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晦涩的比较:两组数值对比的问题。

Abstruse comparisons: the problems of numerical contrasts of two groups.

作者信息

Yueh B, Feinstein A R

机构信息

VA Puget Sound Health Care System and Department of Otolaryngology/Head & Neck Surgery, University of Washington, Seattle 98108, USA.

出版信息

J Clin Epidemiol. 1999 Jan;52(1):13-8. doi: 10.1016/s0895-4356(98)00133-4.

DOI:10.1016/s0895-4356(98)00133-4
PMID:9973069
Abstract

The most common quantitative comparison in medical literature is a contrast of two numbers, such as two means or two rates. The two numbers, A and B, can be compared as a direct increment (A-B), ratio (A/B), relative change ([A-B]/B), or other index of contrast. To appreciate the quantitative distinction, a reader must know the "setting" reflected by the basic values of A and B. For example, a ratio of 2.0 does not distinguish comparisons between rates of 60% versus 30% and 0.006% versus 0.003%. Despite the frequency of published comparisons, they can be expressed with two types of abstrusity: quantitatives, if the basic values for A and B are not readily evident; and qualitative, if the component underlying variables are unfamiliar and not suitably explained. Among the published articles during the first six months of 1995 for JAMA and New England Journal of Medicine, 57 that satisfied inclusion criteria were reviewed for compliance with standards for avoiding the two types of abstrusity. The standards for quantitative abstrusity were applied to the published abstract-summary, because it is often the only "sound bite" that is read and remembered by most readers. The standards for qualitative abstrusity, however, could be fulfilled in the text, not just in the abstract-summaries of each article. Among the 57 abstract-summaries, 30% were abstruse quantitatively, and 11 (48%) of 23 pertinent papers were qualitatively abstruse. Abstrusity can be eliminated if authors and editors insist that quantitative contrasts cite the basic numbers being compared and the meaning of the associated variables and their rating scales.

摘要

医学文献中最常见的定量比较是两个数字的对比,比如两个均值或两个比率。这两个数字A和B,可以作为直接增量(A - B)、比率(A/B)、相对变化([A - B]/B)或其他对比指标来进行比较。为了理解这种定量差异,读者必须了解由A和B的基础值所反映的“背景”。例如,2.0的比率无法区分60%与30%的比率比较和0.006%与0.003%的比率比较。尽管已发表的比较很常见,但它们可能会以两种晦涩的形式呈现:如果A和B的基础值不明显,就是定量晦涩;如果基础变量不为人熟悉且未得到适当解释,就是定性晦涩。在1995年上半年发表于《美国医学会杂志》和《新英格兰医学杂志》的文章中,对57篇符合纳入标准的文章进行了审查,看其是否符合避免这两种晦涩形式的标准。定量晦涩的标准应用于已发表的摘要总结,因为它往往是大多数读者阅读并记住的唯一“简短信息”。然而,定性晦涩的标准可以在正文中满足,而不仅仅是在每篇文章的摘要总结中。在这57篇摘要总结中,30%存在定量晦涩问题,在23篇相关论文中,有11篇(48%)存在定性晦涩问题。如果作者和编辑坚持要求定量对比引用所比较的基础数字以及相关变量及其评级量表的含义,晦涩问题是可以消除的。

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Rhinosinusitis: establishing definitions for clinical research and patient care.鼻窦炎:为临床研究和患者护理确立定义。
J Allergy Clin Immunol. 2004 Dec;114(6 Suppl):155-212. doi: 10.1016/j.jaci.2004.09.029.
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