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投身于一项流体试验中。

Gone fishing in a fluid trial.

作者信息

Hjortrup Peter B, Haase Nicolai, Wetterslev Jørn, Perner Anders

机构信息

Department of Intensive Care, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark.

Copenhagen Trial Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark.

出版信息

Crit Care Resusc. 2016 Mar;18(1):55-8.

PMID:26947417
Abstract

OBJECTIVE

To maximise the yield of existing data by assessing the effect on mortality of being born under the zodiac sign Pisces in a trial of intravenous (IV) fluids.

DESIGN, SETTING AND PARTICIPANTS: A retrospective observational study, with no predefined hypothesis or statistical analysis plan, of 26 Scandinavian intensive care units between 2009 and 2011. Patients aged 18 years or older with severe sepsis and in need of fluid resuscitation, randomised in the Scandinavian Starch for Severe Sepsis/ Septic Shock (6S) trial.

MAIN OUTCOME MEASURE

Ninety-day mortality.

RESULTS

We included all 798 randomised patients in our study; 70 (9%) were born under the sign of Pisces. The primary outcome (death within 90 days after randomisation) occurred in 25 patients (35.7%) in the Pisces group, compared with 348 patients (48%) in the non-Pisces group (relative risk, 0.75; 95% CI, 0.54-1.03; one-sided P = 0.03).

CONCLUSIONS

In a multicentre randomised clinical trial of IV fluids, being born under the sign of Pisces was associated with a decreased risk of death. Our study shows that with convenient use of statistics and an enticing explanatory hypothesis, it is possible to achieve significant findings in post-hoc analyses of data from large trials.

摘要

目的

在一项静脉输液试验中,通过评估出生于双鱼座对死亡率的影响,使现有数据的产出最大化。

设计、背景和参与者:一项回顾性观察性研究,无预先设定的假设或统计分析计划,研究对象为2009年至2011年期间的26个斯堪的纳维亚重症监护病房。年龄在18岁及以上、患有严重脓毒症且需要液体复苏的患者,这些患者被随机纳入斯堪的纳维亚重症脓毒症/感染性休克淀粉研究(6S)试验。

主要结局指标

90天死亡率。

结果

我们的研究纳入了所有798名随机分组的患者;70名(9%)出生于双鱼座。双鱼座组有25名患者(35.7%)出现主要结局(随机分组后90天内死亡),而非双鱼座组有348名患者(48%)出现该结局(相对风险,0.75;95%置信区间,0.54 - 1.03;单侧P = 0.03)。

结论

在一项关于静脉输液的多中心随机临床试验中,出生于双鱼座与死亡风险降低相关。我们的研究表明,通过方便地运用统计学方法和一个诱人的解释性假设,有可能在大型试验数据的事后分析中获得显著结果。

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