[Prediction of new outbreaks of myocardial infarction, based on a multivariate meteorological analysis].

J C Cohen, G der Megreditchian, N Gerbier, E Choisnel, D Pezzi-Giraud, J Pasteyer, M Poisvert, F Besançon
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Abstract

In a previous paper, meteorological circumstances of myocardial infarctions, cerebrovascular attacks, and suicidal attempts were studied by a univariate method. The present work used the same clinical reports, collected by the Medical Emergency Assistance System (SAMU) in the Paris area from 1975 to 1977, but with multivariate calculations. 150 potential predictive indicators were submitted to "progressive ascending selection". Selected indicators were then combined into a composite index by "linear canonic discrimination". This index was tested in terms of successful prediction. The 150 indicators were: 1) meteorological variables, recorded at ground level, such as wind and temperature (expressed respectively in 28 and 24 ways), airpressure, moisture; 2) variables computed from data recorded in altitude; 3) pollutants; 4) non-meteorological indicators, such as day of the week, season, solar activity; 5) the "past of the predictand", i.e. the frequency of infarctions during the previous days; 6) types of weather, defined after confronting meteorological maps with clinical data. The coding of qualitative data required a new procedure. The event to be predicted, which occurred only one day a week, was an incidence of infarctions of at least twice the average. The percentage of successful prediction was 78.7%. The type of weather was by far the best indicator. Detrimental circumstances were changing weathers, with in the order of decreasing correlations, atmosphere fluxes coming from S-SE, E, SW, and NW. These results complete those of univariate analysis. They validate a simple and efficient predictive method, similar in its principle to that used in Germany.

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[基于多变量气象分析的心肌梗死新爆发预测]。
在以前的一篇论文中,用单变量方法研究了心肌梗死、脑血管发作和自杀企图的气象环境。本研究使用了相同的临床报告,这些报告是由医疗紧急援助系统(SAMU)从1975年到1977年在巴黎地区收集的,但采用了多变量计算。150个潜在预测指标提交“递进升序选择”。然后通过“线性正则判别”将选定的指标组合成一个综合指数。该指标在成功预测方面进行了测试。150个指标是:1)气象变量,记录在地面,如风和温度(分别用28和24种方式表示)、气压、湿度;2)根据海拔记录数据计算的变量;3)污染物;4)非气象指标,如星期几、季节、太阳活动等;5)“预测对象的过去”,即前几天发生梗死的频率;6)天气类型,在气象地图与临床数据对比后定义。定性数据的编码需要一个新的程序。被预测的事件每周只发生一天,梗死的发生率至少是平均值的两倍。预测成功率为78.7%。到目前为止,天气类型是最好的指示器。不利的环境是不断变化的天气,从相关性递减的顺序来看,大气通量来自东南、东南、西南和西北。这些结果完成了单变量分析的结果。他们验证了一种简单而有效的预测方法,其原理与德国使用的方法相似。
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