Granholm Anders, Perner Anders, Krag Mette, Hjortrup Peter Buhl, Haase Nicolai, Holst Lars Broksø, Marker Søren, Collet Marie Oxenbøll, Jensen Aksel Karl Georg, Møller Morten Hylander
Department of Intensive Care 4131, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark.
Centre for Research in Intensive Care, Copenhagen, Denmark.
BMJ Open. 2017 Mar 9;7(3):e015339. doi: 10.1136/bmjopen-2016-015339.
Mortality prediction scores are widely used in intensive care units (ICUs) and in research, but their predictive value deteriorates as scores age. Existing mortality prediction scores are imprecise and complex, which increases the risk of missing data and decreases the applicability bedside in daily clinical practice. We propose the development and validation of a new, simple and updated clinical prediction rule: the Simplified Mortality Score for use in the Intensive Care Unit (SMS-ICU).
During the first phase of the study, we will develop and internally validate a clinical prediction rule that predicts 90-day mortality on ICU admission. The development sample will comprise 4247 adult critically ill patients acutely admitted to the ICU, enrolled in 5 contemporary high-quality ICU studies/trials. The score will be developed using binary logistic regression analysis with backward stepwise elimination of candidate variables, and subsequently be converted into a point-based clinical prediction rule. The general performance, discrimination and calibration of the score will be evaluated, and the score will be internally validated using bootstrapping. During the second phase of the study, the score will be externally validated in a fully independent sample consisting of 3350 patients included in the ongoing Stress Ulcer Prophylaxis in the Intensive Care Unit trial. We will compare the performance of the SMS-ICU to that of existing scores.
We will use data from patients enrolled in studies/trials already approved by the relevant ethical committees and this study requires no further permissions. The results will be reported in accordance with the Transparent Reporting of multivariate prediction models for Individual Prognosis Or Diagnosis (TRIPOD) statement, and submitted to a peer-reviewed journal.
死亡率预测评分在重症监护病房（ICU）和研究中被广泛应用，但随着评分时间的推移，其预测价值会下降。现有的死亡率预测评分不精确且复杂，这增加了数据缺失的风险，并降低了在日常临床实践中的床边适用性。我们提议开发并验证一种新的、简单且更新的临床预测规则：用于重症监护病房的简化死亡率评分（SMS-ICU）。
在研究的第一阶段，我们将开发并进行内部验证一种临床预测规则，该规则可预测ICU入院时的90天死亡率。开发样本将包括4247名急性入住ICU的成年危重症患者，这些患者来自5项当代高质量的ICU研究/试验。该评分将使用二元逻辑回归分析并通过向后逐步排除候选变量来开发，随后转换为基于点数的临床预测规则。将评估该评分的总体性能、区分度和校准度，并使用自抽样法进行内部验证。在研究的第二阶段，该评分将在一个完全独立的样本中进行外部验证，该样本由正在进行的ICU应激性溃疡预防试验中纳入的3350名患者组成。我们将比较SMS-ICU与现有评分的性能。
我们将使用已获相关伦理委员会批准的研究/试验中患者的数据，本研究无需进一步的许可。结果将按照个体预后或诊断多变量预测模型的透明报告（TRIPOD）声明进行报告，并提交给同行评审期刊。
