Physiotherapy Dept, Morriston Hospital, Swansea Bay University Health Board, Swansea, Wales, SA6 6NL, UK.
Swansea Trials Unit, Swansea University Medical School, Swansea University, Swansea, UK.
BMC Emerg Med. 2024 Oct 12;24(1):189. doi: 10.1186/s12873-024-01107-6.
The aim of this systematic review was to investigate how clinical prediction models compare in terms of their methodological development, validation, and predictive capabilities, for patients with blunt chest trauma presenting to the Emergency Department.
A systematic review was conducted across databases from 1st Jan 2000 until 1st April 2024. Studies were categorised into three types of multivariable prediction research and data extracted regarding methodological issues and the predictive capabilities of each model. Risk of bias and applicability were assessed.
41 studies were included that discussed 22 different models. The most commonly observed study design was a single-centre, retrospective, chart review. The most widely externally validated clinical prediction models with moderate to good discrimination were the Thoracic Trauma Severity Score and the STUMBL Score.
This review demonstrates that the predictive ability of some of the existing clinical prediction models is acceptable, but high risk of bias and lack of subsequent external validation limits the extensive application of the models. The Thoracic Trauma Severity Score and STUMBL Score demonstrate better predictive accuracy in both development and external validation studies than the other models, but require recalibration and / or update and evaluation of their clinical and cost effectiveness.
PROSPERO database ( https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=351638 ).
本系统评价的目的是调查针对因钝性胸部创伤而到急诊科就诊的患者，临床预测模型在方法学开发、验证和预测能力方面的比较情况。
我们在 2000 年 1 月 1 日至 2024 年 4 月 1 日期间在数据库中进行了系统评价。研究分为三种多变量预测研究类型，并提取了关于每个模型的方法学问题和预测能力的数据。评估了风险偏差和适用性。
共纳入 41 项研究，讨论了 22 个不同的模型。最常见的观察性研究设计是单中心、回顾性、图表回顾。具有中等至良好区分度的最广泛外部验证的临床预测模型是胸外伤严重程度评分和 STUMBL 评分。
本综述表明，一些现有临床预测模型的预测能力是可以接受的，但高风险偏差和缺乏后续外部验证限制了模型的广泛应用。胸外伤严重程度评分和 STUMBL 评分在开发和外部验证研究中均显示出比其他模型更高的预测准确性，但需要重新校准和/或更新，并评估其临床和成本效益。
PROSPERO 数据库（https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=351638）。
