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目的:人群中存在着急性高原病易感者,为此,对相关研究成果进行分析、评价和系统综合,以建立预测体系和数学模型,用于大部队急进高原时易感者的预测。资料来源:应用计算机检索Medline、PubMed、PML数据库1970-01/2002-12有关急性高原病易感者预测研究的文章,检索词“acutemoun-tainsickness,susceptibleherd,prediction”,限定文章语言种类为英文。同时计算机检索了中国期刊全文数据库、万方数据库和中文生物医学文献数据库1970-01/2004-8的相关文章,检索词“急性高原病、预测、易感人群”,限定文章语言种类为中文。研究对象为急性高原病易感者。最后,采用追溯法补充查找了部分文献和专著。资料选择:通过文献资料的系统分析和归纳,然后筛选出无试验支撑的研究,对剩余的文献开始查找全文,以是否能用于急性高原病易感人群预测为指标纳入标准。资料提炼:共总结出19项预测指标,在此基础上,运用系统分析、专家咨询法、层级分析法(AHP)对预测指标进行了筛选,纳入13项,排除6项。资料综合:按神经-体液调节能力、呼吸系统获氧能力、中枢神经系统抗缺氧能力、心理调适能力及卫勤保障能力进行分类。在此基础上,运用系统分析、专家咨询法、AHP方法对预测指标进行筛选,建立了指标体系,确定了指标权重和指标体系权集,并
OBJECTIVE: There is an acute susceptibility to altitude sickness in the population. To this end, the related research results are analyzed, evaluated and systematically integrated to establish the prediction system and mathematical model for predicting the susceptibility of large units to radical plateau. DATA SOURCES: A computer-based online search of Medline, PubMed and PML databases was conducted from January 1970 to December 2002, and the article “acutemoun-tainsickness, susceptibleherd, prediction” was used to search for the predictive value of susceptibility to acute altitude sickness. The limited article language was English. At the same time, the related articles of Chinese Journal Full-text Database, Wanfang Database and Chinese Biomedical Literature Database from January 1970 to August 2004 were retrieved by computer. The search term “acute altitude sickness, predicted and susceptible population” was used to limit the article language to Chinese. The object of study was acute mountain sickness. Finally, the retrospective method is used to find some documents and monographs. Data selection: Through the systematic analysis and summary of the literature, the study of no experimental support was screened out and the remaining articles were searched to find the full text, and whether the prediction could be used for the prediction of susceptible population of acute mountain sickness as the index was included. DATA EXTRACTION: A total of 19 forecasting indicators were summarized. Based on this, the forecasting indicators were screened by systematic analysis, expert consultation and AHP, including 13 items and 6 items excluded. Data synthesis: According to neuro-humoral regulation, respiratory oxygen capacity, central nervous system anti-anaerobic ability, psychological adjustment ability and medical support ability classification. On this basis, using system analysis, expert consultation and AHP methods to forecast the forecasting index, the paper establishes the index system, determines the index weight and the index system weight set,