Analysis on the training effect of criteria and practical guidance for determination of brain death: clinical diagnosis

Abstract

Objective Clinical diagnosis is the most predominant in the criteria for determination of brain death. This paper aims to analyze the training results of clinical diagnosis for brain death determination and to improve the training program. Methods A total of 461 trainees received theoretical training, simulation skills training, bedside skills training and test analysis. The composition of trainees was analyzed and the error rates of knowledge points were calculated. Univariate and multivariate backward Logistic regression analyses were used to analyze the influence of factors including sex, age, specialty, professional qualification and hospital level, on the error rates. Results Four hundred and sixty-one trainees came from 161 hospitals. Among them, trainees of 30-49 years old occupied 77.87% (359/461), and most of them came from third grade, grade A hospitals (88.29%, 407/461). There were 200 trainees (43.39% ) from Department of Neurology, 109 trainees (23.64% ) from Department of Neurosurgery, and 88 trainees (19.09%) from Intensive Care Unit. Most of them (66.59%, 307/461) had senior certificate. Total error rate of 13 knowledge points was 5.81% (1054/18 128). The error rate of corneal reflex was the highest (24.64% , 104/422), followed by deep coma (11.59% , 365/3149), oculocephalogyric reflex (9.48%, 40/422), step and time of determination (7.48%, 138/1844), and pupillary light reflex (5.10% , 90/1766). Univariate and multivariate Logistic regression analyses showed that age (OR = 1.558, 95%CI: 1.435-1.693; P = 0.000), specialty (OR = 1.080, 95%CI: 1.021-1.143; P = 0.007) and hospital level (OR = 1.395, 95%CI: 1.174-1.659; P = 0.000) were independent risk factors associated with high error rates. Conclusions The training patterns and methods of clinical diagnosis for brain death determination should be further improved, especially the individual training, to rise the training quality.

DOI: 10.3969/j.issn.1672-6731.2015.12.006