of PTE and control group (25 healthy individuals). Serum endocan levels in all participants' blood samples were measured. The average age of the individuals was 61.76 ± 16.39 years. There was a significant difference in the serum endocan levels between the patients and those of the control group [321.93 ng/l (111.35-2511.33) and 192.77 ng/l (118.30-309.02), respectively; P < 0.030]. The serum endocan levels in the submassive [469.41 ng/l (258.13-800.54)] and the massive PTE groups [719.18 ng/l (319.84-2511.33)] were statistically higher than those in the control group [192.77 ng/l (118.30-309.02)] (P < 0.001 and P < 0.001, respectively). In addition, there was a statistically significant difference between the serum endocan levels of the nonmassive PTE group [188.57 ng/l (111.35-685.56)] and the submassive PTE group (P < 0.01). The serum endocan levels correlated with the international normalization ratio (INR), right ventricular dilatation (RVD) and SBP (r = 0.418, P = 0.004; r = 0.659, P < 0.001; r = -0.425, P = 0.003, respectively). In conclusion, serum endocan levels can be considered a practicable biomarker to determine the severity of PTEs and follow-up thrombolytic therapy.
Trace elements are essential components of biological structures, but alternatively, they can be toxic at concentrations beyond those necessary for their biological functions. Changes in the concentration of essential trace elements and heavy metals may affect acute hemorrhagic stroke. The aim of this study was to measure serum levels of essential trace elements [iron (Fe), zinc (Zn), manganese (Mn), copper (Cu), and magnesium (Mg)] and heavy metals [cobalt (Co), cadmium (Cd), and lead (Pb)] in patients with acute hemorrhagic stroke. Twenty-six patients with acute hemorrhagic stroke and 29 healthy controls were enrolled. Atomic absorption spectrophotometry (UNICAM-929) was used to measure serum Fe, Cu, Pb, Cd, Zn, Co, Mn and Mg concentrations. Serum Cd, Pb and Fe levels were significantly higher in patients with acute hemorrhagic stroke than controls (p < 0.001), while serum Cu, Zn, Mg and Mn levels were significantly lower (all p < 0.001). However, there was no significant difference between the groups with respect to serum Co levels (p > 0.05). We first demonstrate increased Cd, Pb, and Fe levels; and decreased Cu, Zn, Mg, and Mn levels in patients with acute hemorrhagic stroke. These findings may have diagnostic and prognostic value for acute hemorrhagic stroke. Further studies are required to elucidate the roles of trace elements and heavy metals in patients with acute hemorrhagic stroke.
BackgroundUsing computer-based simulation systems in medical education is becoming more and more common. Although the benefits of practicing with these systems in medical education have been demonstrated, advantages of using computer-based simulation in emergency medicine education are less validated. The aim of the present study was to assess the success rates of final year medical students in doing emergency medical treatment and evaluating the effectiveness of computer-based simulation training in improving final year medical students’ knowledge.MethodsTwenty four Students trained with computer-based simulation and completed at least 4 hours of simulation-based education between the dates Feb 1, 2010 - May 1, 2010. Also a control group (traditionally trained, n =24) was chosen. After the end of training, students completed an examination about 5 randomized medical simulation cases.ResultsIn 5 cases, an average of 3.9 correct medical approaches carried out by computer-based simulation trained students, an average of 2.8 correct medical approaches carried out by traditionally trained group (t = 3.90, p < 0.005). We found that the success of students trained with simulation training in cases which required complicated medical approach, was statistically higher than the ones who didn’t take simulation training (p ≤ 0.05).ConclusionsComputer-based simulation training would be significantly effective in learning of medical treatment algorithms. We thought that these programs can improve the success rate of students especially in doing adequate medical approach to complex emergency cases.
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