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首页> 外文期刊>The Journal of trauma >Blunt Cerebrovascular Injury Is Poorly Predicted by Modeling With Other Injuries: Analysis of NTDB Data.
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Blunt Cerebrovascular Injury Is Poorly Predicted by Modeling With Other Injuries: Analysis of NTDB Data.

机译:通过与其他伤害进行建模,可预测的钝性脑血管伤害很差:NTDB数据分析。

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BACKGROUND: : Traumatic blunt cerebrovascular injury (BCVI) may portend catastrophic complications if untreated. Who should be screened for BCVI is controversial. The purpose of this study was to develop and validate a prediction score (pBCVI) to identify those at sufficient risk to warrant dedicated screening. METHODS: : We conducted a cohort study using data for years 2002-2007 from the National Trauma Data Bank. Blunt trauma patients aged 16 years and older were randomly divided into two groups for score creation and validation. Final prediction model included age, sex, Trauma Mortality Prediction Model p(death), traumatic intracranial hemorrhage, cerebellar/brain stem injury, malar/maxillary fracture, mandible fracture, cervical spine fracture, cervical spinal cord injury, thoracic spinal cord injury, and chest Abbreviated Injury Scale >/=3. pBCVI was evaluated using receiver operating characteristic curve area and the Hosmer-Lemeshow statistic. The Youden Index estimated an optimal cut-point (J) of the pBCVI. RESULTS: : The cohort numbered 1,398,310 patients, including 2,125 with BCVI. The overall incidence of BCVI was 0.15%. Cervical spine fracture had the strongest association with BCVI (odds ratio 4.82, p < 0.001). The receiver operating characteristic curve for pBCVI was 0.93 and the Hosmer-Lemeshow statistic was 206.3, p < 0.01. The optimal cut-point (J) of pBCVI was 0.0013 (sensitivity 0.91, specificity 0.82) and would miss 186 (8.8%) injuries in our cohort. To identify all BCVI using this model, an unrealistic 96% of the cohort would require screening. CONCLUSIONS: : A model based on a pattern of other injuries cannot be used as a stand-alone instrument to determine screening for BCVI. "Optimal" model cut-points are not ideal for all injuries. Clinical suspicion that integrates energy of mechanism and associated injuries remains essential to effectively screen for BCVI and minimize patient risk for a catastrophic missed injury.
机译:背景:如果不进行治疗,创伤性钝性脑血管损伤(BCVI)可能预示着灾难性并发症。谁应该接受BCVI筛查是有争议的。这项研究的目的是开发和验证预测评分(pBCVI),以识别有足够风险进行专项筛查的人。方法::我们使用来自国家创伤数据库的2002-2007年数据进行了队列研究。将年龄在16岁及以上的钝性创伤患者随机分为两组,进行评分创建和验证。最终预测模型包括年龄,性别,创伤死亡率预测模型p(死亡),颅内外伤,小脑/脑干损伤,黄斑/上颌骨骨折,下颌骨骨折,颈椎骨折,颈椎脊髓损伤,胸椎脊髓损伤和胸部简短伤害量表> / = 3。使用接收器工作特征曲线面积和Hosmer-Lemeshow统计量评估pBCVI。尤登指数估计了pBCVI的最佳切点(J)。结果:该队列共有1,398,310名患者,其中2,125名患有BCVI。 BCVI的总发生率为0.15%。颈椎骨折与BCVI的关联最强(比值比为4.82,p <0.001)。 pBCVI的接收器工作特性曲线为0.93,Hosmer-Lemeshow统计量为206.3,p <0.01。 pBCVI的最佳切点(J)为0.0013(敏感性0.91,特异性0.82),在我们的研究组中将错过186次(8.8%)的伤害。要使用此模型识别所有BCVI,不现实的96%队列将需要进行筛查。结论::基于其他损伤模式的模型不能用作确定BCVI筛查的独立工具。 “最佳”模型切割点并不适合所有伤害。整合机制和相关伤害的能量的临床怀疑对于有效筛查BCVI并最大程度地降低患者发生灾难性遗漏伤害的风险仍然至关重要。

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