Domain validation of the CRASH prognostic model for predicting 14-day mortality among patients and traumatic brain injury and intracranial hemorrhage in a Thai emergency department.

IF 2 Q2 EMERGENCY MEDICINE
Welawat Tienpratarn, Phichayut Phinyo, Chaiyaporn Yuksen, Sirote Wongwaisayawan, Jiraporn Khorana, Jayanton Patumanond
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引用次数: 0

Abstract

Background: Traumatic brain injury (TBI) is a significant health concern, with intracranial haemorrhage (ICH) being a common complication following injury. The CRASH prediction model plays a crucial role in clinical prognostication and decision-making within this patient group. However, external validation is critical to ensure the model's validity and applicability across different populations and settings beyond those in which it was originally developed. This study aimed to validate the CRASH prediction model for 14-day mortality among TBI patients with ICH presenting to a Thai emergency department.

Methods: This retrospective study included adult TBI patients with ICH who visited the emergency department (ED) at Ramathibodi Hospital, Thailand, between 2020 and 2022. The Basic model, which incorporates age, Glasgow Coma Scale (GCS) score (3-15), pupillary reaction, and major extracranial injury, and the CT model, which extends the Basic model by including CT findings, were evaluated for their discriminative ability and calibration.

Results: A total of 232 patients were included in the validation dataset. Significant differences in clinical characteristics were observed between the datasets, including older age, predominance of mild TBI, subarachnoid hemorrhage, and non-evacuated hematoma in the validation dataset. The observed 14-day mortality rate in this cohort was 9.1%, compared to 20.7% in the development dataset. The area under the receiver operating characteristics curve (AuROC) was 0.92 (95% CI: 0.84, 1.00) for the Basic model and 0.93 (95% CI: 0.86, 1.00) for the CT model. However, the calibration for both models was fair. Recalibration achieved better predictive accuracy and reduced overestimation in high-risk groups.

Conclusion: The original CRASH prediction model demonstrates strong discriminative ability for predicting 14-day mortality in TBI patients; however, significant miscalibration was observed. Recalibration was therefore undertaken to improve the model's generalisability to local populations. Nonetheless, further studies are warranted to confirm the consistency and applicability of the recalibrated models.

CRASH预测泰国急诊科创伤性脑损伤和颅内出血患者14天死亡率的预测模型的领域验证
背景:外伤性脑损伤(TBI)是一个重要的健康问题,颅内出血(ICH)是损伤后常见的并发症。CRASH预测模型在该患者群体的临床预测和决策中起着至关重要的作用。然而,外部验证对于确保模型在不同人群和环境中的有效性和适用性至关重要,而不仅仅是在最初开发模型的人群和环境中。本研究旨在验证在泰国急诊科就诊的合并脑出血的TBI患者14天死亡率的CRASH预测模型。方法:本回顾性研究纳入了2020年至2022年期间在泰国Ramathibodi医院急诊科(ED)就诊的合并脑出血的成年TBI患者。基本模型包括年龄、格拉斯哥昏迷评分(GCS)评分(3-15)、瞳孔反应和主要颅外损伤,CT模型通过包括CT表现扩展了基本模型,对其判别能力和校准进行了评估。结果:共有232例患者被纳入验证数据集。临床特征在数据集之间存在显著差异,包括年龄较大、轻度TBI的优势、蛛网膜下腔出血和验证数据集中的非排出性血肿。在该队列中观察到的14天死亡率为9.1%,而在发展数据集中为20.7%。基本模型的受试者工作特征曲线下面积(AuROC)为0.92 (95% CI: 0.84, 1.00), CT模型的受试者工作特征曲线下面积为0.93 (95% CI: 0.86, 1.00)。然而,两个模型的校准都是公平的。在高危人群中,重新校准获得了更好的预测准确性,并减少了高估。结论:原始CRASH预测模型对预测TBI患者14天死亡率具有较强的判别能力;然而,观察到明显的误校准。因此,进行了重新校准,以提高模式对当地人口的普遍性。尽管如此,需要进一步的研究来证实重新校准模型的一致性和适用性。
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来源期刊
CiteScore
4.60
自引率
0.00%
发文量
63
审稿时长
13 weeks
期刊介绍: The aim of the journal is to bring to light the various clinical advancements and research developments attained over the world and thus help the specialty forge ahead. It is directed towards physicians and medical personnel undergoing training or working within the field of Emergency Medicine. Medical students who are interested in pursuing a career in Emergency Medicine will also benefit from the journal. This is particularly useful for trainees in countries where the specialty is still in its infancy. Disciplines covered will include interesting clinical cases, the latest evidence-based practice and research developments in Emergency medicine including emergency pediatrics.
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