共识还是数据来源的解剖严重性评分?

Lynne Moore, André Lavoie, Natalie Le Sage, Eric Bergeron
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引用次数: 0

摘要

我们的目的是比较共识衍生和数据衍生的损伤严重程度评分在单独考虑和结合年龄和生理状态时的预测准确性。分析基于25111例患者。每个严重程度评分的预测效度在预测住院死亡率的逻辑回归模型中使用判别和校准措施进行评估。在单变量模型中,数据衍生的评分始终比共识衍生的评分具有更好的预测准确性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consensus or data-derived anatomical severity scoring?

We aimed to compare the predictive accuracy of consensus-derived and data-derived injury severity scores when considered alone and in combination with age and physiological status. Analyses were based on 25,111 patients. The predictive validity of each severity score was evaluated in logistic regression models predicting in-hospital mortality using measures of discrimination and calibration. Data-derived scores had consistently better predictive accuracy than consensus-derived scores in univariate models (p<0.0001) but very little difference between scores was observed in models including information on age and physiological status. Data-derived scores provide more accurate mortality prediction than consensus-derived scores when only anatomic injury severity is considered but offer little advantage if age and physiological status are taken into account.

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