Abstract:

Objective  To analyze the training results of electroencephalogram (EEG) for brain death determination and to improve the training program.  Methods  A total of 114 trainees received theoretical training, simulation skills training, bedside skills training and test analysis. The composition of the trainees and the results of EEG tests were analyzed. The error rates of 5 knowledge points of EEG tests were calculated. Univariate and multivariate backward Logistic regression analyses were used to analyze the influence of factors including sex, age, specialty, professional category, professional qualification and hospital level on the error rates. Results  All of 114 trainees came from 72 hospitals. Among them, 91 trainees (79.82%) were between 30-49 years old, 108 trainees (94.74%) came from third grade, grade A hospitals, and most of them were from Department of Neurology (57.89% , 66/114) and Electrophysiology (19.30% , 22/114). There were 98 clinicians (85.96% ) and 52 trainees (45.61% ) had intermediate certificate. Of the 5 knowledge points, the total error rate was 9.19% (204/2221). Among them, the error rate of parameter setting was the highest (11.40% , 26/228), followed by those of result determination (10.44%, 80/766), recording techniques (10.25%, 69/673), environmental requirements (7.46%, 17/228) and pitfalls (3.68%, 12/326). The error rate of trainees who were older than 50 was significantly higher than that in other ages (P = 0.000, for all). The error rate of technicians was higher than that of clinicians (P = 0.039). Univariate and multivariate Logistic regression analyses showed that age was independent risk factor associated with high error rates (OR = 1.382, 95%CI: 1.156-1.652; P = 0.000).  Conclusions  Among the trainees, degree of mastering the knowledge points is different. The training program should be optimized according to the trainees. More attention should be paid to the difference of EEG between brain death determination and routine check to improve the quality of determination for brain death by EEG.

Key words: Brain death, Electroencephalography, Reference standards, Training (not in MeSH)

摘要：

目的 对脑死亡脑电图确认试验培训效果进行分析，以发现培训模式存在的问题，并加以改进和完善。方法 采用理论培训、模拟技能培训、床旁技能培训和考核后培训的方式对114 名学员进行脑电图确认试验的培训与考核，单因素和多因素后退法Logistic 回归分析评价学员性别、年龄、专科类别、专业岗位、专业技术职称和医院级别等因素对知识点考核错误率的影响。结果 114 名学员中30 ~49 岁占79.82%（91/114），主要来自三级甲等医院（94.74%，108/114）的神经内科（57.89%，66/114）和电生理科（19.30%，22/114），其中医师占85.96%（98/114），中级职称占45.61%（52/114）。5 项知识点考核总错误率为9.19%（204/2221），由高至低依次为脑电图参数设置11.40%（26/228）、结果判定10.44%（80/766）、记录方法10.25%（69/673）、环境要求7.46%（17/228）和注意事项3.68%（12/326）；其中，> 50 岁学员错误率高于其他年龄者（均P = 0.000），技师错误率高于医师（P = 0.039）。单因素和多因素Logistic 回归分析显示，仅年龄是导致考核错误率高的独立危险因素（OR = 1.382，95%CI：1.156 ~ 1.652；P = 0.000）。结论 不同学员对知识点的掌握程度存在差异，应加强针对重点对象的培训力度，重视脑死亡脑电图确认试验与常规脑电图监测的区别，提高脑死亡脑电图确认试验的判定质量。

关键词: 脑死亡, 脑电描记术, 参考标准, 培训（非MeSH 词）