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挪威创伤生存预测模型在芬兰南部严重创伤后创伤情况中的外部验证

External validation of the Norwegian survival prediction model in trauma after major trauma in Southern Finland.

作者信息

Raj R, Brinck T, Skrifvars M B, Handolin L

机构信息

Department of Neurosurgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Töölö Trauma Unit, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

出版信息

Acta Anaesthesiol Scand. 2016 Jan;60(1):48-58. doi: 10.1111/aas.12592. Epub 2015 Aug 6.

Abstract

BACKGROUND

The Norwegian Survival Prediction Model in Trauma (NORMIT) is a newly developed outcome prediction model for patients with trauma. We aimed to compare the novel NORMIT to the more commonly used Trauma and Injury Severity Score (TRISS) in Finnish trauma patients.

METHODS

We performed a retrospective open-cohort study, using the trauma registry of Helsinki university hospital's trauma unit, including severely injured patients (new injury severity score > 15) admitted from 2007 to 2011. We used 30-day in-hospital mortality as the primary outcome, and discharge functional outcome as a secondary outcome of interest. Model performance was evaluated by comparing discrimination (by area under the receiver operating characteristic curve [AUC]), using a re-sample bootstrap technique, and by assessing calibration (GiViTI belt).

RESULTS

We identified 1111 patients fulfilling the study inclusion criteria. Overall mortality was 13% (n = 147). NORMIT showed slightly better discrimination for mortality prediction (AUC = 0.83, 95% confidence interval [CI] = 0.80-0.86 vs. AUC = 0.79, 95% CI = 0.75-0.83, P = 0.004) and functional outcome prediction (AUC = 0.78, 95% CI = 0.76-0.82 vs. AUC = 0.75, 95% CI = 0.72-0.78, P < 0.001) than TRISS. Calibration testing revealed poor calibration for both NORMIT and TRISS (P < 0.001), by giving too pessimistic predictions (predicted survival significantly lower than actual survival).

CONCLUSION

NORMIT and TRISS showed good discrimination, but poor calibration, in this mixed cohort of severely injured trauma patients from Southern Finland. We found NORMIT to be a feasible alternative to TRISS for trauma patient outcome prediction, but trauma prediction models with improved calibration are needed.

摘要

背景

挪威创伤生存预测模型(NORMIT)是一种新开发的创伤患者结局预测模型。我们旨在比较新型的NORMIT与芬兰创伤患者中更常用的创伤和损伤严重程度评分(TRISS)。

方法

我们进行了一项回顾性开放队列研究,使用赫尔辛基大学医院创伤科的创伤登记数据,纳入2007年至2011年收治的重伤患者(新损伤严重程度评分>15)。我们将30天院内死亡率作为主要结局,将出院时的功能结局作为感兴趣的次要结局。通过使用重复抽样自举技术比较辨别力(通过受试者操作特征曲线下面积[AUC])以及评估校准(GiViTI带)来评估模型性能。

结果

我们确定了1111名符合研究纳入标准的患者。总体死亡率为13%(n = 147)。NORMIT在死亡率预测(AUC = 0.83,95%置信区间[CI] = 0.80 - 0.86,而TRISS的AUC = 0.79,95% CI = 0.75 - 0.83,P = 0.004)和功能结局预测(AUC = 0.78,95% CI = 0.76 - 0.82,而TRISS的AUC = 0.75,95% CI = 0.72 - 0.78,P < 0.001)方面显示出略好的辨别力。校准测试显示NORMIT和TRISS的校准均较差(P < 0.001),因为给出的预测过于悲观(预测生存率显著低于实际生存率)。

结论

在芬兰南部这个重伤创伤患者的混合队列中,NORMIT和TRISS显示出良好的辨别力,但校准较差。我们发现NORMIT是TRISS用于创伤患者结局预测的可行替代方法,但需要校准得到改善的创伤预测模型。

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