1.Meta- analysis of the effect of single hand pipe method on venous indwelling needle puncture
Lina CUI ; Jiqing XIA ; Xun SU
Chinese Journal of Practical Nursing 2017;33(14):1108-1116
Objective To evaluate the effect of single hand pipe method on venous indwelling needle puncture. Methods Literature about the impact of single hand pipe method on venous indwelling needle puncture was retrieved from digital databases of PubMed, Medline, EMbase, The Cochrane Library, SinoMed, VIP database, China National Knowledge Infrastructure(CNKI), and WanFang Data. The quality of literature was evaluated by the Cochrane Handbook (5.1.0). The Meta data was analyzed by RevMan 5.3. Results Ten random control trials were included . Ten studies indicated that single hand pipe method increased success rate of puncture[related to the risk(RR)=1.16, 95%confidence interval(CI) 1.11-1.22]. And, it decreased the complication rate (3 studies) (RR=0.32, 95%CI 0.13-0.79) and pain rate(2 studies) (RR=0.25, 95%CI 0.13-0.47) as well as shorten the time of tube(2 studies) (WMD:-1.68, 95%CI-2.44--0.93). Conclusions Single hand pipe method can improve a puncture success rate and reduce complications and pain rate and shorten the time of tube, so that get more time to rescue the patient, and improve the level of the working efficiency and nursing for the nursing staff. In addition, to some extent, save manpower. It is worth being popularized.
2.Changes in electroencephalogram in rat epilepsy model via nonlinear dynamical approach
Minguang XU ; Peng XIA ; Yong JIANG ; Kaiping LONG ; Jiqing YANG
Chinese Journal of Tissue Engineering Research 2005;9(21):216-218
BACKGROUND: The dynamic characteristics of electroencephalogram (EEG) include a decrease in the chaotic dimension, the correlation dimen sion, the Lyapunov exponent, the chaotic complexity, the freedom of EEG and an enhanced synchronization and periodicity of the EEG from several minutes to tens of minutes before epileptic seizures. All these characteristics prefigure the forthcoming seizures. Some studies have proven that the non linear dynamical system can be used as a feasible approach to explore the potential variables for describing the chaos portrait of EEG. OBJECTIVE: To analyze the electric characteristics of EEG signal in the epileptic seizures in rat model by investigating the nonlinear dynamical variables, such as the approximate entropy (ApEn) and correlation dimen sion. DESIGN: Observational and experimental study based on animals. SETTING: Department of Medical Engineering, Department of Gastroen terology, Second Artilleryman General Hospital of Chinese PLA; Department of Physics, Faulty of Biomedical Engineering, Fourth Military Medical Uni versity of Chinese PLA. MATERIALS: From September 2001 to January 2002, this study was conducted at the Complexity Laboratory of the Biomedical Department of the Fourth Military Medical University of Chinese PLA. Six male SD rats,weighing 150- 200 g, were selected.INTERVENTIONS: After intraperitoneal injection of chloral hydrate (0. 5 mL), the male SD rats were deeply anesthetized. When their EEG signal became stable, bemegride injection was diluted at 1:1 with saline and was given on a volume of 0.5 mL to the rats intraperitoneally. After a while,the epileptic seizures started marked by a spasm with a deep roar. The entire epileptic seizures were recorded. According to the shape of EEG waves and the corresponding symptoms of the rats during their seizures, data of the four phases, referring to normal condition, preictal phase, ictal phase and postictal phases of epileptic seizures, were selected for nonlinear analysis. The variations of the ApEn and the correlation dimension were calculated.MAIN OUTCOME MEASURES: In the four phases of the seizures, before seizures, preictal phase, ictal phase and postictal phases, the changes in the ApEn and correlation dimension were observed.RESULTS: All the 6 rats entered the statistical procedure. During epilepsy, the ApEn and correlation dimension of the EEG signal in ictal phases (0. 447 ±0. 126, 2. 166 ±0. 377) decreased significantly while those in preictal phases(0. 807 ±0. 182, 4. 773 ±0. 319) and postictal phases (1. 241 ±0. 125, 6. 042 ±0. 373) (t = -3. 984to 17. 902, P <0. 01). The ApEn and the correlation dimension of the EEG signal in preictal and ictal phases had significant difference with those observed under normal conditions (1.313 ± 0. 090, 6. 405 ± 0. 694) (t = -5. 228 to 12. 740, P < 0. 01 ).CONCLUSION: The changes in ApEn and correlation dimension showed by nonlinear dynamical approach in this study reflect the characteristics of EEG signals in preictal time, ictal time and postictal timeof the epileptic seizures and the differences among them. Additionally, they also reveal the laws in the changes of the complex ictal EEG signal.
3.CT scan evaluation of tumor response to thermoradiation therapy
Qingxuan SUN ; Tingyi XIA ; Xiaoli SHI ; Zuoren WANG ; Jiqing CUI
Chinese Journal of Radiation Oncology 1992;0(04):-
80% of low density area in tumor), 10 PR(50%-80%) and 3 NC(0.05). Conclusion For tumor treated with hyperthermia plus radiotherapy, the response evaluation should be based on both the change in the mass size and the percentage of low density area in the tumor.
4.Analysis of the EEG information of rats epileptic model using unstable periodic orbits.
Minguang XU ; Peng XIA ; Boyuan YU ; Jiqing YANG ; Wei YAN ; Baoyue QIU ; Shen CHEN ; Xueying GUO
Journal of Biomedical Engineering 2005;22(3):584-587
In order to further research into the EEG information of rats epileptic model, we applied different nonlinear dynamic methods. After having analyzed the EEG signal of rat falling sickness by means of approximate entropy and correlation dimension, we adopted a the new method, unstable periodic orbits, which was used to analyze complex activity of neurons system to look for the change regularity of change in the EEG signal in the whole course of rat's falling sickness. We found period 1 orbits and period 2 orbits to be statistically significant in the data of ictal time of epilepsy. At the same time, we found period 1 orbits to be statistically significant in the data of preictal time of epilepsy.
Animals
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Disease Models, Animal
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Electroencephalography
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Entropy
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Epilepsy
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physiopathology
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Nonlinear Dynamics
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Rats
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Signal Processing, Computer-Assisted