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减压表设计与测试的统计学方面

Statistical aspects of the design and testing of decompression tables.

作者信息

Homer L D, Weathersby P K

出版信息

Undersea Biomed Res. 1985 Sep;12(3):239-49.

PMID:4060333
Abstract

Before a decompression procedure is recommended for general use it is subjected to a limited number of human trial dives. Based on the trial, one attempts to reject unsafe procedures but accept those with a low incidence of decompression sickness (DCS). Binomial confidence regions are often so broad that even after 40 dives it may be impossible to distinguish between the possibility that the table being tested has a 0.6% risk of DCS and the possibility that it has a 17% risk. Our proposed alternative is to select some rule (e.g., one or more cases of DCS in 10 dives) for rejecting tables and to calculate the probabilities of accepting tables as a function of the probability of DCS. With such calculations we conclude that (a) generally one cannot reduce the risk of adopting unsafe tables without increasing the risk of rejecting safe ones unless one chooses to increase the number of test dives; (b) truncated sequential designs could reduce the number of dives required for testing by 15 to 20%; and (c) rules similar to the ones tested will always have a zone of indifference. Tables with a probability of DCS in this zone will be accepted or rejected with nearly equal frequency even if tested with hundreds of dives. The use of models describing the probability of DCS as a function of dive parameters should allow us to combine information from dives previously analyzed separately and perhaps to improve our selection of new tables to be tested.

摘要

在推荐减压程序以供普遍使用之前,会对其进行有限次数的人体试验潜水。基于这些试验,人们试图摒弃不安全的程序,而接受减压病(DCS)发病率较低的程序。二项式置信区间往往很宽,以至于即使经过40次潜水,也可能无法区分被测试表格出现DCS的风险为0.6%的可能性和出现17%风险的可能性。我们建议的替代方法是选择一些规则(例如,10次潜水中出现一例或多例DCS)来摒弃表格,并根据DCS的概率计算接受表格的概率。通过这样的计算,我们得出以下结论:(a)一般来说,除非增加测试潜水的次数,否则在不增加拒绝安全表格风险的情况下,无法降低采用不安全表格的风险;(b)截断序贯设计可以将测试所需的潜水次数减少15%至20%;(c)与所测试规则类似的规则总会存在一个无差异区域。处于该区域的DCS概率的表格,即使经过数百次潜水测试,被接受或拒绝的频率也几乎相等。使用将DCS概率描述为潜水参数函数的模型,应该能让我们整合之前单独分析的潜水信息,并可能改进我们对新测试表格的选择。

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