Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients

格拉斯哥昏迷指数 医学 逻辑回归 创伤性脑损伤 第三脑室 蓄水池 沙希德 队列 统计的 外科 内科学 统计 精神科 哲学 神学 考古 数学 历史
作者
Pablo Perel,Miguel Arango,Tim Clayton,Phil Edwards,Morenikeji Komolafe,Stuart Poccock,Ian Roberts,Haleema Shakur‐Still,Ewout W. Steyerberg,Surakrant Yutthakasemsunt
出处
期刊:BMJ [BMJ]
卷期号:336 (7641): 425-429 被引量:1124
标识
DOI:10.1136/bmj.39461.643438.25
摘要

Objective To develop and validate practical prognostic models for death at 14 days and for death or severe disability six months after traumatic brain injury. Design Multivariable logistic regression to select variables that were independently associated with two patient outcomes. Two models designed: “basic” model (demographic and clinical variables only) and “CT” model (basic model plus results of computed tomography). The models were subsequently developed for high and low-middle income countries separately. Setting Medical Research Council (MRC) CRASH Trial. Subjects 10 008 patients with traumatic brain injury. Models externally validated in a cohort of 8509. Results The basic model included four predictors: age, Glasgow coma scale, pupil reactivity, and the presence of major extracranial injury. The CT model also included the presence of petechial haemorrhages, obliteration of the third ventricle or basal cisterns, subarachnoid bleeding, midline shift, and non-evacuated haematoma. In the derivation sample the models showed excellent discrimination (C statistic above 0.80). The models showed good calibration graphically. The Hosmer-Lemeshow test also indicated good calibration, except for the CT model in low-middle income countries. External validation for unfavourable outcome at six months in high income countries showed that basic and CT models had good discrimination (C statistic 0.77 for both models) but poorer calibration. Conclusion Simple prognostic models can be used to obtain valid predictions of relevant outcomes in patients with traumatic brain injury.
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