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扩张型心肌病合并肺动脉高压的预测模型。

A predictive model for dilated cardiomyopathy with pulmonary hypertension.

机构信息

The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.

Guangzhou University of Chinese Medicine, Guangzhou, China.

出版信息

ESC Heart Fail. 2021 Oct;8(5):4255-4264. doi: 10.1002/ehf2.13535. Epub 2021 Aug 2.

Abstract

AIMS

Dilated cardiomyopathy (DCM) is defined as a serious cardiac disorder caused by the presence of left ventricular dilatation and contractile dysfunction in the absence of severe coronary artery disease and abnormal loading conditions. The incidence of cardiac death is markedly higher in patients with DCM with pulmonary hypertension (PH) than in DCM patients without PH. No previous studies have constructed a predictive model to predict PH in patients with DCM.

METHODS

Data from 218 DCM patients (68.3% man; mean age 57.33) were collected. Patients were divided into low, intermediate and high PH-risk groups based on the echocardiographic assessment at the tricuspid regurgitation peak velocity (TRV) in conjunction with the presence of echocardiographic signs from at least two different categories. Basic information, vital signs, comorbidities and biochemical data of each patient were determined. The impact of each parameter on PH probability was analysed by univariable and multivariable analyses, the data from which were employed to establish a predictive model. Finally, the discriminability, calibration ability and clinical efficacy of the model were verified for both the modelling group and the external validation group.

RESULTS

We successfully applied a history of chronic obstructive pulmonary disease (COPD) or chronic bronchitis, systolic murmur (SM) at the tricuspid area, SM at the apex and brain natriuretic peptide (BNP) level to establish a model for predicting PH probability in DCM. The model was proven to have high accuracy and good discriminability (area under the receiver operating characteristic curve 0.889), calibration ability and clinical application value.

CONCLUSIONS

A model for predicting PH probability in patients with DCM was successfully established. The new model is reliable for predicting PH probability in DCM and has good clinical applicability.

摘要

目的

扩张型心肌病(DCM)是一种严重的心脏疾病,其特征为左心室扩张和收缩功能障碍,而不存在严重的冠状动脉疾病和异常负荷情况。与无肺动脉高压(PH)的 DCM 患者相比,患有 PH 的 DCM 患者的心脏死亡发生率明显更高。之前没有研究构建过预测 DCM 患者 PH 的预测模型。

方法

共收集了 218 名 DCM 患者(68.3%为男性;平均年龄 57.33 岁)的数据。根据三尖瓣反流峰值速度(TRV)的超声心动图评估,并结合至少两个不同类别的超声心动图征象,将患者分为低、中、高 PH 风险组。确定每位患者的基本信息、生命体征、合并症和生化数据。通过单变量和多变量分析,分析每个参数对 PH 概率的影响,根据这些数据建立预测模型。最后,对模型在建模组和外部验证组中的区分能力、校准能力和临床疗效进行验证。

结果

我们成功地应用了慢性阻塞性肺疾病(COPD)或慢性支气管炎病史、三尖瓣区收缩期杂音(SM)、心尖区 SM 和脑钠肽(BNP)水平来建立预测 DCM 患者 PH 概率的模型。该模型具有较高的准确性和良好的区分能力(受试者工作特征曲线下面积 0.889)、校准能力和临床应用价值。

结论

成功建立了预测 DCM 患者 PH 概率的模型。该新模型可可靠地预测 DCM 患者 PH 概率,具有良好的临床适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4263/8497218/131ccbda678e/EHF2-8-4255-g003.jpg

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