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Received:November 26, 2022 Published Online:June 20, 2023
Received:November 26, 2022 Published Online:June 20, 2023
中文摘要: 目的 基于胸痛中心数据库,构建急性肺血栓栓塞症(PTE)的早期诊断模型。 方法 根据济宁医学院附属医院胸痛中心数据库,回顾性收集2020年1月至12月因急性胸痛急诊的患者临床资料,按照是否诊断PTE分为PTE组和非PTE胸痛组,对两组患者的临床相关指标进行比较,将两组间有统计学差异的研究指标纳入多因素logistic回归分析,并建立PTE早期诊断列线图模型;绘制模型的ROC以评估预测准确度,利用Hosmer-Lemeshow检验验证模型拟合优度。另收集2021年1月至3月就诊的胸痛患者资料共654例对模型进行外部验证。 结果 共纳入2 738例患者用于构建模型,其中确诊的PTE患者117例(4.27%)。多因素分析显示,手术外伤史、下肢制动/卧床>3 d、伴呼吸困难、伴晕厥、低入院脉搏血氧饱和度(SpO2)、高D-二聚体、心电图电轴右偏和完全性右束支传导阻滞是胸痛患者诊断PTE的独立因素(P<0.05)。ROC曲线分析显示,内部验证数据曲线下面积为0.985(95%CI:0.969~0.999),外部验证数据曲线下面积为0.924(95%CI:0.872~0.977),显示该模型有较好的区分度。Hosmer-Lemeshow拟合优度检验显示,内部验证(χ2=14.077, P=0.080)和外部验证(χ2=-615.69, P=0.986)均表明该模型可以很好的拟合。 结论 本研究构建了急性胸痛患者诊断PTE的列线图模型,该模型可有效的预测急性胸痛患者发生PTE的风险概率。
Abstract:Objective To construct an early diagnosis model of acute pulmonary thromboembolism (PTE) based on chest pain center database. Methods According to the database of Chest Pain Center of Affiliated Hospital of Jining Medical University, the clinical data of patients who visited the emergency department from January to December 2020 were retrospectively collected, and the patients were divided into PTE group and non-PTE chest pain group according to whether diagnosed PTE. The clinically relevant indicators of the two groups were compared, and the study indicators with statistical differences between the two groups were included in the multivariate logistic regression analysis, and a nomogram model for the early diagnosis of PTE was established. The receiver operating characteristic (ROC) curve of the model was plotted to assess the predictive accuracy, and the model was tested for goodness of fit using the Hosmer-Lemeshow test. An additional 654 patients presenting with chest pain between January 2021 and March 2021 were collected to externally validate the model. Results A total of 2 738 patients were included for the construction of the model, of whom 117 (4.27%) had confirmed PTE. On multivariate analysis, a history of surgical trauma, > 3 d of immobilization / bed rest on the lower extremities, with dyspnea, syncope, low pulse oxygen staturation (SpO2) at admission, high D-dimer, right deviation of electrocardiographic axis, and complete right bundle branch block were independent factors for the diagnosis of PTE in patients with chest pain (P<0.05) . ROC curve analysis showed that the area under the curve was 0.985 (95%CI: 0.969-0.999) in internal validation data and 0.924 (95%CI: 0.872-0.977) in external validation data, showing that the model had a good discrimination. The goodness of fit test was performed using Hosmer-Lemeshow, and validated internally (χ2=14.077, P=0.080) and external validation (χ2=615.690, P=0.986) both indicating a good fit of the model. Conclusion This study constructed a nomogram model for the diagnosis of PTE in patients with acute chest pain, and this model could effectively predict the risk probability of PTE in patients with acute chest pain.
keywords: Pulmonary embolism Pulmonary thromboembolism Chest pain Chest pain center Early diagnosis Nomogram
文章编号: 中图分类号:R563.5 文献标志码:A
基金项目:山东省医药卫生科技发展计划资助项目 (202010000964); 济宁市重点研发计划资助项目 (2022YXNS045); 济宁 医学院附属医院 “苗圃” 科研计划资助项目 (MP-MS-2020-006)
Author Name | Affiliation |
WANG Xinyan, LI Yong, XIAO Ziya, MENG Fanliang, LYU Tingting, GUO Xiangjie | Emergency Department, Affiliated Hospital of Jining Medical University, Jining, Shandong 272029, China |
Author Name | Affiliation |
WANG Xinyan, LI Yong, XIAO Ziya, MENG Fanliang, LYU Tingting, GUO Xiangjie | Emergency Department, Affiliated Hospital of Jining Medical University, Jining, Shandong 272029, China |
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