我国军事飞行员停飞疾病谱的Meta分析

Meta-analysis of disease spectrum associated with flying disqualification of Chinese military pilots

目的对公开发表的我国军事飞行员停飞疾病谱数据进行汇总,运用Meta分析方法了解我国军事飞行员停飞疾病构成,评价疾病特点与影响因素,为军事飞行员招收培养和健康维护等工作提供循证依据。方法检索中国知网(CNKI)、万方数据(WanFang Data)、重庆维普(VIP),以及PubMed等数据库中有关我国军事飞行员停飞疾病谱的文献,使用R3.4.3软件对停飞疾病的构成进行率的合并,检验异质性并选择相应的效应模型,通过线性回归法识别发表偏倚,同时依据调查时间进行亚组分析。结果纳入研究13篇文献,总人数4 326人,Meta分析结果显示,我国军事飞行员医学原因停飞疾病构成比前7位依次为神经衰弱、晕厥、头痛、脊柱疾病、高血压、屈光不正、前庭功能不良。2000年后,因神经衰弱、晕厥、屈光不正原因停飞占比下降,因脊柱疾病、高血压、头痛原因停飞占比大幅提升,均具有统计学意义。结论心身疾病是导致停飞的主要因素,飞行环境与停飞疾病密切相关,飞行员选拔培养应重视循证决策。

Objective To summarize the disease spectrum data of Chinese military pilots who were disqualified for flight for medical reasons using meta-analysis, to find out about the composition of diseases, and to identify the characteristics and influencing factors so as to provide evidence for the recruitment, training and health maintenance of military pilots. Methods Published literature on the disease spectrum resulting in flying disqualification of Chinese military pilots was retrieved from CNKI, Wanfang Data, VIP and the Pubmed. The rates of disease composition were combined, the heterogeneity of data tested and the corresponding effect model was selected by R 3.4.3 software. Publication bias was identified by linear regression and subgroup analysis was performed based on the survey time. Results Thirteen pieces of literature were included in the study, involving a total number of 4 326 pilots. Meta-analysis results showed that the top seven diseases responsible for flying disqualification of Chinese military pilots were neurasthenia, syncope, headache, spinal disease, hypertension, ametropia, and vestibular dysfunction. After the year of 2000, the proportion of flying disqualification due to neurasthenia, syncope and ametropia decreased, while that of spinal diseases, hypertension and headache increased, and the difference was of statistical significance. Conclusion Psychosomatic diseases are the main factors leading to flying disqualification, and the flight environment is closely related to diseases. In addition, evidence-based decision-making should be emphasized in pilot selection and training.