摘要：

目的 对脑死亡短潜伏期体感诱发电位（SLSEP）确认试验的培训效果进行分析，以改进和完善脑死亡判定标准和技术规范。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101 名受训学员进行SLSEP 确认试验培训，以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对各知识点考核错误率的影响。结果 101 名学员中30 ~ 49 岁占76.24%（77/101），主要来自三级甲等医院（98.02%，99/101）的神经内科（77.23%，78/101），其中医师占81.19%（82/101），高级和中级职称分别占30.69%（31/101）和41.58%（42/101）。6项知识点考核总错误率为4.50（91/2020），由高至低依次为SLSEP 注意事项9.41%（19/202）、结果判定5.94%（12/202）、记录方法4.75%（24/505）、操作步骤3.96%（32/808）、确认试验顺序1.98%（2/101）和环境条件0.99%（2/202）。单因素和多因素Logistic 回归分析显示，年龄（OR = 1.566，95%CI：1.116 ~2.197；P = 0.009）和专业技术职称（OR = 1.669，95%CI：1.163 ~ 2.397；P = 0.005）为导致试卷考核错误率高的独立危险因素。结论 应加强受训学员对脑死亡SLSEP 确认试验与常规诱发电位检测的鉴别能力，以提高该项试验对脑死亡的判定质量。

关键词: 脑死亡, 诱发电位, 躯体感觉, 参考标准, 培训（非MeSH 词）

Abstract:

Objective  To analyze the training results of short-latency somatosensory-evoked potential (SLSEP) for brain death determination and to improve the training program.  Methods  A total of 101 trainees received theoretical training, simulation skills training, bedside skills training and test analysis for SLSEP in brain death determination. The composition of trainees was analyzed and the error rates of 6 knowledge points 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  Among them, trainees of 30-49 years old occupied 76.24% (77/101), most of them were from third grade, grade A hospitals (98.02%, 99/101), and 78 trainees (77.23%) were from Department of Neurology. There were 82 clinicians (81.19%), 31 (30.69%) had senior certificate and 42 (41.58%) had intermediate certificate. Total error rate of 6 knowledge points was 4.50% (91/2020). Of the 6 knowledge points, the error rate of pitfalls was the highest (9.41%, 19/202), followed by result determination (5.94% , 12/202), recording techniques (4.75% , 24/505), procedures (3.96%, 32/808), sequence of confirmatory tests (1.98%, 2/101) and environmental conditions (0.99%, 2/202). Univariate and multivariate Logistic regression analyses showed that age (OR = 1.566, 95% CI: 1.116-2.197; P = 0.009) and professional qualification (OR = 1.669, 95% CI: 1.163-2.397; P = 0.005) were independent risk factors associated with high error rates.  Conclusions  The differences between brain death determination and routine check of SLSEP should be paid more attention to improve the quality of determination for brain death by SLSEP.

Key words: Brain death, Evoked potentials, somatosensory, Reference standards, Training (not in MeSH)