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摘要翻译：
目的：通过对一个典型案例的分析，并进一步讨论那些数据似乎与当前知识不一致的情况，探讨反直觉数据的问题。病例：在重症监护数据库（MIMIC-III）中识别了844例术后CABG患者，他们在手术后24小时内拔管。护士引起的疼痛评分记录在他们住院期间，在0到10的范围内。水平以平均值、中位数和最大值进行跟踪，并分为无(0/10)、轻度(1-3)、中度（4-6）和重度疼痛（7-10）。采用回归分析法分析疼痛评分与相关结果（死亡率和住院费用）之间的关系。经过协变量调整后，疼痛水平的增加被发现与较低的死亡率和较低的医院损失有关。结论：这些与CABG术后疼痛相关的结果违反直觉，此前尚未见报道。虽然不能代表足够有力的证据来改变临床实践，但像这些证实和可靠的结果应该作为研究的导火索，并促进对疼痛和患者结局之间意想不到的联系的进一步研究。随着频繁的电子健康档案二次分析的到来，这样违反直觉的数据结果很可能会变得更加频繁。我们以扩展的方式讨论反直觉数据的问题，包括这种现象的可能原因和方法。
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英文标题：
《Analyzing counterintuitive data》
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作者：
E. Doty, N. McCague, D.J. Stone, L.A. Celi
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最新提交年份：
2018
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分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
Purpose: To explore the issue of counterintuitive data via analysis of a representative case and further discussion of those situations in which the data appear to be inconsistent with current knowledge. Case: 844 postoperative CABG patients, who were extubated within 24 hours of surgery were identified in a critical care database (MIMIC-III). Nurse elicited pain scores were documented throughout their hospital stay on a scale of 0 to 10. Levels were tracked as mean, median, and maximum values, and categorized as no (0/10), mild (1-3), moderate (4-6) and severe pain (7-10). Regression analysis was employed to analyze the relationship between pain scores and outcomes of interest (mortality and hospital LOS). After covariate adjustment, increased levels of pain were found to be associated with lower mortality rates and reduced hospital LOS. Conclusion: These counterintuitive results for post-CABG pain related outcomes have not been previously reported. While not representing strong enough evidence to alter clinical practice, confirmed and reliable results such as these should serve as a research trigger and prompt further studies into unexpected associations between pain and patient outcomes. With the advent of frequent secondary analysis of electronic health records, such counterintuitive data results are likely to become more frequent. We discuss the issue of counterintuitive data in extended fashion, including possible reasons for, and approaches to, this phenomenon.
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PDF链接：
https://arxiv.org/pdf/1806.05547
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