Abstract:Objective To analyze the hypercoagulable state and risk factors in patients with acute cerebral infarction (CI)among military officers using thromboelastography. Methods A total of 200 military officers with acute cerebral infarctions admitted to our department between January 2016 and July 2017 were selected as the case group, while another 200 military officers over 50 years old and under health checkups were selected as the control group. Eight primary risk factors for cerebral infarctions were retrospectively analyzed, and thromboelastography was used to detect coagulation function in patients in the two groups. Two sample t test and logistic regression equation were used to analyze the relationships between the main risk factors and TEG. Results There was significant difference in such TEG parameters as R values (t=5.472, P<0.001), K values (t=7.434, P<0.001), α-Angle (t=7.531, P<0.001)and MA values (t=6.997, P<0.001) between the two groups. There was statistically significant difference in such risk factors as smoking (χ2=4.64, P=0.031), excessive drinking (χ2=6.17, P=0.013) and working overtime (χ2=4.48, P=0.034) between the two groups. However, there was no statistically significant difference in tea drinking, insomnia, amount of water drinking, high-salt diet or family history of stroke. Among these risk factors, smoking had the strongest influence on TEG indexes of the case group, followed by drinking, insomnia, high salt diet and a family history of cerebral infarction, while tea drinking was a protection factor. Conclusions The blood of patients with acute cerebral infarction among military officers is hypercoagulable. Long-term smoking, drinking, insomnia, and high-salt diet may accelerate the formation of the hypercoagulable state, and tea drinking can reduce the formation.
George P M, Steinberg G K . Novel stroke therapeutics: unraveling stroke pathophysiology and its impact on clinical treatments[J]. Neuron, 2015, 87(2):297-309.
[2]
Adler M, Ivic S, Bodmer N S, et al. Thromboelastometry and thrombelastography analysis under normal physiological conditions-systematic review[J]. Transfus Med Hemother, 2017, 44(2): 78-83.
Gosselin R C, Estacio E E, Song J Y, et al. Verifying the performance characteristics of the TEG5000 thromboelastogram in the clinical laboratory[J].Int J Lab Hematol, 2016, 38(2):183-192.
Wang J, Wen X, Li W, et al. Risk factors for stroke in the chinese population: a systematic review and meta-analysis[J]. J Stroke Cerebrovasc Dis, 2017, 26(3):509-517.
[7]
Safiri S, Ayubi E. Smoking,hypertension, and their combined effect on ischemic stroke incidence: a prospective study among inner mongolians in china: methodological and statistical issues[J]. J Stroke Cerebrovasc Dis, 2017, 26(12): 749-754.
[8]
Zhang C, Qin Y, Chen Q, et al. Alcohol intake and risk of stroke: a dose-response meta-analysis of prospective studies[J].Int J Cardiol, 2014, 174(3): 669-677.
[9]
Klatsky A L, Tran H N. Alcohol and stroke: the splitters win again[J]. BMC Medicine, 2016, 14(1):14.
Feng J H, Pomborodrigues S, Macgregor G A. Salt reduction in england from 2003 to 2011: its relationship to blood pressure, stroke and ischaemic heart disease mortality[J]. BMJ Open, 2014, 4(4):e4549.
[12]
Eguchi K, Hoshide S, Ishikawa S, et al. Short sleep duration is an independent predictor of stroke events in elderly hypertensive patients[J]. J Am Soc Hypertens, 2010, 4(5):255-262.
[13]
Shen L, Song L G, Ma H, et al. Tea consumption and risk of stroke: a dose-response meta-analysis of prospective studies[J]. J Zhejiang Univ Sci B, 2012, 13(8):652-662.