Suppr超能文献

从非梗阻性肥厚型心肌病中识别梗阻性肥厚型心肌病:基于心电图特征的模型的建立和验证。

Identifying Obstructive Hypertrophic Cardiomyopathy from Nonobstructive Hypertrophic Cardiomyopathy: Development and Validation of a Model Based on Electrocardiogram Features.

机构信息

Department of Cardiology, Xijing Hospital, the Fourth Military Medical University, Xi'an, Shaanxi, China.

Department of Ultrasound, Xijing Hospital, the Fourth Military Medical University, Xi'an, Shaanxi, China.

出版信息

Glob Heart. 2023 Aug 4;18(1):40. doi: 10.5334/gh.1250. eCollection 2023.

Abstract

BACKGROUND

The clinical presentation and prognosis of hypertrophic cardiomyopathy (HCM) are heterogeneous between nonobstructive HCM (HNCM) and obstructive HCM (HOCM). Electrocardiography (ECG) has been used as a screening tool for HCM. However, it is still unclear whether the features presented on ECG could be used for the initial classification of HOCM and HNCM.

OBJECTIVE

We aimed to develop a pragmatic model based on common 12-lead ECG features for the initial identification of HOCM/HNCM.

METHODS

Between April 1 and September 30, 2020, 172 consecutive HCM patients from the International Cooperation Center for Hypertrophic Cardiomyopathy of Xijing Hospital were prospectively included in the training cohort. Between January 4 and February 30, 2021, an additional 62 HCM patients were prospectively included in the temporal internal validation cohort. External validation was performed using retrospectively collected ECG data with definite classification (390 HOCM and 499 HNCM ECG samples) from January 1, 2010 to March 31, 2020. Multivariable backward logistic regression (LR) was used to develop the prediction model. The discrimination performance, calibration and clinical utility of the model were evaluated.

RESULTS

Of all 30 acquired ECG parameters, 10 variables were significantly different between HOCM and HNCM (all < 0.05). The P wave interval and SV1 were selected to construct the model, which had a clearly useful C-statistic of 0.805 (0.697, 0.914) in the temporal validation cohort and 0.776 (0.746, 0.806) in the external validation cohort for differentiating HOCM from HNCM. The calibration plot, decision curve analysis, and clinical impact curve indicated that the model had good fitness and clinical utility.

CONCLUSION

The pragmatic model constructed by the P wave interval and SV1 had a clearly useful ability to discriminate HOCM from HNCM. The model might potentially serve as an initial classification of HCM before referring patients to dedicated centers and specialists.

HIGHLIGHTS

Evident differences exist in the ECG presentations between HOCM and HNCM.To the best of our knowledge, this study is the first piece of evidence to quantify the difference in the ECG presentations between HOCM and HNCM.Based on routine 12-lead ECG data, a probabilistic model was generated that might assist in the initial classification of HCM patients.

摘要

背景

肥厚型心肌病(HCM)的临床表现和预后在非梗阻性 HCM(HNCM)和梗阻性 HCM(HOCM)之间存在异质性。心电图(ECG)已被用作 HCM 的筛查工具。然而,目前尚不清楚 ECG 上的特征是否可用于 HOCM 和 HNCM 的初步分类。

目的

我们旨在基于常见的 12 导联 ECG 特征建立一种实用模型,用于初步识别 HOCM/HNCM。

方法

2020 年 4 月 1 日至 9 月 30 日,来自西京医院国际肥厚型心肌病合作中心的 172 例连续 HCM 患者前瞻性纳入训练队列。2021 年 1 月 4 日至 2 月 30 日,另外 62 例 HCM 患者前瞻性纳入时间内部验证队列。使用从 2010 年 1 月 1 日至 2020 年 3 月 31 日期间回顾性收集的具有明确分类的 ECG 数据(390 例 HOCM 和 499 例 HNCM ECG 样本)进行外部验证。采用多变量向后逻辑回归(LR)建立预测模型。评估模型的判别性能、校准和临床实用性。

结果

在所有 30 个获得的 ECG 参数中,HOCM 和 HNCM 之间有 10 个变量存在显著差异(均<0.05)。选择 P 波间隔和 SV1 构建模型,在时间验证队列中,该模型对区分 HOCM 和 HNCM 的清晰有用 C 统计量为 0.805(0.697,0.914),在外部验证队列中为 0.776(0.746,0.806)。校准图、决策曲线分析和临床影响曲线表明,该模型具有良好的拟合度和临床实用性。

结论

由 P 波间隔和 SV1 构建的实用模型具有明确区分 HOCM 和 HNCM 的能力。该模型可能有助于在将患者转介至专门中心和专家之前,对 HCM 进行初步分类。

重点

HOCM 和 HNCM 之间的心电图表现存在明显差异。据我们所知,这是首次对 HOCM 和 HNCM 之间的心电图表现差异进行量化的研究。基于常规 12 导联 ECG 数据,生成了一个概率模型,可能有助于对 HCM 患者进行初步分类。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a62d/10402817/8c705334fde6/gh-18-1-1250-g1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验